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Igor Boiko

The Petroleum Institute, Electrical Engineering, Faculty Member

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Dr. Igor Boiko has MSc, PhD and DSc (Habil.) degrees in electromechanical engineering and control system engineering. He has known for his research contributions in the areas of dynamic systems, discontinuous control, sliding mode control, frequency-domain methods and PID controller tuning. In particular, he developed such methods and concepts as LPRS method, dynamic harmonic balance, phase deficit, fractal dynamics, and optimal non-parametric controller tuning. Over his career, Dr. Boiko led research projects in the areas of control of various process systems in the oil and gas industry, control of pneumatic and electric servomechanisms and drives, unmanned aerial vehicle control, power converter control, optimal PID tuning, applied mathematics. He also worked for 15 years in the petrochemical industry and held leading positions in control system development on such multi-billion projects as Syncrude UE-1 and Shell Albian Sands (both in Alberta, Canada). He has authored/co-authored four books and over 200 journal and conference papers, book chapters. Dr. Boiko is a Fellow (Academician) of Russian Academy of Natural Sciences, a Senior Member of IEEE.

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Konkuk University

University of Cologne

Evangelos Papadopoulos

National Technical University of Athens

Benedetto Allotta

Università degli Studi di Firenze (University of Florence)

Armando Marques-Guedes

UNL - New University of Lisbon

Chiara Maria Mauro

Universidad Complutense de Madrid

Andrea Cherubini

LIRMM

Emilia Mataix Ferrándiz

Universitat Internacional de Catalunya

Gigih Priyandoko

Indrazno Siradjuddin

State Polytechnic Of Malang

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Papers by Igor Boiko

Discontinuous Control Systems

Birkhäuser Boston eBooks, 2009

By means of some simple examples from economics, we elucidate certain solution tools for the solu... more By means of some simple examples from economics, we elucidate certain solution tools for the solution of optimal control problems were the system under study undergoes major changes when certain boundaries are crossed. The "major changes" may be that the state gets a jump discontinuity when crossing a boundary, or that the right hand side of the differential equation changes. Some theoretical result are presented. Among the results presented, at least the sufficient condition related to fields of extremals should be new. .

Learning-Based Navigation and Collision Avoidance Through Reinforcement for UAVs

IEEE Transactions on Aerospace and Electronic Systems, 2023

Reinforcement learning (RL) has been proven to enable the automation of tasks involving complex s... more Reinforcement learning (RL) has been proven to enable the automation of tasks involving complex sequential decision-making. The simulation to reality (sim2real) gap, however, poses a major challenge in most engineering applications. In this work, we propose a learning approach combining RL based navigation and collision avoidance scheme with low-level advanced control to bridge the sim2real gap for unmanned aerial vehicle (UAV) applications. The proposed approach puts the RL agent at the top of the control hierarchy to focus on behavioral intelligence. We demonstrate the transferability of the RL policy trained in simulation to a real UAV without randomization of the system's dynamic parameters. The direct transfer is enabled by (1) the use of deep neural networks with the modified relay feedback test (DNN-MRFT) to identify the parameters of the UAV, and (2) formulating a reward function to penalize excessive actor actions. Particularly, the RL agent generates high-level velocity actions to achieve the sought task, while the low-level controller minimizes any unwanted disturbances and model discrepancies. The proposed approach has been tested and validated using computer simulations and real-world experiments. The real-world experimental results demonstrated the agent's capability to achieve the navigation task with a 90% success rate. The experimental results can be found in this video: .

Multirotors from Takeoff to Real-Time Full Identification Using the Modified Relay Feedback Test and Deep Neural Networks

arXiv (Cornell University), Oct 6, 2020

Low cost real-time identification of multirotor unmanned aerial vehicle (UAV) dynamics is an acti... more Low cost real-time identification of multirotor unmanned aerial vehicle (UAV) dynamics is an active area of research supported by the surge in demand and emerging application domains. Such real-time identification capabilities shorten development time and cost, making UAVs' technology more accessible, and enable a wide variety of advanced applications. In this paper, we present a novel comprehensive approach, called DNN-MRFT, for real-time identification and tuning of multirotor UAVs using the Modified Relay Feedback Test (MRFT) and Deep Neural Networks (DNN). The main contribution is the development of a generalized framework for the application of DNN-MRFT to higher-order systems. One of the notable advantages of DNN-MRFT is the exact estimation of identified process gain, which mitigates the inaccuracies introduced due to the use of the describing function method in approximating the response of Lure's systems. A secondary contribution is a generalized controller based on DNN-MRFT that takes-off a UAV with unknown dynamics and identifies the inner loops dynamics in-flight. Using the developed framework, DNN-MRFT is sequentially applied to the outer translational loops of the UAV utilizing in-flight results obtained for the inner attitude loops. DNN-MRFT takes on average 15 seconds to get the full knowledge of multirotor UAV dynamics and without any further tuning or calibration the UAV would be able to pass through a vertical window, and accurately follow trajectories achieving state-of-the-art performance. Such demonstrated accuracy, speed, and robustness of identification pushes the limits of state-of-theart in real-time identification of UAVs.

Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation

arXiv (Cornell University), Sep 5, 2022

In this paper, we analyze the effect of time delay dynamics on controller design for Unmanned Aer... more In this paper, we analyze the effect of time delay dynamics on controller design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time delay is an inevitable phenomenon in cyber-physical systems, and has important implications on controller design and trajectory generation for UAVs. The impact of time delay on UAV dynamics increases with the use of the slower vision based navigation stack. We show that the existing models in the literature, which exclude time delay, are unsuitable for controller tuning since a trivial solution for minimizing an error cost functional always exists. The trivial solution that we identify suggests use of infinite controller gains to achieve optimal performance, which contradicts practical findings. We avoid such shortcomings by introducing a novel nonlinear time delay model for UAVs, and then obtain a set of linear decoupled models corresponding to each of the UAV control loops. The cost functional of the linearized time delay model of angular and altitude dynamics is analyzed, and in contrast to the delay-free models, we show the existence of finite optimal controller parameters. Due to the use of time delay models, we experimentally show that the proposed model accurately represents system stability limits. Due to time delay consideration, we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based UAV navigation, which is on par with the state-of-the-art. Multi-rotor UAVs are fairly complex non-linear and underactuated systems which are inherently unstable. Hence, the control of UAV is a challenging task and has been addressed

On Inherent Gain Margins of Sliding-Mode Control Systems

Studies in systems, decision and control, Aug 13, 2017

In this book chapter, analysis of first-order and second-order sliding-mode (SM) control systems ... more In this book chapter, analysis of first-order and second-order sliding-mode (SM) control systems from the perspective of the gain margins of the averaged dynamics is done. These averaged dynamics result from the fact of the existence of chattering, so that averaging on the period of chattering can be considered. Analysis is done via the describing function method and the locus of a perturbed relay system method. First-order SM, hysteresis relay control, twisting algorithm and sub-optimal algorithm are compared in terms of the gain margins of the averaged dynamics that can describe the propagation of external signals through a SM control system.

Design of Dynamics Invariant LSTM for Touch Based Human-UAV Interaction Detection

arXiv (Cornell University), Jul 12, 2022

The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few... more The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions with humans is important for commercialization of UAVs. One particular human-UAV scenario of interest for this paper is the payload handover scheme, where a UAV hands over a payload to a human upon their request. In this scope, this paper presents a novel real-time human-UAV interaction detection approach, where Long short-term memory (LSTM) based neural network is developed to detect state profiles resulting from human interaction dynamics. A novel data pre-processing technique is presented; this technique leverages estimated process parameters of training and testing UAVs to build dynamics invariant testing data. The proposed detection algorithm is lightweight and thus can be deployed in real-time using off the shelf UAV platforms; in addition, it depends solely on inertial and position measurements present on any classical UAV platform. The proposed approach is demonstrated on a payload handover task between multirotor UAVs and humans. Training and testing data were collected using real-time experiments. The detection approach has achieved an accuracy of 96%, giving no false positives even in the presence of external wind disturbances, and when deployed and tested on two different UAVs.

The Role of Time Delay in Sim2real Transfer of Reinforcement Learning for Cyber-Physical Systems

arXiv (Cornell University), Sep 30, 2022

This paper analyzes the simulation to reality gap in reinforcement learning (RL) cyber-physical s... more This paper analyzes the simulation to reality gap in reinforcement learning (RL) cyber-physical systems with fractional delays (i.e. delays that are non-integer multiple of the sampling period). The consideration of fractional delay has important implications on the nature of the cyber-physical system considered. Systems with delays are non-Markovian, and the system state vector needs to be extended to make the system Markovian. We show that this is not possible when the delay is in the output, and the problem would always be non-Markovian. Based on this analysis, a sampling scheme is proposed that results in efficient RL training and agents that perform well in realistic multirotor unmanned aerial vehicle simulations. We demonstrate that the resultant agents do not produce excessive oscillations, which is not the case with RL agents that do not consider time delay in the model.

LPRS analysis of sliding mode control of a boost converter

This paper provides analysis of a boost converter dynamics using the locus of a perturbed relay s... more This paper provides analysis of a boost converter dynamics using the locus of a perturbed relay system (LPRS) method. This method allows one to determine the exact amplitude and frequency of the output voltage oscillations, as well as it describes the external signal propagation throughout the system. The efficiency of the proposed approach is verified experimentally and via simulations.

Analysis of a Sliding Mode DC–DC Boost Converter Through LPRS of a Nonlinear Plant

IEEE Transactions on Power Electronics, Nov 1, 2020

Cabled ocean observatory systems that provide abundant power and broad bandwidth communication en... more Cabled ocean observatory systems that provide abundant power and broad bandwidth communication enabling undersea science have been evolving during the last decade. To establish such permanent infrastructure in the ocean, the technology of cable network switching and fault isolation with very high reliability is essential. In this paper, we review existing switching methods as applied to a constant voltage tree topology network. We propose an actively controllable method that can configure each branch of the network only by changing the feeding current; the current level implicitly conveys the switching information. A laboratory prototype demonstrated the features of backbone switching with zero current and low voltage (less than 20 V), and active controllability of the switch.

Non-parametric auto-tuning of PID controllers for DC-DC converters

Institution of Engineering and Technology eBooks, Dec 31, 2022

Swarm Cooperative Navigation Using Centralized Training and Decentralized Execution

Drones

The demand for autonomous UAV swarm operations has been on the rise following the success of UAVs... more The demand for autonomous UAV swarm operations has been on the rise following the success of UAVs in various challenging tasks. Yet conventional swarm control approaches are inadequate for coping with swarm scalability, computational requirements, and real-time performance. In this paper, we demonstrate the capability of emerging multi-agent reinforcement learning (MARL) approaches to successfully and efficiently make sequential decisions during UAV swarm collaborative tasks. We propose a scalable, real-time, MARL approach for UAV collaborative navigation where members of the swarm have to arrive at target locations at the same time. Centralized training and decentralized execution (CTDE) are used to achieve this, where a combination of negative and positive reinforcement is employed in the reward function. Curriculum learning is used to facilitate the sought performance, especially due to the high complexity of the problem which requires extensive exploration. A UAV model that high...

Energy Efficient Satellite Attitude Control through Direct Commanding of Reaction Wheels Speed

2022 IEEE Conference on Control Technology and Applications (CCTA)

Design of Dynamics Invariant LSTM for Touch Based Human–UAV Interaction Detection

IEEE Access

The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few... more The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions with humans is important for commercialization of UAVs. One particular human-UAV scenario of interest for this paper is the payload handover scheme, where a UAV hands over a payload to a human upon their request. In this scope, this paper presents a novel real-time human-UAV interaction detection approach, where Long short-term memory (LSTM) based neural network is developed to detect state profiles resulting from human interaction dynamics. A novel data pre-processing technique is presented; this technique leverages estimated process parameters of training and testing UAVs to build dynamics invariant testing data. The proposed detection algorithm is lightweight and thus can be deployed in real-time using off the shelf UAV platforms; in addition, it depends solely on inertial and position measurements present on any classical UAV platform. The proposed approach is demonstrated on a payload handover task between multirotor UAVs and humans. Training and testing data were collected using real-time experiments. The detection approach has achieved an accuracy of 96%, giving no false positives even in the presence of external wind disturbances, and when deployed and tested on two different UAVs.

Novel Variable-Structure PD Controller for Satellite Attitude Control

2022 16th International Workshop on Variable Structure Systems (VSS)

Non-parametric tuning of PID Controllers: Evolution of ideas

Journal of Physics: Conference Series, 2021

Non-parametric tuning was introduces by J. Ziegler and N. Nichols with the step test and continuo... more Non-parametric tuning was introduces by J. Ziegler and N. Nichols with the step test and continuous cycling tests and the respective tuning rules. Whereas the step test based tuning had some feature of parametric tuning, the continuous cycling test based tuning was purely non-parametric. The latter test involves bringing the system under proportional control into a sustained oscillation and measuring the frequency of these oscillations and fixing the gain value, that are called the ultimate frequency and ultimate gain. The test was intended for manual tuning of PID controllers. It is relatively hard to automate, and it is not used in auto-tuners. Another test, called relay feedback test (RFT), was proposed by K. Astrom and T. Hagglund to excite self-oscillations through the inclusion of a nonlinear element (relay) in the control loop. This test is easier to automate, and it found applications in industrial auto-tuners. In both these tests ultimate frequency coincides with the phase ...

Two-Relay Controller Test Approach to Non-parametric PID Tuning of a Magnetic Levitation System

2018 15th International Workshop on Variable Structure Systems (VSS), 2018

A non-parametric PID tuning approach for a Magnetic Levitation System (MLS) is proposed in this p... more A non-parametric PID tuning approach for a Magnetic Levitation System (MLS) is proposed in this paper. The proposed tuning method is non-iterative and is based on a test involving the two-relay controller (modified twisting algorithm), that provides identification at frequencies higher than the phase cross over frequency of the process. The tuning procedure has two consecutive stages. First, generating self-excited oscillations in the closed loop of the MLS using the two-relay controller test, and measuring the ultimate frequency and ultimate amplitude of the generated oscillations. Second, using the results obtained from the test and certain non-parametric tuning rules, the parameters of the PID controller are determined. The tuning rules that are produced and used guarantee the specified gain margin for the corresponding linearized system and the motion in the vicinity of the specific set point. To ensure optimal performance of the MLS, the test and tuning are repeated at other se...

On counter-examples to Aizerman and Kalman conjectures

International Journal of Control, 2020

A PDE based model of artificial gas lift, its novel solution by the plastic bag algorithm and application in real-time simulator

RDPETRO 2018: Research and Development Petroleum Conference and Exhibition, Abu Dhabi, UAE, 9-10 May 2018, 2018

Simulator and Controller Tuning/Testing Rig for Artificial Gas Lift

Abu Dhabi International Petroleum Exhibition & Conference, 2017

Quasi optimum PI controller tuning rules for a grid-connected three phase AC to DC PWM rectifier

International Journal of Electrical Power & Energy Systems, 2018

Controller tuning is deemed to be critical when dealing with the voltage oriented control (VOC) a... more Controller tuning is deemed to be critical when dealing with the voltage oriented control (VOC) as it ultimately defines the system performance. This paper contributes to the tuning issue associated with VOC in three key points. Firstly, an algebraic solution (i.e. PI-parameters) based on the first-order-plus-time-delay (FOPTD) approximations of the plant dynamics is developed, along with approximating relationships and methodology. Secondly, a non-linear multi-criteria optimization algorithm, with PI-controller parameters being the decision variables, is developed in order to achieve the optimum disturbance rejection. The cost function employs a weighted-sum criterion to account for two sources of disturbances: grid voltage sag/dip and load current disturbances, which affect the regulated dc voltage. Simulation results suggest a quasi-optimum system performance, in terms of minimum integral time absolute of the error (ITAE) performance index of the dc-bus voltage, using the FOPTD tuning parameters. Hence, the developed FOPTD approximations demonstrate an accurate linear approximation. Thirdly and consequently, analytic tuning rules for the PI-controllers are proposed. The proposed rules provide quasi-optimum PI-parameters by direct substitution of system parameters in the tuning formulae, rather than solving complex algebraic equations as in the FOPTD tuning approach. The obtained results are verified experimentally.

Discontinuous Control Systems

Birkhäuser Boston eBooks, 2009

By means of some simple examples from economics, we elucidate certain solution tools for the solu... more By means of some simple examples from economics, we elucidate certain solution tools for the solution of optimal control problems were the system under study undergoes major changes when certain boundaries are crossed. The "major changes" may be that the state gets a jump discontinuity when crossing a boundary, or that the right hand side of the differential equation changes. Some theoretical result are presented. Among the results presented, at least the sufficient condition related to fields of extremals should be new. .

Learning-Based Navigation and Collision Avoidance Through Reinforcement for UAVs

IEEE Transactions on Aerospace and Electronic Systems, 2023

Reinforcement learning (RL) has been proven to enable the automation of tasks involving complex s... more Reinforcement learning (RL) has been proven to enable the automation of tasks involving complex sequential decision-making. The simulation to reality (sim2real) gap, however, poses a major challenge in most engineering applications. In this work, we propose a learning approach combining RL based navigation and collision avoidance scheme with low-level advanced control to bridge the sim2real gap for unmanned aerial vehicle (UAV) applications. The proposed approach puts the RL agent at the top of the control hierarchy to focus on behavioral intelligence. We demonstrate the transferability of the RL policy trained in simulation to a real UAV without randomization of the system's dynamic parameters. The direct transfer is enabled by (1) the use of deep neural networks with the modified relay feedback test (DNN-MRFT) to identify the parameters of the UAV, and (2) formulating a reward function to penalize excessive actor actions. Particularly, the RL agent generates high-level velocity actions to achieve the sought task, while the low-level controller minimizes any unwanted disturbances and model discrepancies. The proposed approach has been tested and validated using computer simulations and real-world experiments. The real-world experimental results demonstrated the agent's capability to achieve the navigation task with a 90% success rate. The experimental results can be found in this video: .

Multirotors from Takeoff to Real-Time Full Identification Using the Modified Relay Feedback Test and Deep Neural Networks

arXiv (Cornell University), Oct 6, 2020

Low cost real-time identification of multirotor unmanned aerial vehicle (UAV) dynamics is an acti... more Low cost real-time identification of multirotor unmanned aerial vehicle (UAV) dynamics is an active area of research supported by the surge in demand and emerging application domains. Such real-time identification capabilities shorten development time and cost, making UAVs' technology more accessible, and enable a wide variety of advanced applications. In this paper, we present a novel comprehensive approach, called DNN-MRFT, for real-time identification and tuning of multirotor UAVs using the Modified Relay Feedback Test (MRFT) and Deep Neural Networks (DNN). The main contribution is the development of a generalized framework for the application of DNN-MRFT to higher-order systems. One of the notable advantages of DNN-MRFT is the exact estimation of identified process gain, which mitigates the inaccuracies introduced due to the use of the describing function method in approximating the response of Lure's systems. A secondary contribution is a generalized controller based on DNN-MRFT that takes-off a UAV with unknown dynamics and identifies the inner loops dynamics in-flight. Using the developed framework, DNN-MRFT is sequentially applied to the outer translational loops of the UAV utilizing in-flight results obtained for the inner attitude loops. DNN-MRFT takes on average 15 seconds to get the full knowledge of multirotor UAV dynamics and without any further tuning or calibration the UAV would be able to pass through a vertical window, and accurately follow trajectories achieving state-of-the-art performance. Such demonstrated accuracy, speed, and robustness of identification pushes the limits of state-of-theart in real-time identification of UAVs.

Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation

arXiv (Cornell University), Sep 5, 2022

In this paper, we analyze the effect of time delay dynamics on controller design for Unmanned Aer... more In this paper, we analyze the effect of time delay dynamics on controller design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time delay is an inevitable phenomenon in cyber-physical systems, and has important implications on controller design and trajectory generation for UAVs. The impact of time delay on UAV dynamics increases with the use of the slower vision based navigation stack. We show that the existing models in the literature, which exclude time delay, are unsuitable for controller tuning since a trivial solution for minimizing an error cost functional always exists. The trivial solution that we identify suggests use of infinite controller gains to achieve optimal performance, which contradicts practical findings. We avoid such shortcomings by introducing a novel nonlinear time delay model for UAVs, and then obtain a set of linear decoupled models corresponding to each of the UAV control loops. The cost functional of the linearized time delay model of angular and altitude dynamics is analyzed, and in contrast to the delay-free models, we show the existence of finite optimal controller parameters. Due to the use of time delay models, we experimentally show that the proposed model accurately represents system stability limits. Due to time delay consideration, we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based UAV navigation, which is on par with the state-of-the-art. Multi-rotor UAVs are fairly complex non-linear and underactuated systems which are inherently unstable. Hence, the control of UAV is a challenging task and has been addressed

On Inherent Gain Margins of Sliding-Mode Control Systems

Studies in systems, decision and control, Aug 13, 2017

In this book chapter, analysis of first-order and second-order sliding-mode (SM) control systems ... more In this book chapter, analysis of first-order and second-order sliding-mode (SM) control systems from the perspective of the gain margins of the averaged dynamics is done. These averaged dynamics result from the fact of the existence of chattering, so that averaging on the period of chattering can be considered. Analysis is done via the describing function method and the locus of a perturbed relay system method. First-order SM, hysteresis relay control, twisting algorithm and sub-optimal algorithm are compared in terms of the gain margins of the averaged dynamics that can describe the propagation of external signals through a SM control system.

Design of Dynamics Invariant LSTM for Touch Based Human-UAV Interaction Detection

arXiv (Cornell University), Jul 12, 2022

The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few... more The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions with humans is important for commercialization of UAVs. One particular human-UAV scenario of interest for this paper is the payload handover scheme, where a UAV hands over a payload to a human upon their request. In this scope, this paper presents a novel real-time human-UAV interaction detection approach, where Long short-term memory (LSTM) based neural network is developed to detect state profiles resulting from human interaction dynamics. A novel data pre-processing technique is presented; this technique leverages estimated process parameters of training and testing UAVs to build dynamics invariant testing data. The proposed detection algorithm is lightweight and thus can be deployed in real-time using off the shelf UAV platforms; in addition, it depends solely on inertial and position measurements present on any classical UAV platform. The proposed approach is demonstrated on a payload handover task between multirotor UAVs and humans. Training and testing data were collected using real-time experiments. The detection approach has achieved an accuracy of 96%, giving no false positives even in the presence of external wind disturbances, and when deployed and tested on two different UAVs.

The Role of Time Delay in Sim2real Transfer of Reinforcement Learning for Cyber-Physical Systems

arXiv (Cornell University), Sep 30, 2022

This paper analyzes the simulation to reality gap in reinforcement learning (RL) cyber-physical s... more This paper analyzes the simulation to reality gap in reinforcement learning (RL) cyber-physical systems with fractional delays (i.e. delays that are non-integer multiple of the sampling period). The consideration of fractional delay has important implications on the nature of the cyber-physical system considered. Systems with delays are non-Markovian, and the system state vector needs to be extended to make the system Markovian. We show that this is not possible when the delay is in the output, and the problem would always be non-Markovian. Based on this analysis, a sampling scheme is proposed that results in efficient RL training and agents that perform well in realistic multirotor unmanned aerial vehicle simulations. We demonstrate that the resultant agents do not produce excessive oscillations, which is not the case with RL agents that do not consider time delay in the model.

LPRS analysis of sliding mode control of a boost converter

This paper provides analysis of a boost converter dynamics using the locus of a perturbed relay s... more This paper provides analysis of a boost converter dynamics using the locus of a perturbed relay system (LPRS) method. This method allows one to determine the exact amplitude and frequency of the output voltage oscillations, as well as it describes the external signal propagation throughout the system. The efficiency of the proposed approach is verified experimentally and via simulations.

Analysis of a Sliding Mode DC–DC Boost Converter Through LPRS of a Nonlinear Plant

IEEE Transactions on Power Electronics, Nov 1, 2020

Cabled ocean observatory systems that provide abundant power and broad bandwidth communication en... more Cabled ocean observatory systems that provide abundant power and broad bandwidth communication enabling undersea science have been evolving during the last decade. To establish such permanent infrastructure in the ocean, the technology of cable network switching and fault isolation with very high reliability is essential. In this paper, we review existing switching methods as applied to a constant voltage tree topology network. We propose an actively controllable method that can configure each branch of the network only by changing the feeding current; the current level implicitly conveys the switching information. A laboratory prototype demonstrated the features of backbone switching with zero current and low voltage (less than 20 V), and active controllability of the switch.

Non-parametric auto-tuning of PID controllers for DC-DC converters

Institution of Engineering and Technology eBooks, Dec 31, 2022

Swarm Cooperative Navigation Using Centralized Training and Decentralized Execution

Drones

The demand for autonomous UAV swarm operations has been on the rise following the success of UAVs... more The demand for autonomous UAV swarm operations has been on the rise following the success of UAVs in various challenging tasks. Yet conventional swarm control approaches are inadequate for coping with swarm scalability, computational requirements, and real-time performance. In this paper, we demonstrate the capability of emerging multi-agent reinforcement learning (MARL) approaches to successfully and efficiently make sequential decisions during UAV swarm collaborative tasks. We propose a scalable, real-time, MARL approach for UAV collaborative navigation where members of the swarm have to arrive at target locations at the same time. Centralized training and decentralized execution (CTDE) are used to achieve this, where a combination of negative and positive reinforcement is employed in the reward function. Curriculum learning is used to facilitate the sought performance, especially due to the high complexity of the problem which requires extensive exploration. A UAV model that high...

Energy Efficient Satellite Attitude Control through Direct Commanding of Reaction Wheels Speed

2022 IEEE Conference on Control Technology and Applications (CCTA)

Design of Dynamics Invariant LSTM for Touch Based Human–UAV Interaction Detection

IEEE Access

The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few... more The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions with humans is important for commercialization of UAVs. One particular human-UAV scenario of interest for this paper is the payload handover scheme, where a UAV hands over a payload to a human upon their request. In this scope, this paper presents a novel real-time human-UAV interaction detection approach, where Long short-term memory (LSTM) based neural network is developed to detect state profiles resulting from human interaction dynamics. A novel data pre-processing technique is presented; this technique leverages estimated process parameters of training and testing UAVs to build dynamics invariant testing data. The proposed detection algorithm is lightweight and thus can be deployed in real-time using off the shelf UAV platforms; in addition, it depends solely on inertial and position measurements present on any classical UAV platform. The proposed approach is demonstrated on a payload handover task between multirotor UAVs and humans. Training and testing data were collected using real-time experiments. The detection approach has achieved an accuracy of 96%, giving no false positives even in the presence of external wind disturbances, and when deployed and tested on two different UAVs.

Novel Variable-Structure PD Controller for Satellite Attitude Control

2022 16th International Workshop on Variable Structure Systems (VSS)

Non-parametric tuning of PID Controllers: Evolution of ideas

Journal of Physics: Conference Series, 2021

Non-parametric tuning was introduces by J. Ziegler and N. Nichols with the step test and continuo... more Non-parametric tuning was introduces by J. Ziegler and N. Nichols with the step test and continuous cycling tests and the respective tuning rules. Whereas the step test based tuning had some feature of parametric tuning, the continuous cycling test based tuning was purely non-parametric. The latter test involves bringing the system under proportional control into a sustained oscillation and measuring the frequency of these oscillations and fixing the gain value, that are called the ultimate frequency and ultimate gain. The test was intended for manual tuning of PID controllers. It is relatively hard to automate, and it is not used in auto-tuners. Another test, called relay feedback test (RFT), was proposed by K. Astrom and T. Hagglund to excite self-oscillations through the inclusion of a nonlinear element (relay) in the control loop. This test is easier to automate, and it found applications in industrial auto-tuners. In both these tests ultimate frequency coincides with the phase ...

Two-Relay Controller Test Approach to Non-parametric PID Tuning of a Magnetic Levitation System

2018 15th International Workshop on Variable Structure Systems (VSS), 2018

A non-parametric PID tuning approach for a Magnetic Levitation System (MLS) is proposed in this p... more A non-parametric PID tuning approach for a Magnetic Levitation System (MLS) is proposed in this paper. The proposed tuning method is non-iterative and is based on a test involving the two-relay controller (modified twisting algorithm), that provides identification at frequencies higher than the phase cross over frequency of the process. The tuning procedure has two consecutive stages. First, generating self-excited oscillations in the closed loop of the MLS using the two-relay controller test, and measuring the ultimate frequency and ultimate amplitude of the generated oscillations. Second, using the results obtained from the test and certain non-parametric tuning rules, the parameters of the PID controller are determined. The tuning rules that are produced and used guarantee the specified gain margin for the corresponding linearized system and the motion in the vicinity of the specific set point. To ensure optimal performance of the MLS, the test and tuning are repeated at other se...

On counter-examples to Aizerman and Kalman conjectures

International Journal of Control, 2020

A PDE based model of artificial gas lift, its novel solution by the plastic bag algorithm and application in real-time simulator

RDPETRO 2018: Research and Development Petroleum Conference and Exhibition, Abu Dhabi, UAE, 9-10 May 2018, 2018

Simulator and Controller Tuning/Testing Rig for Artificial Gas Lift

Abu Dhabi International Petroleum Exhibition & Conference, 2017

Quasi optimum PI controller tuning rules for a grid-connected three phase AC to DC PWM rectifier

International Journal of Electrical Power & Energy Systems, 2018

Controller tuning is deemed to be critical when dealing with the voltage oriented control (VOC) a... more Controller tuning is deemed to be critical when dealing with the voltage oriented control (VOC) as it ultimately defines the system performance. This paper contributes to the tuning issue associated with VOC in three key points. Firstly, an algebraic solution (i.e. PI-parameters) based on the first-order-plus-time-delay (FOPTD) approximations of the plant dynamics is developed, along with approximating relationships and methodology. Secondly, a non-linear multi-criteria optimization algorithm, with PI-controller parameters being the decision variables, is developed in order to achieve the optimum disturbance rejection. The cost function employs a weighted-sum criterion to account for two sources of disturbances: grid voltage sag/dip and load current disturbances, which affect the regulated dc voltage. Simulation results suggest a quasi-optimum system performance, in terms of minimum integral time absolute of the error (ITAE) performance index of the dc-bus voltage, using the FOPTD tuning parameters. Hence, the developed FOPTD approximations demonstrate an accurate linear approximation. Thirdly and consequently, analytic tuning rules for the PI-controllers are proposed. The proposed rules provide quasi-optimum PI-parameters by direct substitution of system parameters in the tuning formulae, rather than solving complex algebraic equations as in the FOPTD tuning approach. The obtained results are verified experimentally.