Robust control systems

The article addresses a robust control strategy for efficient path tracking of nonholonomic wheeled mobile robot (WMR) based on time delay approach. Depending on the application requirements, nonholonomic WMR system might be subjected to various payloads, which affects the overall system mass, inertia, position of center of mass and other hardware parameters statically or dynamically. Under such circumstances, accurate modeling of nonholonomic robots is difficult and challenging. The proposed controller negotiates uncertainties caused due to payload variations as well as associated disturbances and reduces modeling effort through approximation of the overall uncertainties with a composite function. It has been shown that the controller does not require any bounds on the uncertainties, thus providing unconstrained working paradigm. The controller is proposed for a nonholonomic WMR and its effectiveness is verified through simulation and experimentally while WMR is commanded to track various paths. The superior performance is also noted against adaptive sliding mode control law

This paper considers the design problem of integrated controls and diagnostics. The foundation for such an integrated approach was presented in (Nett et al., 1988), where the approach made use of the so-called four degrees-of-freedom (4-DOF) controller. This controller has 2-inputs and 2-outputs (rather than one). The additional controller output was viewed as a diagnostic output which is monitored to detect and isolate sensor and actuator failures. It will be shown that the 4-DOF controller is a simple case of the standard regulator framework. The design of the integrated controls and diagnostics can thus be done in the framework of robust control theory. This gives the advantage of synthesizing the 4-DOF controller in a single step approach. The effect of model uncertainty is directly incorporated in the synthesis so that when uncertain plants are used, the diagnostic performance should remain reasonable. An example will be presented to demonstrate the proposed design approach.

This article studies the problem of designing robust control laws to achieve multiple performance objectives for linear uncertain systems. Specifically, in this study we have selected one of the control objectives to be a closed-loop pole placement in specific regions of the left-half complex plane. As such, a guaranteed cost-based multi-objective control approach is proposed and compared with the H_2 / H_∞ control by means of an application example.

The robust decentralized formation control for the multiagent quadrotor is investigated in this article. The leaderless formation protocol is proposed for a class of square multi-input multi-output nonlinear multiagent systems with an undirected communication graph. The six degree of freedom underactuated nonlinear model of multiagent quadrotor is considered and altered to a four-input four-output model by stabilizing two states internally using sliding mode control (SMC). Later, the sliding mode-based finite-time position, altitude and heading formation is established based on Lyapunov stability theory. The numerical simulations are performed using MATLAB/ Simulink which validate the proposed formation protocol.

: Linear systems controlled by a nonlinear version of the PI algorithm are under study. The modified PI controller in question is known in the literature as the Super–Twisting (STW) algorithm (see Levant (1993)), and it belongs to the family of second order sliding mode controllers. The considered closed–loop system exhibits self–sustained stable oscillations (chattering) when the relative degree of the linear plant is higher than one (see Boiko and Fridman (2005)) and it is the task of the present paper to present a systematic yet simple procedure for tuning the STW algorithm parameters in order to obtain pre–specified  requency and magnitude of the resulting chattering oscillation. The proposed methodology is based on the Describing Function (DF) approach. The approach is theoretically illustrated and verified by means of, both, simulation analysis and experiments carried out by making references to a DC motor.

Explicit state-space formulae for an H∞-based two degrees-of-freedom robust controller are derived in discrete time. The controller provides robust stability against coprime factor uncertainty, and a degree of robust performance in the sense of making the closed-loop system match a pre-specified reference model. It is shown that the controller consists of a plant state observer, the chosen reference model, and a generalized state feedback law associated with the plant and reference model states. A design for a glass tube production process is presented as an illustrative example. Important implementation issues are discussed. The controller structure is shown to be utilized to yield considerable savings in the number of real time computations required.

In this paper a robust MPC scheme based on a partial-state availability is developed for uncertain discrete-time linear systems described by structured norm-bounded model uncertainties and subject to saturation and rate of variation constraints. The algorithm is based on the minimization, at each time instant, of a semi-definite convex optimization problem subject to Linear Matrix Inequalities (LMI) feasibility constraints which are derived by a judicious use of S-Procedure arguments. Numerical comparisons with competitor algorithms are finally reported by dealing with the control augmentation problem of an High Altitude Performance Demonstrator (HAPD) unmanned aircraft with redundant control surfaces.

In this paper, robust controllers for the benchmark problem are designed using H∞ loop-shaping techniques. Explicit closed-loop performance is obtained by designing the weighting function parameters using numerical optimization techniques in the form of the method of inequalities. Performance is improved by including an adaptive gain scheme.

This paper is concerned with discrete-time model reduction via order-reduction of a discrete-time left coprime factor representation of a given model or controller. The proposed model reduction scheme is suitable for both, stable and unstable models, and for non-minimal state-space systems. Balanced singular perturbation approximation is considered rather than balanced truncation. Numerical issues are also considered.

The aim of this paper is to introduce an internal model control (IMC) design procedure for synthesizing two degrees-of-freedom (2-DOF) IMC controllers in a H∞ optimization framework. In order to evaluate the applicability of the proposed 2-DOF IMC approach in process industries, we will demonstrate the technique on one of the most common and most studied control problems in industry: a distillation column. It will be applied to an experimental methanol/water distillation column model. When applied to the distillation column, robust performance of the 2-DOF IMC controller is found to be significantly better than traditional single-loop P+I controllers.

Identification of uncertainty bounds in robust control design is known to be a critical issue that attracts the attention of research in robust control field recently. Nevertheless, the practical implementation involves a trial and error procedure, which depends on the designer prior knowledge and the available information about the system under study. Artificial intelligent techniques provide a suitable solution to such a problem. In this paper a new intelligent identification method of uncertainty bound using an adaptive neuro-fuzzy inference system (ANFIS) in an enhanced feedback scheme is proposed. The proposed ANFIS structure enables accurate determination of the uncertainty bounds and guarantees robust stability and performance. In our proposed technique, the validation of the intelligent identified uncertainty weighting function is based on the measurement of both the v-gap metric and the stability margin that result from the corresponding robust controller design. Additionally, these two indices are used to improve the accuracy of the intelligent estimation of uncertainty bound in conjunction with the robust control design requirements. The enhanced intelligent identification of uncertainty bound is demonstrated on a servo positioning system. Simulation and experimental results prove the validity of the applied approach; more reliable and highly efficient estimation of the uncertainty weighting function for robust controller design.

We consider methods for synthesizing robust controllers that can be directly implemented in the Internal Model Control (IMC) scheme. We show how to put H∞ design methods into the IMC scheme to improve its robustness. These methods include one degree-of-freedom (one d.o.f.) and two degrees-of-freedom (two d.o.f.) H∞ designs. Explicit state-space formulae for the H∞ one d.o.f. and two d.o.f. IMC-based controllers are derived in discrete time. We show that the IMC controller solves a special H∞ control problem, namely a disturbance feedforward control problem, and it proves robust stability against coprime factor uncertainty and with a degree of robust performance for the two d.o.f. case, in the sense of making the closed-loop system match a pre-specified reference model. A design for a glass tube production process is presented as an illustrative example.

In this paper, robust controllers for the benchmark problem are designed using H∞ loop-shaping techniques. Explicit closed-loop performance is obtained by designing the weight-ing function parameters using numerical optimization techniques in the form of the method of inequalities. Performance is improved by including an adaptive gain scheme.

This paper presents the simulation of real time data acquisition of a solar panelin LabVIEW. A prototype model has been made where two Arduino were used. One is used for interfacing the solar panel with the PC for acquisition of data and the other one isused with the servomotor. The servomotor is linked with the solar panel with the help of a shaft and is rotated according to the LDR output. Two LDR is fixed on both the sides of the solar panel for tracing the sunlight. The whole simulation is performed with the help of LINX firmware wizard, which is available in LabVIEW Maker's Hub. Data were collected of different days in different duration of time. According to the collected data, behaviour and the voltage of the solar module was analysed. This paper describes the design of a low cost, solar tracking and real time data acquisition system.

In this paper a comparison between various advanced multivariable identification techniques and a description of various control design methods, all applied to a glass tube production process, will be discussed. The main features such as accuracy, user-friendliness and speed, will be presented for each identification technique. Also, the differences between the identified models with respect to order, static-gains and dynamical behaviour will be discussed. Starting with a nominal model derived via advanced identification, a robust controller is designed based on an Internal-Model Control (IMC) scheme. The control objectives together with the controller design results, will be presented. It will be shown that the application of advanced identification techniques and robust control design methods can achieve high levels of performance specifications in industrial processes.

In this paper, we adopt the hybrid supervisory control architecture developed in [1] for constrained control sys- tems. The strategy is based on Command Governor (CG) ideas and is tailored to jointly take into account time-varying set- points/constraints and unpredictable anomalies in the nominal dynamical plant behaviour. The main contribution is to develop a low-computational demanding predictive scheme known in literature as the command governor (CG) for the supervision of non- linear dynamical systems subject to sudden switchings amongst operating conditions and time-varying constraints by preserving its basic properties.
In order to show the effectiveness of proposed approach, we show significant simulations on the P92 commercial aircraft used for general aviation purposes.

The aim of this paper remains to introduce the extensive application of a state-of-the-art autonomous underwater vehicle (AUV-150) capable of operating up to a depth of 150 meters, without any human intervention. The AUV-150 has been developed to perform seabed mapping and collect oceanographic data like salinity, temperature and conductivity at various depths. In this regard, various functional aspects of the system shall also be discussed in this paper. Considering navigational and guidance issues relating AUV-150 as well as the images obtained on an account of underwater terrain mapping done employing the payload sensors as the pioneer space; the paper also includes the plots generated as a result of post-processing algorithms applied on the raw data obtained from the scanning sensors used typically for seabed mapping.

The process of identifying the central nodes in complex networks research has remained interesting and
very important issue for network analysis. The identification of main nodes in the network can lead to many
answers for the solution of security and other problems depending on the type of complex networks under
analysis. Different topological metrics of the network can be used to locate the major nodes in the network
but the degree and betweenness (Load) centralities perform very important role in evolution and
communication of nodes in growing networks. Unfortunately, these metrics have been analyzed in different
complex systems mainly either on the bases of the number of links to nodes in the network or with much
focused from the perspective of weights of links. Therefore, locating the main nodes in the network not
only depends on links but majorly on weight of links. Routers network of the internet is an example of
scale-free nature which follow power-law distribution and causes inhomogeneous structure with some
nodes with large number of links while many with a few. Further, in this type of distribution few nodes
become very important. In this paper, we analyze the behavior of routers network by using two metrics of
centralities with weighted and un-weighted links based on the dataset of PTCL routers network in Pakistan.
Furthermore, by using centralities measures we try to show that weight of links is important as compare to
number of links by following the concept from “rich get richer” to “fit get richer” in routers network.
Moreover, we prove that weighted routers network is very close to scale-free networks as compared to unweighted,
and due to this phenomenon these networks sustain their robustness.

This paper deals with the problem of stabilizing a class of structures subject to an uncertain excitation due to the temporary coupling of the main system with another uncertain dynamical subsystem. A Lyapunov function based control scheme is proposed to attenuate the structural vibration. In the control design, the actuator dynamics is taken into account. The control scheme is implemented by using only feedback information of the main system. The effectiveness of the control scheme is shown for a bridge platform with crossing vehicle.

Precise speed control of DC motors is an important requirement for
efficient industrial automation and diverse applications fields. In this paper, a speed control of a DC motor for a photovoltaic system is proposed using fuzzy logic technique as a controller with a DC-DC converter type positive output Luo converter (POLC). POLC, one of a new generation of DC-DC converters which presents multiples advantages, is used as an intermediary between the photovoltaic source and the DC motor, in order to control the transmitted power with low power losses. Multiple classical control techniques could be used to control DC motor speed. However, in this work, a PI fuzzy logic controller (FLC) is proposed to get better pursuit, response and speed accuracy which represents important parameters to control on some industrial applications. Different system blocks are developed on MATLAB/Simulink as environment. Simulation results, using comparison between a conventional PID controller and the PI-fuzzy logic controller, demonstrate the good behaviour of the proposed system.

International Journal of Electrical and communication engineering (IJECE) is an open access peer-reviewed journal that publishes quality articles contributing new results in all areas of Applied Control Systems, Electrical Engineering and Electronics Engineering. The Journal of Electrical and communication engineering (IJECE) is an abstracted and indexed international journal of high quality devoted to the publication of original research papers from Control Systems, Electrical Engineering, Power Systems, Automation, Electronics Engineering, Networks and Communication Systems and their broad range of applications.

This article describes a probabilistic control model based on Markov Decision
Processes for the locomotion of a hexagonal hexapod robot. Uncertainty is
naturally taken into account in probabilistic models, resulting in flexible control
models that enable a robot to react to both, expected and unexpected
situations. The model was tested using a simulated robot under various experimental
conditions.