Papers by Enrique Ferreira
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2010
The estimation of the vertical in humans is important in everyday life although the mechanisms in... more The estimation of the vertical in humans is important in everyday life although the mechanisms involved are not completely understood yet. This paper presents two sets of experiments with normal subjects, using the same virtual reality setup, aiming to help in this understanding. First, a steady state experiment is presented, which is used to determine the gravitational vertical precision while the second, a dynamical transient response experiment, is used to find dynamic models of each subject response. Results show that the dynamic models are able to reproduce the results of the steady state experiment while having the benefits that a dynamic model brings to evaluate subjects performance.
IFAC-PapersOnLine, 2015
This paper presents a two-level control strategy for the trajectory tracking of the quadcopter. T... more This paper presents a two-level control strategy for the trajectory tracking of the quadcopter. The external loop is designed to move the translational dynamics of the robot to follow smooth parametric functions using an appropriate variables substitution. The outer loop generates the desired trajectories of the orientation angles, which are controlled in the inner loop. The parameter gains are calculated using linear optimal control in order to minimize the energy consumption of the rotors. The control architecture is designed to be compatible with standard electronic platforms of commercial quadcopters and incorporates the purpose of maximizing flight time, an important requirement in real applications of multi-rotor aerial vehicles. Some numerical simulations show the performance of the control approach.
Acta Oto-Laryngologica, 2016
Conclusions The assessment of postural responses (PR) based in a feedback control system model sh... more Conclusions The assessment of postural responses (PR) based in a feedback control system model shows selective gains in different bands of frequencies adaptable with child development. Objective PR characterization of pre-lingual cochlear implant users (CIU) in different sensory conditions. Methods Total energy consumption of the body's center of pressure signal (ECCOP) and its distribution in three bands of frequencies: band 1 (0-0.1 Hz), band 2 (0.1-0.7 Hz), and band 3 (0.7-20 Hz) was measured in a sample of 18 CIU (8-16 years old) and in a control group (CG) (8-15 years old). They were assessed in a standing position on a force platform in two sensory conditions: 1 = Eyes open. 2 = Eyes closed and standing on foam. Results In condition 1, total ECCOP of PR and its proportion of energy consumption in the three bands of frequencies were similar between CIU and CG (p > 0.05). In condition 2, CIU have significantly higher ECCOP, mainly in high frequencies (bands 2 and 3) (p < 0.05). ECCOP values decreased with age also, mainly in bands 2 and 3. This behavior is interpreted in the control system model proposed as an adaptation process related with child development.
Computers & Chemical Engineering, 2015
Lecture Notes in Computer Science, 2015
This paper presents a two-level control strategy for the trajectory tracking of the quadcopter. T... more This paper presents a two-level control strategy for the trajectory tracking of the quadcopter. The external loop is designed to move the translational dynamics of the robot to follow smooth parametric functions using an appropriate variables substitution. The outer loop generates the desired trajectories of the orientation angles, which are controlled in the inner loop. The parameter gains are calculated using linear optimal control in order to minimize the energy consumption of the rotors. The control architecture is designed to be compatible with standard electronic platforms of commercial quadcopters and incorporates the purpose of maximizing flight time, an important requirement in real applications of multi-rotor aerial vehicles. Some numerical simulations show the performance of the control approach.
2015 IEEE 6th Latin American Symposium on Circuits & Systems (LASCAS), 2015
Este trabajo describe el diseño e implementación del control automático para un tipo de procesos ... more Este trabajo describe el diseño e implementación del control automático para un tipo de procesos de prensado y salado de quesos de alto valor agregado. Se enmarca en el desarrollo de una planta piloto experimental para una empresa láctea de mediano porte, para producción e investigación de recetas de producción. Se alcanzaron resultados muy satisfactorios con un diseño de bajo costo adecuado al tipo de empresa. La facilidad y flexibilidad de uso implementada posibilita el estudio sistemático de la influencia de los parámetros de producción en la calidad final de los productos, habilitando un ensayo científico de recetas de producción.
Recently, distance based formation of groups of mobile robots is attracting researchers to provid... more Recently, distance based formation of groups of mobile robots is attracting researchers to provide a better format for decentralized control strategies. However, the setup formulation introduces rigidity problems and additional undesired local minima in the formation convergence standard algorithms. This paper explores the use of combined distance-based attractive-repulsive potentials to simplify the navigation problem as well as the use of angular information between robots to avoid unwanted formation patterns that verify the distance constraints. The proposed algorithms are analyzed for the case of omnidirectional robots in a two-dimensional environment and tested by numerical simulations showing a sliding mode behavior to reach the intended formation configuration.
Hybrid Systems, 1997
This paper presents the results of simulation and control experiments using a recentlyproposed me... more This paper presents the results of simulation and control experiments using a recentlyproposed method for real-time switching among a pool of controllers. The switching strategyselects the current controller based on neural network estimates of the future systemperformance for each controller. This neural-network-based switching controller has been implementedfor a simulated inverted pendulum and a level control system for an underwatervehicle in
A research on the application of Neural Networks in Control was done. The plant proposed was the ... more A research on the application of Neural Networks in Control was done. The plant proposed was the Inverted Pendulum as an unstable system with non-linearities mainly due to friction force. A CMAC neural network, simulated in a PC AT compatible computer, was used in two different structures. In the first structure the CMAC learned to control the plant copying an existing linear controller (CRE). In the second one the CMAC learned the inverted transference of the plant to be controlled. Then control actions were generated based on a trajectory planner. Both structures gave very good results as described herein.
The Gyrover is a single wheel gyroscopically stabilized mobile robot developed at Carnegie Mellon... more The Gyrover is a single wheel gyroscopically stabilized mobile robot developed at Carnegie Mellon University. An internal pendulum serves as a counter weight for a drive motor that causes fore/aft motion, while a tilt-mechanism on a large gyroscope provides a mechanism for lateral actuation. In this paper, we develop a detailed dynamic model for the Gyrover, and use this model in an extended Kalman filter to estimate the complete state. A linearized version of the model is used to develop a state feedback controller. The design methodology is based on a semidefinite programming procedure which optimize the stability region subject to a set of Linear Matrix Inequalities that capture stability and pole placement constraints. Finally, the controller design combined with the extended Kalman filter are verified on the prototype.
In this thesis we explore the use of neural networks to evaluate the performance of nonlinear sys... more In this thesis we explore the use of neural networks to evaluate the performance of nonlinear systemsand to switch among a pool of controllers to achieve a desired closed-loop performance. Thismethod is motivated on the needs of a automated way to generate controller schedules and thedevelopment of a control architecture for evolvable systems called SIMPLEX. The method is basedon two
American Control Conference, 1999
This paper presents new results on the use of neural networks to estimate stability regions for a... more This paper presents new results on the use of neural networks to estimate stability regions for autonomous nonlinear systems. In contrast to model-based analytical methods, this approach uses empirical data from the system to train the neural network. A method is developed to generate confidence intervals for the regions identified by the trained neural network. The neural network results are
IFIP TC12 Publications, 2006
This article introduces an approach to anomaly intrusion detection based on a combination of supe... more This article introduces an approach to anomaly intrusion detection based on a combination of supervised and unsupervised machine learning algorithms. The main objective of this work is an effective modeling of the TCP/IP network traffic of an organization that allows the detection of anomalies with an efficient percentage of false positives for a production environment. The architecture proposed uses a
Hybrid Systems, 1998
This paper presents new results on switching control using neural networks. Given a set of candid... more This paper presents new results on switching control using neural networks. Given a set of candidate controllers, a pair of neural networks is trained to identify the stability region and estimate the closed-loop performance for each controller. The neural network outputs are used in the on-line switching rule to select the controller output to be applied to the system during each control period. The paper presents architectures and training procedures for the neural networks and sufcient conditions for stability of the closed-loop system using the proposed switching strategy. The neural-network-based switching strategy is applied to generate the switching strategy embeded in the simplex architecture, a real-time infrastructure for soft on-line control system upgrades. Results are shown for the real-time level control of a submerged vessel.
Lecture Notes in Computer Science, 1998
This paper presents new results on switching control using neural networks. Given a set of candid... more This paper presents new results on switching control using neural networks. Given a set of candidate controllers, a pair of neural networks is trained to identify the stability region and estimate the closed-loop performance for each controller. The neural network outputs are used in the on-line switching rule to select the controller output to be applied to the system during each control period. The paper presents architectures and training procedures for the neural networks and sufcient conditions for stability of the closed-loop system using the proposed switching strategy. The neural-network-based switching strategy is applied to generate the switching strategy embeded in the simplex architecture, a real-time infrastructure for soft on-line control system upgrades. Results are shown for the real-time level control of a submerged vessel.
Lecture Notes in Computer Science, 1999
This paper presents the results of simulation and control experiments using a recentlyproposed me... more This paper presents the results of simulation and control experiments using a recentlyproposed method for real-time switching among a pool of controllers. The switching strategyselects the current controller based on neural network estimates of the future systemperformance for each controller. This neural-network-based switching controller has been implementedfor a simulated inverted pendulum and a level control system for an underwatervehicle in
Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), 1999
This paper presents new results on the use of neural networks to estimate stability regions for a... more This paper presents new results on the use of neural networks to estimate stability regions for autonomous nonlinear systems. In contrast to model-based analytical methods, this approach uses empirical data from the system to train the neural network. A method is developed to generate confidence intervals for the regions identified by the trained neural network. The neural network results are
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Papers by Enrique Ferreira