Eugenio Castelan - Academia.edu (original) (raw)
Papers by Eugenio Castelan
IEEE Control Systems Letters
2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA), 2021
In this work, we investigate an incremental stabilizing Output Feedback control law for discrete-... more In this work, we investigate an incremental stabilizing Output Feedback control law for discrete-time linear parameter-varying (LPV) systems subject to state constraints, control amplitude limits, and bounds of the control-rate variation. To this end, we consider the Positive-Invariance and Contractivity properties of polyhedral sets to guarantee the regional closed-loop stability and that the constraints are all respected. As usual in LPV literature, the varying parameters are considered online available. Furthermore, we describe the constrained control system in the extended state space composed of the system's state and control variables, in which the control variations act as the control inputs. From this extended LPV formulation, we use the known necessary and sufficient algebraic conditions for positive-invariance and contractivity to propose a new bilinear optimization problem to design the controller. The proposed objective function optimizes the polyhedron size in given directions, and an efficient non-linear optimization solver is used to tackle the present bilinearities. Numerical examples showcase the effectiveness and potential of our proposal.
2019 7th International Conference on Robotics and Mechatronics (ICRoM), 2019
Simultaneous Localization and Mapping (SLAM) is being developed as a hot topic issue in computer ... more Simultaneous Localization and Mapping (SLAM) is being developed as a hot topic issue in computer vision which nowadays, is the main core of self-localization and autonomous navigation in robotic technology and unmanned vehicles. In this way, Visual-Inertial SLAM algorithm is a popular strategy to attain high accurate 6-DOF state estimation. But such an accurate system is vulnerable to extreme movements and texture-less environments, and it sometimes fails in confronting such circumstances. In this paper, a tightly-coupled and optimization-based monocular Visual-Inertial SLAM system is proposed, which can tackle the scale ambiguity - a problem that arises by poor initialization. To perform this, the ORB-SLAM as the most reliable feature-based monocular SLAM algorithm has been selected as the base of our study. Then, to improve the accuracy, a Visual-Inertial Odometry (VIO) is carried out that fuses the camera information and Inertial Measurement Unit (IMU) data. We evaluate the performance of our system on the European Robotics Challenge (EuRoC) dataset and compare it with the state-of-the-art algorithms, providing better accuracy in some sequences owing to the improved initialization. Furthermore, we implement the real-world indoor experiment using a monocular-inertial camera to demonstrate the appropriate performance of our system.
1992 American Control Conference, 1992
A state-feedback eigenstructure assignment method is described for providing a robust solution to... more A state-feedback eigenstructure assignment method is described for providing a robust solution to some linear regulation problems under constraints on the state or on the input vector. The main result is that if the initial state vector belongs to a particular bounded set, the trajectories emanating from it will respect the constraints in a robust way, that is even if the system dynamics are slightly perturbed.
2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), 2018
This brief addresses the accuracy of the pose estimation of a Low-Cost Quadrotor using visual SLA... more This brief addresses the accuracy of the pose estimation of a Low-Cost Quadrotor using visual SLAM and sensor data fusion for making an autonomous indoor navigation in a known GPS-denied environment. To perform this approach, two kinds of modules are employed. For the former, a Simultaneous Localization and Mapping (SLAM) system is used. This SLAM system uses Oriented Fast and rotated BRIEF (ORB) features, also known as ORB_SLAM. The second module is Extended Kalman Filter (EKF) that is applied for combining the obtained pose from ORB_SLAM and Inertial Measurement Unit (IMU). Since in this paper the SLAM process is performed by the frontal monocular camera of Quadrotor, so developing scale factor estimation in order to calculate the scale of the map with minimum error is necessary. In addition, a Proportional Integral Derivative (PID) is utilized to conduct the maneuver of the robot. All of these processes are done by sending data via Wi-Fi to a ground station in order to perform the data processing. To show the performance of the proposed algorithm, two experiments are carried out on an AR-Drone 2.0 quadrotor. The first one is position holding that shows the robustness of the estimated position of the system in hovering situation after take-off. The second one is an indoor trajectory tracking that illustrates the difference between the downward camera output position and the estimated position.
IFAC-PapersOnLine, 2020
We propose a numerical method to compute stabilizing state feedback control laws and associated p... more We propose a numerical method to compute stabilizing state feedback control laws and associated polyhedral invariant sets for nonlinear systems represented by Fuzzy Takagi-Sugeno (T-S) models, subject to state and control constraints, and persistent disturbances. Sufficient conditions are derived under which a given polyhedral set is positively invariant under a Parallel Distributed Compensation (PDC), in the form of bilinear algebraic inequalities. Then, a bilinear programming (BP) problem is proposed to compute the state feedback gains and an associated positively invariant polyhedron, with predefined complexity, which solve a constrained regulation problem for the Fuzzy T-S system. A numerical example illustrates the effectiveness of the method.
IEEE Transactions on Automatic Control, 2018
We address the problem of robust input-to-state stabilization of parameter-varying discrete-time ... more We address the problem of robust input-to-state stabilization of parameter-varying discrete-time systems with time-varying state delay, saturating actuators, and subject to ℓ2-limited disturbance. It is assumed that the delay belongs to a known interval and its maximum variation between two consecutive instants is taken into account. The proposed convex delay-dependent conditions for the synthesis of robust state feedback controllers ensure local input-to-state stability of the closed-loop system for a set of initial conditions and for energy bounded disturbance signals. However, the computed controllers do not require the real-time knowledge of the delay. The approach is based on the rewriting of the saturating and delayed system in terms of a switched uncertain augmented delay-free system with a dead-zone non-linearity and on the application of the generalized sector condition. To illustrate the efficiency of our approach, we compare it by means of numerical examples with others found in the literature.
IFAC-PapersOnLine, 2018
The dynamic output feedback stabilization problem of nonlinear discrete-time systems subject to a... more The dynamic output feedback stabilization problem of nonlinear discrete-time systems subject to amplitude bounded disturbances by means of Takagi-Sugeno (T-S) N-fuzzy models is considered in this paper. The linear matrix inequality (LMI) approach is applied to design a dynamic output feedback fuzzy controller such that the system trajectories are ultimately bounded, that is, the state trajectory starting in a set of admissible initial conditions is guaranteed to converge in finite time to a nearby region of the state space origin. Furthermore, the proposed approach enables to handle with nonlinearities that are not function of the measured outputs but are sector bounded. A numerical example is considered to illustrate the effectiveness of the developed technique.
IFAC Proceedings Volumes, 2008
In the present work a systematic methodology for computing output stabilizing feedback control la... more In the present work a systematic methodology for computing output stabilizing feedback control laws for nonlinear systems subject to saturating inputs is presented. In particular, the class of L'ure type nonlinear systems is considered. Based on absolute stability tools and a modified sector condition to take into account input saturation effects, an LMI framework is proposed to design the controller. Both regional (local) and global stabilization results are presented. The controller structure is composed by a linear part, an anti-windup loop and a term associated to the output of the dynamic nonlinearity. Convex optimization problems are proposed in order to compute the controller matrices aiming at the maximization of the basin of attraction, or the performance enhancement with a guaranteed region of stability. A numerical example illustrates the potentialities of the methodology.
Int J Robust Nonlinear Contr, 2006
This paper addresses the problem of controlling a linear system subject to actuator saturations a... more This paper addresses the problem of controlling a linear system subject to actuator saturations and to L 2bounded disturbances. Linear matrix inequality (LMI) conditions are proposed to design a state feedback gain in order to satisfy the closed-loop input-to-state stability (ISS) and the closed-loop finite gain L 2 stability. By considering a quadratic candidate Lyapunov function, two particular tools are used to derive the LMI conditions: a modified sector condition, which encompasses the classical sector-nonlinearity condition considered in some previous works, and Finsler's Lemma, which allows to derive stabilization conditions which are adapted to treat multiple objective control optimization problems in a potentially less conservative framework.
IFAC Proceedings Volumes, 2008
In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration o... more In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration of a kinematic controller and a torque controller is investigated. The proposed torque controllers (PTCs) are based on a Gaussian radial basis function neural network (RBFNN) modeling technique, which are used to compensate the mobile robot dynamics, significant uncertainties and disturbances. Also, the PTCs are not dependent of the robot dynamics neither requires the off-line training process. The stability analysis and the convergence of tracking errors to zero, as well as the learning algorithms (for weights, centers, and widths) are guaranteed with basis on Lyapunov's theory. In addition, the simulation results shows the efficiency of the PTCs.
2006 IEEE International Symposium on Circuits and Systems
This paper presents some results on absolute stabilization of nonlinear discrete-time systems und... more This paper presents some results on absolute stabilization of nonlinear discrete-time systems under control saturations. The studied control law consists of the feedback of both the states and of the nonlinearity present in the dynamics of the controlled system. Saturations are taken into account by modelling the nonlinear saturated system through deadzone nonlinearities satisfying a modified sector condition. Thus, as
This paper presents a method for synthesis of dynamic output-feedback controller partially de-pen... more This paper presents a method for synthesis of dynamic output-feedback controller partially de-pended on parameter for networked control systems. The results are described in terms of linear matrix inequal-ities based in a polytopic model for the system. Moreover, a restriction related with temporal performance for the closed-loop system is included in the stability condition. A numerical example and simulation are provided in order to illustrate the proposed method. Keywords— networked control systems, linear matrix inequalities, output dynamic compensator. Resumo— Este artigo apresenta uma proposta para síntese de compensador dinâmico, parcialmente depen-dente de parâmetro, para sistemas controlados via rede. Os resultados são desenvolvidos em termos de desigualda-des matriciais lineares, considerando para isso um modelo politópico para o sistema de controle. Adicionalmente, uma restrição temporal, relacionada ao desempenho do sistema em malha fechada e acrescentadà a condição de e...
2008 IEEE International Conference on Emerging Technologies and Factory Automation, 2008
Based on mechanical energies analysis, the aim of this paper is to propose the use of the relativ... more Based on mechanical energies analysis, the aim of this paper is to propose the use of the relative dorsal position of a 5-link bipedal robot in order to compensate its moments during the walking cycle, leading the previously unstable system to stability. Also, a modification of the PD control law avoids hyperextension at the supporting legpsilas knee. Finally, the model parameters are subjected to percentual variations with respect to the real robot parameters and the robustness of the system is verified through simulations.
IFAC Proceedings Volumes, 2007
This paper presents some results on stability and stabilization of a class of uncertain nonlinear... more This paper presents some results on stability and stabilization of a class of uncertain nonlinear discrete-time systems under control saturations. The studied control law consists of the feedback of both the states and of the nonlinearity present in the dynamics of the controlled system. Saturations are taken into account by modeling the nonlinear saturated system through a deadzone nonlinearity satisfying a modified sector condition. Thus, as for precisely known systems, LMI stability and stabilization conditions are proposed, which can be cast into convex programming problems. Some relations of the proposed results with the poly-quadratic stability concept are included.
Proceedings of the 2010 American Control Conference, 2010
Page 1. Dynamic output compensator design for time-varying discrete time systems with delayed sta... more Page 1. Dynamic output compensator design for time-varying discrete time systems with delayed states Valter JS Leite, Eugênio B. Castelan, Márcio F. Miranda and Dimitri C. Viana AbstractConvex conditions, proposed as ...
53rd IEEE Conference on Decision and Control, 2014
In this paper, we assume that a set of non preemptive controller tasks should be implemented on a... more In this paper, we assume that a set of non preemptive controller tasks should be implemented on a limited computational resource platform, and look for a sampling period assignment that allows to obtain the desirable performance. The problem is formulated as a multi-objective optimization problem under a resource constraint, where the cost functions depend on the sampling period. Linear-quadratic controllers are used, resulting on feedback gains that also depend on the sampling period. The global cost function is chosen as a weighted sum of all plants performances, translating the multi-objective optimization problem into a single-objective one which provides an additional degree of freedom and leads to a set of solutions denoted as Pareto efficient. To handle this additional variable, we assume a Nash bargaining cooperative game. An upper level task performs the update of the sampling period and of the plant input, to be used on a finite-horizon control strategy, for each control loop. A numerical example is provided to illustrate our approach.
2008 16th Mediterranean Conference on Control and Automation, 2008
In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration o... more In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains parametric and nonparametric uncertainties. The proposed neural controller (PNC) is constituted of the KNC and the TNC, and designed by use of a modeling technique of Gaussian radial basis function neural networks (RBFNNs). The KNC is applied to compensate the parametric uncertainties of the mobile robot kinematics. The TNC, based on the sliding mode theory, is constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, significant uncertainties, bounded unknown disturbances, neural network modeling errors, influence of payload, and unknown kinematic parameters. To alleviate the problems met in practical implementation using classical sliding mode controllers and to eliminate the chattering phenomenon is used the RNC of the TNC, which is nonlinear and continuous, in lieu of the discontinuous part of the control signals p resent in classical forms. Also, the PNC neither requires the knowledge of the mobile robot kinematics and dynamics nor the time-consuming training process. Stability analysis and convergence of tracking errors to zero as well as the learning algorithms for weights are gua ranteed •with basis on Lyapunov method. Simulations results are provided to show the effectiveness of the proposed approach.
Proceedings of the 2010 American Control Conference, 2010
We present a methodology for computing output feedback control laws for a class of nonlinear syst... more We present a methodology for computing output feedback control laws for a class of nonlinear systems subject to input saturations. This class of systems consists of a L'ure type nonlinear system with some time-varying parameters which are assumed to be real-time available. Based on some tools from the absolute stability theory, on a modified sector condition to take into account input saturation effects, and on the concept of contractive sets applied to a level set obtained from a particular parameter dependent Lyapunov function, an LMI framework is proposed to design dynamic output feedback compensators. Two local stabilization strategies are considered: i) with saturation avoidance, and ii) with saturating actuators. In both cases, convex optimization problems are proposed to compute the controllers matrices aiming at the maximization of the basin of attraction.
IEEE Control Systems Letters
2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA), 2021
In this work, we investigate an incremental stabilizing Output Feedback control law for discrete-... more In this work, we investigate an incremental stabilizing Output Feedback control law for discrete-time linear parameter-varying (LPV) systems subject to state constraints, control amplitude limits, and bounds of the control-rate variation. To this end, we consider the Positive-Invariance and Contractivity properties of polyhedral sets to guarantee the regional closed-loop stability and that the constraints are all respected. As usual in LPV literature, the varying parameters are considered online available. Furthermore, we describe the constrained control system in the extended state space composed of the system's state and control variables, in which the control variations act as the control inputs. From this extended LPV formulation, we use the known necessary and sufficient algebraic conditions for positive-invariance and contractivity to propose a new bilinear optimization problem to design the controller. The proposed objective function optimizes the polyhedron size in given directions, and an efficient non-linear optimization solver is used to tackle the present bilinearities. Numerical examples showcase the effectiveness and potential of our proposal.
2019 7th International Conference on Robotics and Mechatronics (ICRoM), 2019
Simultaneous Localization and Mapping (SLAM) is being developed as a hot topic issue in computer ... more Simultaneous Localization and Mapping (SLAM) is being developed as a hot topic issue in computer vision which nowadays, is the main core of self-localization and autonomous navigation in robotic technology and unmanned vehicles. In this way, Visual-Inertial SLAM algorithm is a popular strategy to attain high accurate 6-DOF state estimation. But such an accurate system is vulnerable to extreme movements and texture-less environments, and it sometimes fails in confronting such circumstances. In this paper, a tightly-coupled and optimization-based monocular Visual-Inertial SLAM system is proposed, which can tackle the scale ambiguity - a problem that arises by poor initialization. To perform this, the ORB-SLAM as the most reliable feature-based monocular SLAM algorithm has been selected as the base of our study. Then, to improve the accuracy, a Visual-Inertial Odometry (VIO) is carried out that fuses the camera information and Inertial Measurement Unit (IMU) data. We evaluate the performance of our system on the European Robotics Challenge (EuRoC) dataset and compare it with the state-of-the-art algorithms, providing better accuracy in some sequences owing to the improved initialization. Furthermore, we implement the real-world indoor experiment using a monocular-inertial camera to demonstrate the appropriate performance of our system.
1992 American Control Conference, 1992
A state-feedback eigenstructure assignment method is described for providing a robust solution to... more A state-feedback eigenstructure assignment method is described for providing a robust solution to some linear regulation problems under constraints on the state or on the input vector. The main result is that if the initial state vector belongs to a particular bounded set, the trajectories emanating from it will respect the constraints in a robust way, that is even if the system dynamics are slightly perturbed.
2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), 2018
This brief addresses the accuracy of the pose estimation of a Low-Cost Quadrotor using visual SLA... more This brief addresses the accuracy of the pose estimation of a Low-Cost Quadrotor using visual SLAM and sensor data fusion for making an autonomous indoor navigation in a known GPS-denied environment. To perform this approach, two kinds of modules are employed. For the former, a Simultaneous Localization and Mapping (SLAM) system is used. This SLAM system uses Oriented Fast and rotated BRIEF (ORB) features, also known as ORB_SLAM. The second module is Extended Kalman Filter (EKF) that is applied for combining the obtained pose from ORB_SLAM and Inertial Measurement Unit (IMU). Since in this paper the SLAM process is performed by the frontal monocular camera of Quadrotor, so developing scale factor estimation in order to calculate the scale of the map with minimum error is necessary. In addition, a Proportional Integral Derivative (PID) is utilized to conduct the maneuver of the robot. All of these processes are done by sending data via Wi-Fi to a ground station in order to perform the data processing. To show the performance of the proposed algorithm, two experiments are carried out on an AR-Drone 2.0 quadrotor. The first one is position holding that shows the robustness of the estimated position of the system in hovering situation after take-off. The second one is an indoor trajectory tracking that illustrates the difference between the downward camera output position and the estimated position.
IFAC-PapersOnLine, 2020
We propose a numerical method to compute stabilizing state feedback control laws and associated p... more We propose a numerical method to compute stabilizing state feedback control laws and associated polyhedral invariant sets for nonlinear systems represented by Fuzzy Takagi-Sugeno (T-S) models, subject to state and control constraints, and persistent disturbances. Sufficient conditions are derived under which a given polyhedral set is positively invariant under a Parallel Distributed Compensation (PDC), in the form of bilinear algebraic inequalities. Then, a bilinear programming (BP) problem is proposed to compute the state feedback gains and an associated positively invariant polyhedron, with predefined complexity, which solve a constrained regulation problem for the Fuzzy T-S system. A numerical example illustrates the effectiveness of the method.
IEEE Transactions on Automatic Control, 2018
We address the problem of robust input-to-state stabilization of parameter-varying discrete-time ... more We address the problem of robust input-to-state stabilization of parameter-varying discrete-time systems with time-varying state delay, saturating actuators, and subject to ℓ2-limited disturbance. It is assumed that the delay belongs to a known interval and its maximum variation between two consecutive instants is taken into account. The proposed convex delay-dependent conditions for the synthesis of robust state feedback controllers ensure local input-to-state stability of the closed-loop system for a set of initial conditions and for energy bounded disturbance signals. However, the computed controllers do not require the real-time knowledge of the delay. The approach is based on the rewriting of the saturating and delayed system in terms of a switched uncertain augmented delay-free system with a dead-zone non-linearity and on the application of the generalized sector condition. To illustrate the efficiency of our approach, we compare it by means of numerical examples with others found in the literature.
IFAC-PapersOnLine, 2018
The dynamic output feedback stabilization problem of nonlinear discrete-time systems subject to a... more The dynamic output feedback stabilization problem of nonlinear discrete-time systems subject to amplitude bounded disturbances by means of Takagi-Sugeno (T-S) N-fuzzy models is considered in this paper. The linear matrix inequality (LMI) approach is applied to design a dynamic output feedback fuzzy controller such that the system trajectories are ultimately bounded, that is, the state trajectory starting in a set of admissible initial conditions is guaranteed to converge in finite time to a nearby region of the state space origin. Furthermore, the proposed approach enables to handle with nonlinearities that are not function of the measured outputs but are sector bounded. A numerical example is considered to illustrate the effectiveness of the developed technique.
IFAC Proceedings Volumes, 2008
In the present work a systematic methodology for computing output stabilizing feedback control la... more In the present work a systematic methodology for computing output stabilizing feedback control laws for nonlinear systems subject to saturating inputs is presented. In particular, the class of L'ure type nonlinear systems is considered. Based on absolute stability tools and a modified sector condition to take into account input saturation effects, an LMI framework is proposed to design the controller. Both regional (local) and global stabilization results are presented. The controller structure is composed by a linear part, an anti-windup loop and a term associated to the output of the dynamic nonlinearity. Convex optimization problems are proposed in order to compute the controller matrices aiming at the maximization of the basin of attraction, or the performance enhancement with a guaranteed region of stability. A numerical example illustrates the potentialities of the methodology.
Int J Robust Nonlinear Contr, 2006
This paper addresses the problem of controlling a linear system subject to actuator saturations a... more This paper addresses the problem of controlling a linear system subject to actuator saturations and to L 2bounded disturbances. Linear matrix inequality (LMI) conditions are proposed to design a state feedback gain in order to satisfy the closed-loop input-to-state stability (ISS) and the closed-loop finite gain L 2 stability. By considering a quadratic candidate Lyapunov function, two particular tools are used to derive the LMI conditions: a modified sector condition, which encompasses the classical sector-nonlinearity condition considered in some previous works, and Finsler's Lemma, which allows to derive stabilization conditions which are adapted to treat multiple objective control optimization problems in a potentially less conservative framework.
IFAC Proceedings Volumes, 2008
In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration o... more In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration of a kinematic controller and a torque controller is investigated. The proposed torque controllers (PTCs) are based on a Gaussian radial basis function neural network (RBFNN) modeling technique, which are used to compensate the mobile robot dynamics, significant uncertainties and disturbances. Also, the PTCs are not dependent of the robot dynamics neither requires the off-line training process. The stability analysis and the convergence of tracking errors to zero, as well as the learning algorithms (for weights, centers, and widths) are guaranteed with basis on Lyapunov's theory. In addition, the simulation results shows the efficiency of the PTCs.
2006 IEEE International Symposium on Circuits and Systems
This paper presents some results on absolute stabilization of nonlinear discrete-time systems und... more This paper presents some results on absolute stabilization of nonlinear discrete-time systems under control saturations. The studied control law consists of the feedback of both the states and of the nonlinearity present in the dynamics of the controlled system. Saturations are taken into account by modelling the nonlinear saturated system through deadzone nonlinearities satisfying a modified sector condition. Thus, as
This paper presents a method for synthesis of dynamic output-feedback controller partially de-pen... more This paper presents a method for synthesis of dynamic output-feedback controller partially de-pended on parameter for networked control systems. The results are described in terms of linear matrix inequal-ities based in a polytopic model for the system. Moreover, a restriction related with temporal performance for the closed-loop system is included in the stability condition. A numerical example and simulation are provided in order to illustrate the proposed method. Keywords— networked control systems, linear matrix inequalities, output dynamic compensator. Resumo— Este artigo apresenta uma proposta para síntese de compensador dinâmico, parcialmente depen-dente de parâmetro, para sistemas controlados via rede. Os resultados são desenvolvidos em termos de desigualda-des matriciais lineares, considerando para isso um modelo politópico para o sistema de controle. Adicionalmente, uma restrição temporal, relacionada ao desempenho do sistema em malha fechada e acrescentadà a condição de e...
2008 IEEE International Conference on Emerging Technologies and Factory Automation, 2008
Based on mechanical energies analysis, the aim of this paper is to propose the use of the relativ... more Based on mechanical energies analysis, the aim of this paper is to propose the use of the relative dorsal position of a 5-link bipedal robot in order to compensate its moments during the walking cycle, leading the previously unstable system to stability. Also, a modification of the PD control law avoids hyperextension at the supporting legpsilas knee. Finally, the model parameters are subjected to percentual variations with respect to the real robot parameters and the robustness of the system is verified through simulations.
IFAC Proceedings Volumes, 2007
This paper presents some results on stability and stabilization of a class of uncertain nonlinear... more This paper presents some results on stability and stabilization of a class of uncertain nonlinear discrete-time systems under control saturations. The studied control law consists of the feedback of both the states and of the nonlinearity present in the dynamics of the controlled system. Saturations are taken into account by modeling the nonlinear saturated system through a deadzone nonlinearity satisfying a modified sector condition. Thus, as for precisely known systems, LMI stability and stabilization conditions are proposed, which can be cast into convex programming problems. Some relations of the proposed results with the poly-quadratic stability concept are included.
Proceedings of the 2010 American Control Conference, 2010
Page 1. Dynamic output compensator design for time-varying discrete time systems with delayed sta... more Page 1. Dynamic output compensator design for time-varying discrete time systems with delayed states Valter JS Leite, Eugênio B. Castelan, Márcio F. Miranda and Dimitri C. Viana AbstractConvex conditions, proposed as ...
53rd IEEE Conference on Decision and Control, 2014
In this paper, we assume that a set of non preemptive controller tasks should be implemented on a... more In this paper, we assume that a set of non preemptive controller tasks should be implemented on a limited computational resource platform, and look for a sampling period assignment that allows to obtain the desirable performance. The problem is formulated as a multi-objective optimization problem under a resource constraint, where the cost functions depend on the sampling period. Linear-quadratic controllers are used, resulting on feedback gains that also depend on the sampling period. The global cost function is chosen as a weighted sum of all plants performances, translating the multi-objective optimization problem into a single-objective one which provides an additional degree of freedom and leads to a set of solutions denoted as Pareto efficient. To handle this additional variable, we assume a Nash bargaining cooperative game. An upper level task performs the update of the sampling period and of the plant input, to be used on a finite-horizon control strategy, for each control loop. A numerical example is provided to illustrate our approach.
2008 16th Mediterranean Conference on Control and Automation, 2008
In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration o... more In this paper, a trajectory tracking control for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains parametric and nonparametric uncertainties. The proposed neural controller (PNC) is constituted of the KNC and the TNC, and designed by use of a modeling technique of Gaussian radial basis function neural networks (RBFNNs). The KNC is applied to compensate the parametric uncertainties of the mobile robot kinematics. The TNC, based on the sliding mode theory, is constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, significant uncertainties, bounded unknown disturbances, neural network modeling errors, influence of payload, and unknown kinematic parameters. To alleviate the problems met in practical implementation using classical sliding mode controllers and to eliminate the chattering phenomenon is used the RNC of the TNC, which is nonlinear and continuous, in lieu of the discontinuous part of the control signals p resent in classical forms. Also, the PNC neither requires the knowledge of the mobile robot kinematics and dynamics nor the time-consuming training process. Stability analysis and convergence of tracking errors to zero as well as the learning algorithms for weights are gua ranteed •with basis on Lyapunov method. Simulations results are provided to show the effectiveness of the proposed approach.
Proceedings of the 2010 American Control Conference, 2010
We present a methodology for computing output feedback control laws for a class of nonlinear syst... more We present a methodology for computing output feedback control laws for a class of nonlinear systems subject to input saturations. This class of systems consists of a L'ure type nonlinear system with some time-varying parameters which are assumed to be real-time available. Based on some tools from the absolute stability theory, on a modified sector condition to take into account input saturation effects, and on the concept of contractive sets applied to a level set obtained from a particular parameter dependent Lyapunov function, an LMI framework is proposed to design dynamic output feedback compensators. Two local stabilization strategies are considered: i) with saturation avoidance, and ii) with saturating actuators. In both cases, convex optimization problems are proposed to compute the controllers matrices aiming at the maximization of the basin of attraction.