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作者： Angulo, Marco Tulio Levant, Arie Department of Control Engineering and Robotics Electrical Engineering Division Faculty of Engineering Mexico School of Mathematical Sciences Tel-Aviv University Ramat-Aviv 69978 Tel-Aviv Israel

ISBN: (纸本)9783902661593

Finite-Time stability of Linear Time Invariant systems with matched perturbations using dynamic output feedback is achieved under the assumptions of well-defined relative degree and a known bound of the perturbations. The approach is based on high order sliding modes, using global controllers and differentiator. A separation criteria that allows to detect the convergence of the differentiator and posterior gain adaptation is presented. Analysis of the performance under noise and sampling is presented.

关键词： Sliding mode control

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Robust Output Regulation with Exact Unmatched Uncertainties Compensation Based on HOSM Observation

Robust Output Regulation with Exact Unmatched Uncertainties ...

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Joint 48th IEEE Conference on Decision and control and 28th Chinese control Conference

作者： Alejandra Ferreira de Loza Francisco Bejarano Leonid Fridman the Department of Control and Robotics Division of Electrical EngineeringEngineering FacultyNational Autonomous University of Mexico （UNAM）

This manuscript tackles the regulation problem of linear time invariant systems with unmatched perturbations. A high order sliding mode observer is used allowing theoretically exact state and perturbation estimation. A compensation control approach based on the identified perturbation values is proposed ensuring exact regulation of the unmatched states. A simulation example shows the feasibility of this approach.

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Output-based Finite Time control of LTI systems with matched perturbations using HOSM

Output-based Finite Time Control of LTI systems with matched...

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Joint 48th IEEE Conference on Decision and control and 28th Chinese control Conference

作者： Marco Tulio Angulo Leonid Fridman Department of Control Engineering and Robotics Electrical Engineering DivisionFaculty of EngineeringNational Autonomous University of Mexico (UNAM)

Finite Time Stability of LTI systems with matched perturbations using dynamic output feedback is achieved under the assumptions of strong observability,controllability and known bounds for the *** is shown that only global controllers are well suited for this *** cases are studied: when the relative degree is well-defined and when it is *** examples are presented in order to illustrate the proposed approach.

关键词： origin Output-based Finite Time control of LTI systems with matched perturbations using HOSM LTI

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On Robust Output Based Finite-Time control of LTI systems using HOSMs

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IFAC Proceedings Volumes 2009年第17期42卷 222-227页

作者： Marco Tulio Angulo Arie Levant Department of Control Engineering and Robotics Electrical Engineering Division Faculty of Engineering National Autonomous University of Mexico (UNAM) Mexico School of Mathematical Sciences Tel-Aviv University Ramat-Aviv 69978 Tel-Aviv Israel

关键词： Dynamic output feedback sliding-mode control

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PSO-based controller design for rotary inverted pendulum system

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Journal of Applied Sciences 2008年第16期8卷 2907-2912页

作者： Hassanzadeh, Iraj Mobayen, Saleh Research Laboratory of Robotics Department of Control Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

This research presents an optimum approach for designing Rotary Inverted Penduhnn (RIP) controller using PSO algorithm. The primary design goal is to balance the pendulum in an inverted position and the control criterion is to minimize the integral absolute error of system angles. Simulation results demonstrate the robustness and effectiveness of proposed controller with regard to parameter variations, various reference trajectory and load disturbances. The proposed method can be considered as a promising way for control of various similar nonlinear systems. © 2008 Asian Network for Scientific Information.

关键词： Genetic algorithms

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Design of augmented extended and unscented Kalman filters for differential-drive mobile robots

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Journal of Applied Sciences 2008年第16期8卷 2901-2906页

作者： Hassanzadeh, Iraj Fallah, Mehdi Abedinpour Research Laboratory of Robotics Department of Control Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

In this study, we present the local reconstruction of differential-drive mobile robots position and orientation with an accurate odometry calibration. Starting from the encoders readings and assuming an absolute measurement available, Augmented Extended and Unscented Kalman Filters (AEUKF) are proposed to localize the vehicle while estimating a proper set of odometric parameters. In order to compare their estimation performances explicitly, both observers are designed for the same mobile robot model and run with the equal covariance matrices under the identical initial conditions. In the simulation results, it is shown that Augmented Unscented Kalman Filter (AUKF) outperforms the Augmented Extended Kalman Filter (AEKF). © 2008 Asian Network for Scientific Information.

关键词： Mobile robots

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GA based input-output feedback linearization controller for rotary inverted pendulum system

GA based input-output feedback linearization controller for ...

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International Symposium on Mechatronics and Its Applications, ISMA

作者： Iraj Hassanzadeh Saleh Mobayen Research Laboratory of Robotics Control Engineering Department Faculty of Electrical Computer Engineering University of Tabriz Tabriz Iran

This paper presents an optimum approach to design input-output feedback linearization (IOFL) controller for a rotary inverted pendulum (RIP) using the Binary Genetic Algorithm. Genetic Algorithms (GAs) are stochastic global search methods that emulate the process of natural evolution and because of their simplicity and robustness, they are more popular and applicable. The primary design goal is to minimize the integral absolute error of system angles and velocities and balance the pendulum in the inverted position by minimizing overshoot, settling time and rise time of step response. An objective function using these indexes is established. Then by minimizing the objective function using Binary Genetic algorithm, the optimal controller parameters can be assigned. Simulation results verified capable and competent characteristics of proposed optimal feedback linearization controller. The proposed method can be considered as a promising way for control of various similar nonlinear systems.

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Multi-agent hierarchical architecture modeling kinematic chains employing continuous RL learning with fuzzified state space

Multi-agent hierarchical architecture modeling kinematic cha...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： John N. Karigiannis Costas S. Tzafestas Faculty of Electrical and Computer Engineering Division of Signals Control and Robotics National and Technical University of Athens Athens Greece

In the context of multi-agent systems, we are proposing a hierarchical robot control architecture that comprises artificial intelligence (AI) techniques and traditional control methodologies, based on the realization of a learning team of agents in a continuous problem setting. In a multi-agent system, action selection is important for cooperation and coordination among the agents. By employing reinforcement learning (RL) methods in a fuzzified state-space, we accomplish to design a control architecture and a corresponding methodology, engaged in a continuous space, which enables the agents to learn, over a period of time, to perform sequences of continuous actions in a cooperative manner, in order to reach their goal without any prior generated task model. By organizing the agents in a nested architecture, as proposed in this work, a type of problem-specific recursive knowledge acquisition is attempted. Furthermore, the agents try to exploit the knowledge gathered in order to be in position to execute tasks that indicate certain degree of similarity. The agents correspond in fact to independent degrees of freedom of the system, and achieve to gain experience over the task that they collaboratively perform, by exploring and exploiting their state-to-action mapping space. A numerical experiment is presented in this paper, performed on a simulated planar 4 degrees of freedom (DOF) manipulator, in order to evaluate both the proposed hierarchical multi-agent architecture as well as the proposed methodological framework. It is anticipated that such an approach can be highly scalable for the control of robotic systems that are kinematically more complex, comprising multiple DOFs and potentially redundancies in open or closed kinematic chains, particularly dexterous manipulators.

关键词： Kinematics State-space methods Learning Multiagent systems Robot control Artificial intelligence control systems Manipulators Organizing Knowledge acquisition

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Design of MIMO controller for a manipulator using Tabu Search algorithm

Design of MIMO controller for a manipulator using Tabu Searc...

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International Conference on Intelligent and Advanced Systems, ICIAS

作者： I. Hassanzadeh S. Mobayen H. Kharrati Research Laboratory of Robotics Control Engineering Department Faculty of Electrical & Computer Engineering University of Tabriz Tabriz Iran

In this paper, we present an optimum approach to design a MIMO controller for a manipulator using discrete tabu search (TS) algorithm. In the first step, the TS algorithm is reviewed and then we employ the proposed method in order to assign efficiently the optimal PID controller parameters. The design goal is to minimize the integral absolute error and reduce transient response by minimizing overshoot, settling time and rise time of the system. A 5-bar-linkage is considered as a case study. We define an objective function including these indexes. Then by minimizing this function using discrete TS algorithm, controller parameters design is performed efficiently and quickly. Superior features of this algorithm are fast tuning of PID parameters, rapid convergence, less computational burden and capability to avoid from local minima. Simulation results demonstrate that our proposed TS method compared with other heuristic method, i.e., the genetic algorithm (GA) is more efficient in terms of improving the step response of the robot.

关键词： Robots Algorithm design and analysis Manipulators Cost function MIMO Mathematical model Heuristic algorithms

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Artificial Behavioral System By Sensor-Motor Mapping Strategy For Multi-Objective Robot Tasks

Artificial Behavioral System By Sensor-Motor Mapping Strateg...

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International Conference on Natural Computation (ICNC)

作者： Evren Daglarli Hakan Temeltas Control Engineering Department Robotics Laboratory Electrical-Electronics Engineering Faculty Istanbul Technical University Maslak Istanbul Turkey

In this study, behavioral system based robot control architecture is built up for a four-wheel driven and four-wheel steered mobile robot. Behavioral system is determined as evolutionary neural-fuzzy inference system for behavior generation and self-learning processes in the general robot control architecture. The kinematics and dynamic model of the mobile robot with non-holonomic constraints is used as present structure which is modeled in previous studies. The posture and speed of the robot and the configurations, speeds and torques of the wheels can be observed from the simulation plant and virtual reality viewer. The behaviors are investigated regarding their gains, fuzzy inference structures, real-time applicability and their coordination.

关键词： Robot sensing systems Mobile robots Robot kinematics Laboratories Robot control control systems Orbital robotics Sensor systems Fuzzy logic Intelligent robots

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