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Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution

IEEE Transactions on systems, Man and Cybernetics Part C: Applications and Reviews 2009年第4期39卷 459-473页

作者： Chen, Cheng-Hung Lin, Cheng-Lin Lin, Chin-Teng Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taiping City 411 Taiwan Department of Computer Science Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Brain Research Center University System of Taiwan Hsinchu 300 Taiwan

This study presents an adaptive neural fuzzy network (ANFN) controller based on a modified differential evolution (MODE) for solving control problems. The proposed ANFN controller adopts a functional link neural network as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN controller is a nonlinear combination of input variables. The proposed MODE learning algorithm adopts an evolutionary learning method to optimize the controller parameters. For design optimization, a new criterion is introduced. A hardware-in-the loop control technique is developed and applied to the designed ANFN controller using the MODE learning algorithm. The proposed ANFN controller with the MODE learning algorithm (ANFN-MODE) is used in two practical applications-the planetary-train-type inverted pendulum system and the magnetic levitation system. The experiment is developed in a real-time visual simulation environment. Experimental results of this study have demonstrated the robustness and effectiveness of the proposed ANFN-MODE controller. © 2009 IEEE.

关键词： controllers

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Using an efficient immune symbiotic evolution learning for compensatory neuro-fuzzy controller

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IEEE Transactions on Fuzzy systems 2009年第3期17卷 668-682页

作者： Chen, Cheng-Hung Lin, Cheng-Jian Lin, Ching-Teng Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung County 411 Taiwan Department of Computer Science National Chiao-Tung University Hsinchu 300 Taiwan Brain Research Center University System of Taiwan Hsinchu 300 Taiwan

This paper presents an efficient immune symbiotic evolution learning (ISEL) algorithm for the compensatory neuro-fuzzy controller (CNFC). The proposed ISEL method includes three major components-initial population, subgroup symbiotic evolution, and immune system algorithm. First, the self-clustering algorithm that determines proper input space partitioning and finds the mean and variance of the Gaussian membership functions and number of rules is applied to the initial population. Second, the subgroup symbiotic evolution method that uses each subantibody represents a single fuzzy rule and the evolution of the rule itself. Third, the immune system algorithm uses the clonal selection principle, such that antibodies between others of high similar degree are canceled, and these antibodies, after processing, will have higher quality, accelerating the search, and increasing the global search capacity. Finally, the proposed CNFC with ISEL (CNFC-ISEL) method is adopted to solve several nonlinear control problems. The simulation results have shown that the proposed CNFC-ISEL can outperform other methods. © 2009 IEEE.

关键词： Immune system

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Optimal control for Deterministic Hybrid systems using Dynamic Programming

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IFAC Proceedings Volumes 2009年第17期42卷 316-321页

作者： Matthias Rungger Olaf Stursberg Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel (Germany)

Dynamic programming provides a method to solve hybrid optimal control problems. This contribution extends existing numerical methods originally developed for purely continuous systems, to a class of hybrid systems with autonomous as well as controlled switching behavior. The hybrid dynamics is approximated by a locally consistent discrete Markov decision process. The original optimal control problem is then reformulated for the Markov decision process and solved by standard dynamic programming methods. The convergence of the discrete approximation to the original problem is ensured. The viability of the numerical scheme is illustrated by a two gear transmission system used previously in literature.

关键词： Optimal control Hybrid systems Markov Decision Process Convergence

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New features of Easy Java simulations for 3D modeling

New features of Easy Java simulations for 3D modeling

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作者： Jara, Carlos A. Esquembre, Francisco Candelas, Francisco A. Torres, Fernando Dormido, Sebastián Department of Physics System Engineering and Signal Theory University of Alicante Alicante Spain Department of Mathematics University of Murcia Murcia Spain Department of Computer Science and Automatic Control UNED University Madrid Spain

ISBN: (纸本)9783902661562

This paper presents a new interface framework which has been added to Easy Java Simualtions' environment in order to improve its graphical features for 3D modeling. These new 3D capabilities provide users a set of new view elements which can be used to develop models with a high degree of reality. In this way, Easy Java Simulations becomes a powerful tool to easily and quickly create 3D realistic simulations.

关键词： Virtual reality

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Design of two-dimensional IIR digital structure-specified filters by using an improved genetic algorithm

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Expert systems with Applications 2009年第3 PART 2期36卷 6928-6934页

作者： Tsai, Jinn-Tsong Ho, Wen-Hsien Chou, Jyh-Horng Department of Computer Science National Pingtung University of Education 4- 18 Ming Shen Road Pingtung 900 Taiwan Department of Medical Information Management Kaohsiung Medical University 100 Shi-Chuan 1st Road Kaohsiung 807 Taiwan Institute of System Information and Control National Kaohsiung First University of Science and Technology 1 University Road Yenchao Kaohsiung 824 Taiwan

This work emphasizes solving a design problem of two-dimensional (2-D) infinite-impulse-response (IIR) digital structure-specified filters by using an improved genetic algorithm, which is called the hybrid Taguchi-genetic algorithm (HTGA), and then uses the designed filters to the image processing. The HTGA, used to digital 2-D filters design, can provide the robust optimal solutions. In this work, the HTGA approach is effectively applied to solve a 2-D IIR digital structure-specified filter design problem and is compared with the previous design methods. The design problem of the 2-D IIR digital structure-specified filter is reduced to a constrained minimization problem the solution of which is achieved by the convergence of the HTGA. The computational experiments with the application of the designed filters to focusing the defocused image show that the HTGA approach can obtain better results than the previous design methods. © 2008 Elsevier Ltd. All rights reserved.

关键词： Genetic algorithms

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Distributed Predictive control of Communicating and Platooning Vehicles

Distributed Predictive Control of Communicating and Platooni...

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

作者： Johannes Dold Olaf Stursberg Institute of Control and System Theory Department of Electrical Engineering and Computer ScienceUniversity of Kassel (Germany)

This paper proposes an approach to robust model predictive control for distributed systems with chain *** by the application of a platoon of autonomous vehicles in linear motion, we consider a system structure in which the dynamics of each subsystem is specified in relative error coordinates and in affine form, considering the input of the preceding subsystem as disturbance(since locally not known a-priori). Employing principles of RMPC suggested before by Kerrigan et al. for the case of non-distributed systems, we first show how robust strong feasibility can be guaranteed for the distributed case. The drawback of this approach is that the zone of robustness is obtained in a relatively conservative form, and that the control error, in general, cannot be forced to zero. Thus,in the second part, we include a scheme for communicating predicted control trajectories between the subsystems in order to improve the control performance and to render the solution less conservative.

关键词： agent Distributed Predictive control of Communicating and Platooning Vehicles

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Function Approximation for the Deterministic Hamilton-Jacobi-Bellman Equation

Function Approximation for the Deterministic Hamilton-Jacobi...

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

作者： Matthias Rungger Olaf Stursberg Institute of Control and System Theory Department of Electrical Engineering and Computer ScienceUniversity of Kassel (Germany)

Based on Gaussian basis functions, a new method for calculating the Hamilton-Jacobi-Bellman equation for deterministic continuous-time and continuous-valued optimal control problems is proposed. A semi-Lagrangian discretization scheme is used to obtain a discrete-time finite-state approximation of the continuous dynamics. The value function of the discretized system is approximated by a Gaussian network. Limit behavior analysis provides a proof of convergence for the scheme. The performance of the presented approach is demonstrated for an underpowered inverted pendulum as numerical ***, a comparison to the approximation by continuous piecewise affine functions(the current state of the art) shows the benefits of the approximation technique proposed here.

关键词： Gaussian Function Approximation for the Deterministic Hamilton-Jacobi-Bellman Equation Hamilton Jacobi

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Cognitive safety control for human-machine interaction 10

Cognitive safety control for human-machine interaction

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2009 10th European control Conference, ECC 2009

作者： Ding, Hao Kain, Sebastian Schiller, Frank Stursberg, Olaf Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Kassel34109 Germany Institute of Information Technology in Mechanical Engineering Technische Universität München Garching bei München85748 Germany

ISBN: (纸本)9783952417393

In order to introduce cognition, i.e. perception and autonomously reconfigured control, into manufacturing systems for increasing the flexibility and adaptivity this paper proposes an architecture of a cognitive safety controller (CSC). The CSC consists of a strategic controller (SC) and an operational controller (OC): the SC iteratively computes (sub-)optimal control strategies taking dynamic models, safety specifications, and learned knowledge into account. The operational controller (OC) provides certified safety by safe realization of the strategy computed by the SC. The paper illustrates the application of the CSC to a cognitive manufacturing system (CMS) in which a robot and a human operator share a workspace. Important components of this application are a procedure to compute (sub)optimal strategies for varying control specifications online and a scheme for implementing the strategy on a programmable logic controller (PLC). © 2009 EUCA.

关键词： controllers

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Increasing reliability of intelligent manufacturing systems by adaptive optimization and safety supervision

Increasing reliability of intelligent manufacturing systems ...

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作者： Ding, Hao Kain, Sebastian Schiller, Frank Stursberg, Olaf Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel D-34109 Kassel Germany Institute of Information Technology in Mechanical Engineering Technische Universität München D-85748 Garching near Munich Germany

ISBN: (纸本)9783902661463

For concurrent consideration of reliability and safety of manufacturing systems on the one hand, and flexibility and performance on the other, a specialized control architecture was proposed recently. It consists of a strategic controller for online computing (sub-)optimal control strategies under consideration of dynamic models, safety specifications, and learned knowledge. The second building block is an operational controller for providing certified safety when dealing with behaviors that are not completely predictable, for instance in case of faults. This paper extends the architecture by a specific technique for the strategic controller: For the case of an intelligent manufacturing system which reacts adaptively to a human operator, control trajectories for a robot arm are computed online such that collision with the operator is excluded. The computation is based on solving a mixed-integer programming problem that takes a dynamic safety area around the operator into account as constraint. © 2009 IFAC.

关键词： Reliability

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Optimal path planning in the workspace for articulated robots using mixed integer programming

Optimal path planning in the workspace for articulated robot...

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2009 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Hao Ding Mingxiang Zhou Olaf Stursberg Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Automatic Control Engineering Munchen Germany

This paper considers the task of path planning for articulated robots such that the end effector is driven optimally between two points in the workspace while collision with dynamic obstacles is avoided. Compared to path planning in the configuration space, approaches in the workspace save the computationally expensive step of mapping obstacles from the workspace into the configuration space. The method presented here builds on a problem formulation as a mixed-integer program considering time-varying constraints resulting from moving obstacles, as well as state and input constraints depending on the region of the work space. The method is applied to a two-link robot with static and moving obstacles and is evaluated for different situations.

关键词： Path planning Linear programming Orbital robotics Intelligent robots Dynamic programming Trajectory Collision avoidance Motion planning Robotics and automation Automatic control

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