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An input-output clustering approach for structure identification of T-S fuzzy neural networks

An input-output clustering approach for structure identifica...

引用

ieee symposium on computational intelligence in control and automation, cica

作者： Wei Li Honggui Han Junfei Qiao College of Electronic Information and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligence System Beijing China

ISBN: (纸本)9781479945290

This paper proposes a novel input-output clustering approach for structure identification of T-S fuzzy neural networks. This approach consists of two phases. Firstly, k-means clustering method is applied to the input data to provide the initial clusters of the input space. Secondly, check whether the sub-clustering is needed for each input cluster by considering the corresponding output variation and then apply the k-means method to further partition those input clusters needed sub-clustering. Applying the above process recursively leads to the structure identification of a T-S fuzzy neural network and then the parameter identification is completed by using the gradient learning algorithm. The experiments by applying the proposed method to several benchmark problems show better performance compared with many existing methods and then verify the effectiveness and usefulness of the proposed method.

关键词： Clustering methods Fuzzy neural networks Accuracy Clustering algorithms Context Fuzzy control Partitioning algorithms

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Backlash compensation by neural-network online learning

Backlash compensation by neural-network online learning

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ieee International symposium on computational intelligence in Robotics and automation

作者： He, C Zhang, YH Meng, M Beijing Inst Technol Dept Automat Control Beijing Peoples R China

ISBN: (纸本)0780372034

To eliminate the influences of backlash nonlinearity generally existing in servo systems, a new neural-network online learning compensation method was presented. Not basing on the identification of backlash nonlinearity, but using the online learning of neural networks, it made the output error of the system approximate to zero so that the system output could accurately follow the given input. To cooperating with this new method, the self-organizing fuzzy CMAC with Gauss basis functions (SOGFCMAC) neural network was proposed on the basis of absorbing the advantages of traditional CMAC neural networks, fuzzy logic, basis functions and self-organizing feature map (SOFM) algorithm. Finally, an actual experimental platform of servo system with low power was built to do the experimental researches. Experimental results show that the method presented in this paper can effectively get rid of the limit cycle caused by the backlash nonlinearity, and remarkably improve the system accuracy.

关键词： Self organizing maps

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Extreme learning ANFIS for control applications

Extreme learning ANFIS for control applications

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ieee symposium on computational intelligence in control and automation, cica

作者： G. N. Pillai Jagtap Pushpak M. Germin Nisha Department of Electrical Engineering Indian Institute of Technology Roorkee Roorkee India

This paper proposes a new neuro-fuzzy learning machine called extreme learning adaptive neuro-fuzzy inference system (ELANFIS) which can be applied to control of nonlinear systems. The new learning machine combines the learning capabilities of neural networks and the explicit knowledge of the fuzzy systems as in the case of conventional adaptive neuro-fuzzy inference system (ANFIS). The parameters of the fuzzy layer of ELANFIS are not tuned to achieve faster learning speed without sacrificing the generalization capability. The proposed learning machine is used for inverse control and model predictive control of nonlinear systems. Simulation results show improved performance with very less computation time which is much essential for real time control.

关键词： Training Mathematical model Equations Neural networks Prediction algorithms Training data Algorithm design and analysis

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Modeling and optimized control of photovoltaic energy conversion systems

Modeling and optimized control of photovoltaic energy conver...

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7th ieee International symposium on Applied computational intelligence and Informatics, SACI 2012

作者： Gana, O. Prostean, O. Vasar, C. Babescu, M. Politehnica University of Timisoara Department of Electrical Engineering Romania Politehnica University of Timisoara Department of Automation and Applied Informatics Romania

ISBN: (纸本)9781467310116

The present paper presents specific issues that arise in Photovoltaic Energy Conversion Systems, being focused on maximizing the output power. There is proposed a model for Photovoltaic PV panel external characteristics. The coordinates of maximum power point are determined and used for imposing the appropriate load resistance to maximize the provided power. A comparison is made considering the classical control methods and the proposed optimized method, that prove better performances than methods based on output power measurement. ©2012 ieee.

关键词： Solar panels

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Proceedings of ieee International symposium on computational intelligence in Robotics and automation, CIRA

Proceedings of IEEE International Symposium on Computational...

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2003 ieee International symposium on computational intelligence in Robotics and automation, CIRA 2003

ISBN: (纸本)0780378660

The proceedings contain 266 papers. The topics discussed include: on using discretized cohen-Grossberg node dynamics for model-free actor-critic neural learning in non-Markovian domains;a parameter control method inspired from neuromodulators in reinforcement learning;manipulation of hidden units activities for fault tolerant multi-layer neural networks;state estimation for flexible joint manipulators using stable neural networks;a text processing kohonen neural network;software tool development for marker making operations in textile industry;genetic design of decentralized controllers for 5dof robotic manipulator;design of sliding mode power system stabilizer via genetic algorithm;an operation planning method for a demand-bus system based on local search of autonomous agents;and an analysis of U-mart experiments by machine and human agents.

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Proceedings of ieee International symposium on computational intelligence in Robotics and automation, CIRA

Proceedings of IEEE International Symposium on Computational...

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2003 ieee International symposium on computational intelligence in Robotics and automation, CIRA 2003

ISBN: (纸本)0780378660

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Linear synchronous motor servo drive based on adaptive wavelet neural network

Linear synchronous motor servo drive based on adaptive wavel...

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2005 ieee International symposium on computational intelligence in Robotics and automation CIRA 2005

作者： Lin, Faa-Jeng Shen, Po-Hung IEEE Department of Electrical Engineering National Dong Hwa University Hualien 974 Taiwan

An adaptive wavelet neural network (AWNN) control system is proposed to control the position of the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive system to track periodic reference trajectories in this study. In the proposed AWNN control system, a WNN with accurate approximation capability is employed to approximate the unknown dynamics of the PMLSM, and a robust term is proposed to confront the inevitable approximation errors due to finite number of wavelet basis functions and disturbances including the friction force. The adaptive learning algorithm that can learn the parameters of weight, dilation and translation of the WNN on line is derived using Lyapunov stability theorem. Moreover, to relax the requirement for the bound of uncertainty in robust term, which comprises a minimum approximation error, optimal parameter vectors, higher-order terms in Taylor series and friction force, an adaptive bound estimation law is investigated where a simple adaptive algorithm is utilized to estimate the bound of uncertainty. Furthermore, the experimental results due to periodic reference trajectories show that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties. © 2005 ieee.

关键词： Synchronous motors

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Proceedings of ieee International symposium on computational intelligence in Robotics and automation, CIRA

Proceedings of IEEE International Symposium on Computational...

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2003 ieee International symposium on computational intelligence in Robotics and automation, CIRA 2003

ISBN: (纸本)0780378660

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Intelligent variable joint impedance control and development of a new whole-sensitive anthropomorphic robot arm

Intelligent variable joint impedance control and development...

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International symposium on computational intelligence in Robotics and automation

作者： Tsetserukou, Dzmitry Tadakuma, Riichiro Kajimoto, Hiroyuki Kawakami, Naoki Tachi, Susumu Univ Tokyo Bunkyo Ku 7-3-1 Hongo Tokyo 1138656 Japan Univ Tokyo Univ Electrocommun Tokyo 1138654 Japan

ISBN: (纸本)9781424407897

The paper focuses on design and control of a new anthropomorphic robot arm enabling the torque measurement in each joint to ensure safety while performing tasks of physical interaction with human and environment. When the contact of the arm with an object occurs, local impedance algorithm provides active compliance of corresponding robot arm joint. Thus, the A-hole structure of the manipulator can safely interact with unstructured environment. A novel variable control strategy was elaborated to increase the robot functionality and to achieve human-like dynamics of interaction. In the paper, we detail the design procedure of 4-DOF robot arm and optical torque sensors. The experimental results of variable joint impedance control show that proposed approach not only pro-sides safe interaction of entire structure of robot arm with a person, but also improves the effectiveness of contact task performance, enables thus to contact with environment in a delicate manner.

关键词： Robotic arms

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On control system design of a human-machine cooperative system considering self-shaping characteristics of its human operator and recognition of object dynamics variation

On control system design of a human-machine cooperative syst...

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2003 ieee International symposium on computational intelligence in Robotics and automation, CIRA 2003

作者： Takeshi, I. Yoshiki, M. Dept. of Applied Computer Eng. Tokai University Japan Dept. of Mech. and Control Fng Tokyo Inst. of Technology Japan

ISBN: (纸本)0780378660

This paper deals with control of human-machine cooperative systems considering maneuverability for their human operators. At first, the general structure and the parameterization of the controlled systems are outlined. Second, it is experimentally verified that self-shaping characteristics of a human operator exists in a human-machine cooperative system similarly in manual control systems and that the characteristics can be used for specifying desirable frequency characteristics of the maneuver transfer function, a transfer function from operational force to motion of object at the operational point. Then, a control design procedure that specifies two closed-loop transfer functions of the controlled system independently is proposed. On the procedure, the maneuver transfer function of object dynamics variation is also specified considering recognition of the variation. Finally, experiments on human-machine cooperative task carried out, and the validity of the proposed design procedure is confirmed. © 2003 ieee.

关键词： Transfer functions

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