Low-cost optimal state feedback fuzzy control of nonlinear second-order servo systems

This paper discusses low-cost optimal Takagi-Sugeno state feedback fuzzy controllers for the position control of servo systems where the process is modeled by second-order linear dynamics with an integral component, and saturation and dead zone input static nonlinearity. The state feedback gain matrices in the rule consequents of the fuzzy controllers are obtained by the combination of the parallel distributed compensation and linear-quadratic regulator applied to each rule. An example concerning the position control of a DC servo system laboratory equipment is offered and experimental results are included.

[1]  S. Kovács,et al.  A Brief Survey and Comparison on Various Interpolation Based Fuzzy Reasoning Methods , 2006 .

[2]  Kin Fong Lei,et al.  Complexity reduction of singleton based neuro-fuzzy algorithm , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[3]  Kazuo Tanaka,et al.  Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach , 2008 .

[4]  Kazuo Tanaka,et al.  Parallel distributed compensation of nonlinear systems by Takagi-Sugeno fuzzy model , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[5]  Yeung Yam,et al.  SVD-based reduction to MISO TS models , 2003, IEEE Trans. Ind. Electron..

[6]  Daniel Hladek,et al.  MULTI-ROBOT CONTROL SYSTEM FOR PURSUIT-EVASION PROBLEM , 2009 .

[7]  Slawomir Wesolkowski,et al.  Multiobjective evolutionary algorithm with risk minimization applied to a fleet mix problem , 2010, IEEE Congress on Evolutionary Computation.

[8]  Changliang Xia,et al.  A Neural-Network-Identifier and Fuzzy-Controller-Based Algorithm for Dynamic Decoupling Control of Permanent-Magnet Spherical Motor , 2010, IEEE Transactions on Industrial Electronics.

[9]  Lu Fang,et al.  Feedback-Feedforward PI-Type Iterative Learning Control Strategy for Hybrid Active Power Filter With Injection Circuit , 2010, IEEE Transactions on Industrial Electronics.

[10]  Igor Skrjanc,et al.  Online fuzzy identification for an intelligent controller based on a simple platform , 2009, Eng. Appl. Artif. Intell..

[11]  Okyay Kaynak,et al.  Type 2 Fuzzy Neural Structure for Identification and Control of Time-Varying Plants , 2010, IEEE Transactions on Industrial Electronics.

[12]  Richard J. Duro,et al.  Unmixing Low-Ratio Endmembers in Hyperspectral Images Through Gaussian Synapse ANNs , 2010, IEEE Transactions on Instrumentation and Measurement.

[13]  József K. Tar,et al.  Generic two-degree-of-freedom linear and fuzzy controllers for integral processes , 2009, J. Frankl. Inst..

[14]  Teresa Orlowska-Kowalska,et al.  Adaptive Sliding-Mode Neuro-Fuzzy Control of the Two-Mass Induction Motor Drive Without Mechanical Sensors , 2010, IEEE Transactions on Industrial Electronics.