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A novel fuzzy framework for nonlinear system control

FUZZY SETS AND systemS 2010年第21期161卷 2746-2759页

作者： Liu, Jie Wang, Wilson Golnaraghi, Farid Kubica, Eric Lakehead Univ Dept Mech Engn Thunder Bay ON P7B 5E1 Canada Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA Simon Fraser Univ Sch Engn Sci Surrey BC V3T 0A3 Canada Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada

nonlinear PID and gain scheduling controls have attracted much research interests in recent years. These control strategies can accommodate some nonlinear characteristics by allowing the gains varied or rescheduled as a function of system states. In this paper, a novel fuzzy framework is developed to transfer this type of nonlinear controller to its fuzzy domain representation. It is proved that the resulting fuzzy controller is functionally exactly identical to the original control system. One of the benefits of the suggested approach is that it provides a well-defined prototype for the design of fuzzy control system. The resulting linguistic representation can facilitate investigation in linguistic terms into how the controller operates, whereas expert knowledge can be effectively implemented to improve control performance. The viability of the proposed mapping technique is demonstrated by using simulations corresponding to a flexible-link robot. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Fuzzy control Fuzzy mapping nonlinear system control nonlinear PID control

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NN/RISE-based controller Design for a Class of Uncertain nonlinear systems with Time-varying Constraints

NN/RISE-based Controller Design for a Class of Uncertain Non...

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IEEE International Conference on Information and Automation (ICIA)

作者： Fan, Bo Yang, Qinmin Sun, Youxian Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9781509041022

This paper presents a novel adaptive control strategy for the tracking control of a class of uncertain nonlinear systems with external disturbances as well as for placing arbitrary user-defined time-varying constraints on the system state. As such, our contribution is a step forward beyond the usual stabilization result to show that the states of the plant not only converge asymptotically, but also remain within user defined, time-varying bound functions. To prove our new results, an error transformed technique is firstly established to generate a new uncertain nonlinear system, whose asymptotic stability guarantees both the satisfaction of the time-varying restrictions and the asymptotic tracking performance of the original system. The uncertainties of the transformed system are overcome by an online neural network (NN) approximator, while the external disturbances and NN reconstruction error are compensated by the robust integral of the sign of the error (RISE) signal. Via standard Lyapunov method, semi-global asymptotic tracking performance is theoretically guaranteed, and all the closed-loop signals are bounded. The requirement for a prior knowledge of bounds of uncertain terms is relaxed. Finally, simulation results demonstrate the merits of the proposed controller.

关键词： Time-varying constraints nonlinear system control asymptotic stability neural network

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Optimized Diving Velocity and Depth control for Diver's Automatic Buoyancy control Device

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MARINE TECHNOLOGY SOCIETY JOURNAL 2015年第1期49卷 124-130页

作者： Riznar, Matej Valenko, Darko Golob, Marjan Muskinja, Nenad Univ Maribor Fac Elect Engn & Comp Sci SLO-2000 Maribor Slovenia Emsiso Doo Maribor Slovenia

In this article the Obsigni'ancrmultiohjeCtive optimization t of 41-11:*-mbi7del-base'd;proportional-integral-deriyative:,(PID) control system fer diVers-;:budyariCy Onto! device (BCD)is presented Changing and maintaining depth (ST,artiessential task (1) diving,=f0r*hiChfthe,divertypIcally;useSpanual:.,control of twd:pnqumatic valves An effeCtiVe automatic control Of the BCD Can be benefi5ial irfemeteurdivirig, ****toillatiC;'aseenclingfri GA'S& Of critical life of the diver, poor visibility, when be:1h Ofthe:cliVershands are requited for other tas4;letciln ***1 Otoblernspused Oy-;internal nonlinear 4nOnicOf the 14O0 hardware'three,Main control aspicti-iwere;OonSideted: pdSitioTi or depth Of thellIt(r;-Vertio4 Meening the:asCending Or de-, *ending 'velocity of ***(upply consiimptibri: OorifthatIwelexaMined and implemented a ornbined deptIlland,verticaF:yelocity control, Whittkya;cortfigured as a ca/Scaded controller set with outerdeptilandjinrier vertical velocity, control loops Such controller setup cOtild easily irnblernenttlie specified Iftnitations of the BCIfi;s vertical VeleCity, "Willa, a critical for 000er deco hipteSsion procedure;-, While the diveris *** environment the optimization Of the, controller Paratneters was achieved With a differential evolution 000 optimum search algOrithm. Obtained results were then compared to a manually driven BCD "i in a simulated: enVirontrient.

关键词： buOyario'y control device difforentiarevOlUifon Optimization Placontr011et nonlinear system control position and velOcity- control

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Stabilization of a nonlinear wing section: a case study for control with inexact nonlinearity cancellations

Stabilization of a nonlinear wing section: a case study for ...

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European control Conference (ECC)

作者： Innocenti, Giacomo Paoletti, Paolo Univ Florence Dipartimento Ingn Informaz Via S Marta 3 I-50139 Florence Italy Univ Liverpool Sch Engn Liverpool L69 3GH Merseyside England

ISBN: (纸本)9783952426937

control of nonlinear systems with uncertain information about the nonlinearity poses significant challenges, as any mismatch between the true nonlinearity and the one assumed for controller design can result in performance degradation or even instability. In this paper we merge optimal nonlinearity approximations with controller dissipativity properties to find explicit expressions for stabilizing output feedback controllers and estimates of the basin of attraction of the equilibrium in the origin. The control of an aeroelastic system with structural nonlinearity is used as a case study to discuss in detail the proposed approach and to demonstrate its effectiveness.

关键词： aerospace components approximation theory control nonlinearities control system synthesis elasticity feedback nonlinear control systems stability aeroelastic system control controller design controller dissipativity properties inexact nonlinearity cancellations nonlinear system control nonlinear wing section stabilization optimal nonlinearity approximation output feedback controller stabilization performance degradation structural nonlinearity uncertain information Aerodynamics Chlorine Mathematical model nonlinear dynamical systems Output feedback Standards Yttrium

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Output Feedback control Design with Guaranteed Cost of Takagi-Sugeno Fuzzy systems 7

Output Feedback Control Design with Guaranteed Cost of Takag...

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Joint 7th International Conference on Soft Computing and Intelligent systems (SCIS) and 15th International Symposium on Advanced Intelligent systems (ISIS)

作者： Yoneyama, Jun Hoshino, Kenta Aoyama Gakuin Univ Dept Elect & Elect Engn Chuo Ku 5-10-1 Fuchinobe Sagamihara Kanagawa 2525258 Japan

ISBN: (纸本)9781479959556

The paper is concerned with control design via output feedback controller for fuzzy systems. Many results on the state feedback control design have been given in the literature. In the actual situation, however, the state of the system is rarely measured and the output feedback control design is desired. In this paper, guaranteed cost control via output feedback control for fuzzy systems is considered and a control design of stabilizing controllers with guaranteed cost is proposed. The stability analysis of the closed-loop system and controller design are given in terms of LMI conditions, which are less conservative than the existing results.

关键词： Takagi-Sugeno fuzzy systems nonlinear system control guaranteed cost control linear matrix inequality

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Performance-Adaptive control system for a Hammerstein system Using GPGPU 19

Performance-Adaptive Control System for a Hammerstein System...

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19th IEEE International Conference on Emerging Technology and Factory Automation (ETFA)

作者： Sato, Takao Kurahashi, Daiki Yamamoto, Toru Araki, Nozomu Konishi, Yasuo Univ Hyogo Grad Sch Engn Dept Mech Engn Div Mech Syst Kobe Hyogo 6500044 Japan Hiroshima Univ Fac Engn Div Elect Syst & Math Engn Hiroshima 730 Japan

ISBN: (纸本)9781479948451

In this study, a nonlinear system is controlled using a linear adaptive method. A nonlinear system is approximated a linear model at each operating point, and a control law is designed based on the approximated linear model. To obtain a suitable linear model at each operating point, many linear models are simultaneously identified. However, the computation load for identifying many models is considerably heavy. Hence, many linear models are identified using General-Purpose computing on Graphics Processing Units (GPGPU). In this study, the assessment of modeling performance is newly introduced. As a result, the control system is updated only when modeling performance is degraded, and frequent update of a control law can be avoided. Finally, numerical results are shown to demonstrate the effectiveness of the proposed method.

关键词： adaptive control approximation theory control system synthesis graphics processing units identification linear systems nonlinear control systems GPGPU Hammerstein system computation load control law design control system update general-purpose computing-on-graphics processing units linear adaptive method linear model approximation modeling performance assessment nonlinear system control operating point performance-adaptive control system system identification Adaptation models Computational modeling control systems Educational institutions Load modeling nonlinear systems Numerical models

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Adaptive Inverse Optimal Neuromuscular Electrical Stimulation

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IEEE TRANSACTIONS ON CYBERNETICS 2013年第6期43卷 1710-1718页

作者： Wang, Qiang Sharma, Nitin Johnson, Marcus Gregory, Chris M. Dixon, Warren E. Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA Univ Pittsburgh Dept Mech Engn & Mat Sci Pittsburgh PA 15261 USA Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA H Johnson Vet Affairs Med Ctr Charleston SC 29401 USA Med Univ S Carolina Dept Hlth Sci & Res Charleston SC 29425 USA

Neuromuscular electrical stimulation (NMES) is a prescribed treatment for various neuromuscular disorders, where an electrical stimulus is provided to elicit a muscle contraction. Barriers to the development of NMES controllers exist because the muscle response to an electrical stimulation is nonlinear and the muscle model is uncertain. Efforts in this paper focus on the development of an adaptive inverse optimal NMES controller. The controller yields desired limb trajectory tracking while simultaneously minimizing a cost functional that is positive in the error states and stimulation input. The development of this framework allows tradeoffs to be made between tracking performance and control effort by putting different penalties on error states and control input, depending on the clinical goal or functional task. The controller is examined through a Lyapunov-based analysis. Experiments on able-bodied individuals are provided to demonstrate the performance of the developed controller.

关键词： Functional electrical stimulation (FES) inverse optimal control Lyapunov stability neural network (NN) neuromuscular electrical stimulation nonlinear system control

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A Functional-Link-Based Neurofuzzy Network for nonlinear system control

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IEEE TRANSACTIONS ON FUZZY systemS 2008年第5期16卷 1362-1378页

作者： Chen, Cheng-Hung Lin, Cheng-Jian Lin, Chin-Teng Natl Chiao Tung Univ Dept Elect & Control Engn Hsinchu 300 Taiwan Natl Chin Yi Univ Technol Dept Comp Sci & Engn Taichung 411 Taiwan Natl Chiao Tung Univ Dept Comp Sci Hsinchu 300 Taiwan Univ Syst Taiwan Brain Res Ctr Hsinchu 300 Taiwan

This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural network (FLNN) to the consequent part of the fuzzy rules. This study uses orthogonal polynomials and linearly independent functions in a functional expansion of the FLNN. Thus, the consequent part of the proposed FLNFN model is a nonlinear combination of input variables. An online learning algorithm, which consists of structure learning and parameter learning, is also presented. The structure learning depends on the entropy measure to determine the number of fuzzy rules. The parameter learning, based on the gradient descent method, can adjust the shape of the membership function and the corresponding weights of the FLNN. Furthermore, results for the universal approximator and a convergence analysis of the FLNFN model are proven. Finally, the FLNFN model is applied in various simulations. Results of this study demonstrate the effectiveness of the proposed FLNFN model.

关键词： Entropy functional link neural networks (FLNNs) neurofuzzy networks (NFNs) nonlinear system control online learning

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Guaranteed Cost control Design Based on Takagi-Sugeno Fuzzy systems with nonlinear Subsystems

Guaranteed Cost Control Design Based on Takagi-Sugeno Fuzzy ...

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IEEE International Conference on systems, Man, and Cybernetics (SMC)

作者： Ochiai, Shunsuke Uchida, Yuzu Yoneyama, Jun Aoyama Gakuin Univ Dept Elect & Elect Engn Sagamihara Kanagawa 2525258 Japan

ISBN: (纸本)9781479906529

This paper is concerned with guaranteed cost control design for a generalized Takagi-Sugeno fuzzy system. The Takagi-Sugeno fuzzy system generally describes nonlinear systems by employing local linear system representations, while a generalized fuzzy system to be considered in this paper describes even a wider class of nonlinear systems by representing locally nonlinear systems. For such a generalized system, a design method of a stabilizing controller with guaranteed cost is proposed by introducing a new class of non-PDC controllers. Non-PDC controller is a generalized controller of PDC one, which is a traditional fuzzy controller. Stabilizing controller design conditions are given in terms of a set of linear matrix inequalities(LMIs), which are easily numerically solvable. A relaxation method is used to reduce the conservatism of design conditions. Finally, numerical examples are given to illustrate our nonlinear control design and to show the effectiveness over other existing results.

关键词： Takagi-Sugeno fuzzy systems nonlinear system control guaranteed cost control linear matrix inequality

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Guaranteed Cost control Design Based on Takagi-Sugeno Fuzzy systems with nonlinear Subsystems

Guaranteed Cost Control Design Based on Takagi-Sugeno Fuzzy ...

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IEEE International Conference on systems, Man, and Cybernetics

作者： Shunsuke Ochiai Jun Yoneyama Yuzu Uchida Department of Electronics and Electrical Engineering Aoyama Gakuin University 5-10-1 Fuchinobe Sagamihara Kanagawa 252-5258 Japan

ISBN: (纸本)9781479906505

关键词： Takagi-Sugeno fuzzy systems nonlinear system control guaranteed cost control linear matrix inequality Fuzzy systems COST control linear matrix inequalities nonlinear systems nonlinear system control controllers relaxation method (mathematics) Generalized fuzzy system T-S fuzzy model design control design condition Conservatism SUB-system New classes

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