HGO-based decentralised indirect adaptive fuzzy control for a class of large-scale nonlinear systems

International audienceThis paper addresses the problem of linear adaptive controller for a class of un- certain continuous-time single-input single-output (SISO) nonaffine nonlinear dy- namic systems. Firstly, using the implicit function theory, the existence of an ideal controller which can achieve control objectives will be demonstrated. Nevertheless, this ideal controller can not be known and computed even if the system model is well known. The aim of our work is to construct this unknown ideal controller us- ing a simple linear controller with the gains updated online by a stable adaptation mechanism designed to minimize the error between the unknown ideal controller and the used linear controller. Since the mathematical model of the system is assumed unknown in this work, the proposed control scheme can be regarded as a simple model free controller for the studied nonaffine class of systems. We prove that the closed-loop system controlled is stable and all the signals are bounded. An application of the proposed linear adaptive controller for a nonaffine system is illustrated through the simulation results to demonstrate the effectiveness of the proposed control scheme

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Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers

Kharola

Patil

2017

International Journal of Fuzzy System Applications

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Elastic Inverted Pendulum system (EIP) are very popular objects of theoretical investigation and experimentation in field of control engineering. The system becomes highly nonlinear and complex due to transverse displacement of elastic pole or pendulum. This paper presents a comparison study for control of EIP using fuzzy and hybrid adaptive neuro fuzzy inference system (ANFIS) controllers. Initially a fuzzy controller was designed, which was used for training and tuning of ANFIS controller using gbell shape membership functions (MFs). The performance of complete system was evaluated through output responses of settling time, steady state error and maximum overshoot. The study also highlights effect of varying number of MFs on training error of ANFIS. The results showed better performance of ANFIS controller compared to fuzzy controller.

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HGO-based decentralised indirect adaptive fuzzy control for a class of large-scale nonlinear systems

Cited by 3 publications

References 30 publications

Intelligence computation based on adaptive tracking design for a class of non-linear discrete-time systems

Intelligence computation based on adaptive tracking design for a class of non-linear discrete-time systems

Linear adaptive control of a class of SISO nonaffine nonlinear systems

Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers

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