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In this paper, a nonlinear control system using a fuzzy self tuning Grey predictor based on a PID controller is proposed. Firstly, the PID controller is designed according to the Zieger-Nichos 2 method with fast response and high robustness. Secondly, the grey predictor is suggested to use to estimate the system response in a near future in order to improve the control performance. In addition, the...
This paper addresses the problem of adaptive fuzzy integral sliding mode control (AFISMC) for uncertain nonlinear systems with state and input delays. First, we employ a state-transformation to map the nonlinear system into an input-delay free system. Then, an adaptive fuzzy technique is applied to estimate the bound of the lumped perturbation. Finally, based on Lyapunov stability theorem, a controller...
Sliding mode-like fuzzy logic control (SMFC) algorithm for nonlinear systems is presented in this paper. Firstly dead zone parameters of sliding mode control (SMC) are self-tuned by proper adaptive laws and then combined into fuzzy logic system (FLS) to compose the opportune fuzzy logic control (FLC), which is equivalent to the pre-designed SMC controller with self-tuning parameters. Robustness and...
Addressing to the difficulties in PID parameter tuning, low accuracy in temperature controlling and the dissatisfaction in high exactitude extrusion processing of the present PID controllers, a new kind of PID controller based on RBF neural network is proposed. It can not only obtain a higher accuracy in temperature controlling, but also infinitely approach the nonlinear system with quicker and more...
A four link biomechanical model of human stable movement is studied through fuzzy modeling and optimal control. Physiologists describe human sit-to-stand movement in different phases; a local linear model is developed for each phase and integrating all local models with Gaussian membership functions. These local linear models of sit-to-stand movement are generated from the general nonlinear model...
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