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This paper presents a grey predictive control method for a class of nonlinear systems with unknown input delay. By using BP neural network, the unknown input delay is identified firstly. The system output is then estimated by the grey predictive algorithm. The output feedback control is fulfilled by PID algorithm which is used to tune its three parameters. By means of combining grey predictive algorithm...
This paper investigates the stabilization of nonlinear networked control systems (NCSs) subject to two types of uncertainties. Firstly, the nonlinear NCS is modeled as a continuous-time Takagi-Sugeno (T-S) fuzzy system, and network-induced delays are represented using fuzzy rules which are designed by the parallel distributed compensation (PDC) technique. Then the norm-bounded uncertainty existing...
This paper presents a kind of multiple model adaptive controller based on fuzzy supervisor for the control system of robots with uncertain parameters. The controller uses the structure of model reference control system and adopts a fuzzy supervisor who controls the switching of respective control models instead of tuning dynamically the parameters of controller to tune control input. So a lot of calculations...
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