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The problem of multi-objective model predictive controller design is solved in this paper. The linear parameter-varying parameter system is considered. The proposed method is based on the solving multi-objective optimization problem using linear matrix inequality approach at each sampling time. The trade-off point among the optimization results is obtained by Nash bargaining solution at each sampling...
A novel robust adaptive control based on neural state observer is proposed for strict-feedback nonlinear systems with state delays. A state observer with neural networks approximators is established to estimate the system states. By using the backstepping method, adaptive output feedback controller is constructed which can achieve the output trajectory. Both the designed observer and controller are...
Two memoryless adaptive observers are proposed for systems with unknown time-delays and nonlinearities, in which time-delays are not used in the observer. Using high order neural networks (HONN), the precise system model, the Lipschitz, linear-in-parameter or norm-bounded assumptions of nonlinear functions are not needed. A robust term based on the matching condition is introduced in the first observer,...
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