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This paper studies the design and the analysis of a nonlinear and neural adaptive control strategy for a complex nonlinear and time varying wastewater treatment bioprocess. In fact a direct adaptive controller based on a radial basis function neural network used as an on-line approximator to learn the time-varying characteristics of process parameters is developed and then is compared with a classical...
In this paper, a novel adaptive NN control scheme is proposed for a class of uncertain single-input and single- output(SISO) nonlinear time-delay systems with the lower triangular form. RBF NNs are used to approximate unknown nonlinear functions, then the adaptive NN tracking controller is constructed by combining Lyapunov-Krasovskii functionals and the dynamic surface control(DSC) technique along...
In this paper, we integrate impulsive control and adaptive control methods, based on the stability theory of impulsive differential equations, generalized projective synchronization between the general complex dynamical networks with time delay is investigated. A nonlinear controller, updating laws and a linear impulsive controller are proposed. An adaptive-impulsive generalized projective synchronization...
A neural network based robust adaptive control design scheme is developed for a class of nonlinear systems represented by input-output models with an unknown nonlinear function and unknown time delay. By on-line approximating the unknown nonlinear functions with a three layer feedforward neural networks, the proposed approach does not require the unknown parameters to satisfy the linear dependence...
In this paper, both indirect and direct adaptive fuzzy controllers with variable structure system (VSS) and Hinfin performance are proposed for a class of nonlinear time-delay systems with unknown dynamics nonlinearities and external disturbances. It is assumed that the unknown nonlinear function of state-delays is bounded by a high-order function with unknown gains. An adaptive fuzzy controller design...
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