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A novel state dependent control approach for continuous-time nonlinear systems with general performance criteria is presented in this paper. This controller is optimally robust for model uncertainties and resilient against control feedback gain perturbations in achieving general performance criteria to secure quadratic optimality with inherent asymptotic stability property together with quadratic...
Approximate dynamic programming formulation implemented with an Adaptive Critic (AC) based neural network (NN) structure has evolved as a powerful alternative technique that eliminates the need for excessive computations and storage requirements needed for solving the Hamilton-Jacobi-Bellman (HJB) equations. A typical AC structure consists of two interacting NNs. In this paper, a novel architecture,...
Underwater vehicles present a difficult control-system design due to their nonlinear dynamics, uncertain models, and the presence of disturbances that are difficult to measure or estimate. A multivariable design based on backstepping jointly with a simple optimization algorithm, that minimizes the energy consumption, is able to carry out the control of this system taking into account the uncertainties...
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