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This paper deals with adaptive tracking for discrete-time multiple-input-multiple-output (MIMO) nonlinear systems in presence of bounded disturbances. In this paper, a high-order neural network (HONN) structure is used to approximate a control law designed by the backstepping technique, applied to a block strict feedback form (BSFF). This paper also(More)
—In this note, we propose a solution to the well-know problem of ensuring a simultaneous globally convergent online estimation of the state and the frequencies of a sinusoid signal composed of sinusoidal terms. We present an estimator which guarantees global boundedness and convergence of the state and frequencies estimation for all initial conditions and(More)
In this paper, the authors propose a particle swarm optimization (PSO) for a discrete-time inverse optimal control scheme of a doubly fed induction generator (DFIG). For the inverse optimal scheme, a control Lyapunov function (CLF) is proposed to obtain an inverse optimal control law in order to achieve trajectory tracking. A posteriori, it is established(More)
This paper presents an inverse optimal control approach for exponential stabilization of discrete-time nonlinear systems, avoiding to solve the associated Hamilton-Jacobi-Bellman (HJB) equation, and minimizing a meaningful cost function. This stabilizing optimal controller is based on a discrete-time control Lyapunov function. The applicability of the(More)
An Integral Nested Sliding Mode Control (INSMC) is proposed for n-link robotic manipulators tracking problem by employing Integral Sliding Mode (ISM) and Nested Sliding Mode (NSM) concepts. This controller has the robustness of NSM against matched and no matched perturbations, and the capability of ISM to reduce the sliding functions gains. Application to a(More)
— This paper presents a speed-gradient-based inverse optimal control approach for the asymptotic stabilization of discrete-time nonlinear systems. With the solution presented, we avoid to solve the associated Hamilton-Jacobi-Bellman equation , and a meaningful cost function is minimized. The proposed stabilizing optimal controller uses the speed-gradient(More)