Alexander G. Loukianov

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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)
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)
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)
A Sliding Mode (SM) Block Control is proposed to control an Antilock Brake System (ABS). The control problem is to achieve reference tracking for the slip rate, such that, the friction between tyre and road surface is good enough to control the car. The closed-loop system is robust in presence of matched and unmatched perturbations. To show the performance(More)
This paper deals with the problem of discrete-time nonlinear system identification via Recurrent High Order Neural Networks. It includes the respective stability analysis on the basis of the Lyapunov approach for the extended Kalman filter (EKF)-based NN training algorithm, which is applied for learning. Applicability of the scheme is illustrated via(More)