Adaptive backstepping quantized control for a class of unknown nonlinear systems. (June 2022) - Aslmostafa, Ehsan; Ghaemi, Sehraneh; Badamchizadeh, Mohammad Ali; Ghiasi, Amir Rikhtehgar
Abstract: In this paper, the stability problem for a class of nonlinear systems in the form of strict-feedback with applying input quantization has been addressed. By considering a sector-bounded hysteresis quantizer, signal quantization has been achieved. The employed quantizer can reduce the potential chattering which can occur in some approaches. By using a common Lyapunov function (CLF) and the backstepping method, a control scheme has been introduced to stabilize the uncertain nonlinear system. Compared with the recent papers, in order to handle the quantization error, one of the sector-bounding features has been utilized straightly instead of decomposing the quantized input into linear and nonlinear parts, in this case, the possible disturbance-like term has been ignored. The designed control scheme does not need the global Lipschitz assumption over the system mismatched nonlinearities. Besides, the asymptotic stability of system trajectories to the origin is guaranteed and the imposed restrictions over quantization design parameters such as quantization density have been eliminated. Finally, in the simulation results, the accuracy and efficiency of the this control scheme are shown. Highlights: Stability of a strict-feedback form with hysteresis quantization is considered. A more general form of the strict-feedback system has been investigated. Restrictions on choosing parameters in the design procedure have been relaxed. Global asymptotic stability in the presence of quantized input has been guaranteed. The superiority and efficiency of the proposed method have been illustrated.