Robust Stabilization of Uncertain Switched Nonlinear Systems With Hybrid Saturated Inputs
针对同时受采样数据控制和脉冲信号饱和约束的不确定切换非线性系统，提出鲁棒镇定方法，通过Lyapunov理论和线性矩阵不等式优化求解控制增益，并用神经网络子系统仿真验证了有效性。
In this article, we propose a novel class of mathematical models of uncertain switched nonlinear systems with saturation constraints on both the sampled-data control signal and the impulsive signal, which can reflect the actuator saturation phenomenon of hybrid control signals more realistically. Based on the Lyapunov stability theory, polytopic representation approach, matrix inequality, and Schur complement, we analyze the robust stability of the considered system, overcoming the relevant difficulties from the parameter uncertainty, the discontinuity produced by impulsive effect and the input constraints on both the sampled-data control signal and the impulsive signal. Moreover, to make it easier to find the suitable control gains, the design of the hybrid control gains is investigated. And, some optimization problems are also established to obtain the larger estimation of the attraction domain. Simulation results for the system consisting of two neural network subsystems are presented to show the feasibility and effectiveness of our robust stabilization methods and the LMI optimization problems.