A Novel Adaptive Controller for Nonlinear Stochastic Systems With Uncertain Virtual Control Gains and Input Nonlinearities

In this article, an adaptive nonlinear controller is developed for a class of stochastic systems, whose inputs are uncertainly nonlinear and virtual control gains (simplified as VCGs) include unknown and known items. A novel auxiliary function of boundedness and smoothness is constructed for handling the unknown items of VCGs. Aiming at the challenges of control laws without enough differentiability and uncertainties caused by deadzone and saturation of inputs, the novel control signals are proposed, which are tested on a nonsmooth system, SISO robot and MIMO quadrotor. The superiority and effectiveness of the designed control strategy are proved via the strict stability analysis and simulation comparisons.