Abstract
In this paper, the problem of robust adaptive control is discussed for a class of multi-input multi-output (MIMO) nonlinear systems with unmodeled dynamics and output constraint. Based on modified dynamic surface control (DSC) and the approximation capability of neural networks, the adaptive vector virtual control and control law are designed in recursive each step. A dynamic signal is used to handle unmodeled dynamics in the system. By introducing the barrier Lyapunov function (BLF), the output constraint is not violated in the designed adaptive control system. The stability analysis shows that all the signals in the closed-loop control system are semi-globally uniformly ultimately bounded (SGUUB). Simulation results with the 2-DOF robotic system is provided to demonstrate the effectiveness of the proposed control scheme.
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