Compact robust FAT control of rigid robots with state constraints

This paper develops a robust regressor-free controller for n-link robots with state constraints. We use the function approximation technique to represent the uncertain robot dynamics. Our controller, which uses a state-dependent barrier Lyapunov function, prevents the states from violating their constraints by guaranteeing uniform ultimate boundedness of the closed-loop dynamics via a fixed control structure and a continuous switching law. In contrast to the drawbacks of controllers developed via the widely used error-dependent barrier Lyapunov functions, our controller overcomes the need to impose constraints on the initial tracking errors and the reference trajectories. When the reference trajectories violate the state constraints, our controller is capable of maintaining states within their constraints. We show that it is easy to switch between the constrained and unconstrained versions of our controller. Our controller requires few tuning parameters and is robust to wide ranges of uncertainties. Simulation and real-time experimental tests validate the practicality of our proposed controller.