Dynamic balance control based on an adaptive gain-scheduled backstepping scheme for power-line inspection robots

This paper presents an adaptive gain-scheduled backstepping control &#x0028 AGSBC &#x0029 scheme for the balance control of an underactuated mechanical power-line inspection &#x0028 PLI &#x0029 robotic system with two degrees of freedom and a single control input. First, a nonlinear dynamic model of the balance adjustment process of the PLI robot is constructed, and then the model is linearized at a nominal equilibrium point to overcome the computational infeasibility of the conventional backstepping technique. Second, to solve generalized stabilization control issue for underactuated systems with multiple equilibrium points, an equilibrium manifold linearized model is developed using a scheduling variable, and then a gain-scheduled backstepping control &#x0028 GSBC &#x0029 scheme for expanding the operational area of the controlled system is constructed. Finally, an adaptive mechanism is proposed to counteract the impact of external disturbances. The robust stability of the closed-loop system is ensured by Lyapunov theorem. Simulation results demonstrate the effectiveness and high performance of the proposed scheme compared with other control schemes.