Motion Tracking Control for State- and Input-Constrained Servo Mechanisms Without Feasibility Conditions

The tracking control of servo mechanisms under physical constraints has consistently attracted research attention. This study focuses on developing an adaptive tracking control methodology for servo mechanisms subject to simultaneous state and input constraints, which remains challenging due to the coupling between state limitations and actuator saturation. First, the control input is expanded as an additional state variable, facilitating the resolution of state and input constraints by addressing a full-state-constrained problem. Second, through the construction of appropriate dynamic surfaces and auxiliary functions, the conventional requirement for the boundedness of the virtual controller in integral Barrier Lyapunov Function (iBLF)-based approaches is eliminated. This enables direct enforcement of full-state constraints without requiring restrictive feasibility. Subsequently, the boundedness and stability of the controlled servo mechanisms are proven through Lyapunov analysis. Finally, comparative simulation results demonstrate that the proposed method effectively guarantees simultaneous state and input constraints while maintaining satisfactory tracking performance.