Adaptive Tracking Control for Uncertain Unmanned Fire Fighting Robot With Input Saturation and Full-State Constraints

This paper considers the tracking control problem for unmanned fire fighting robots subject to both full-state constraints and input saturation. First, a system model is developed that incorporates system internal uncertainties, external disturbances, input saturation, and actuator faults. Then, to address the full-state constraint problem, the original constrained system is transformed into an equivalent unconstrained one by using a new state-dependent transformation function. In addition, to solve asymmetric time-varying constraints on the control input, another new transformation function is also designed. In the end, based on the transformed system, a novel adaptive control scheme is proposed utilizing the backstepping recursive method and first-order filters. It is demonstrated that all signals in the closed-loop system are semi-globally ultimately bounded, and the output variables accurately track the reference signals while satisfying both full-state constraints and input saturation. To validate the effectiveness of our designed control scheme, numerical simulations have been conducted. To ensure repeatability, our codes are open sourced on github: https://github.com/JiannanChen/ATControlUFFR-FullStateConstraintInputSaturation.git.