Adaptive Tracking Control for Uncertain Unmanned Fire Fighting Robot With Input Saturation and Full-State Constraints
Jiannan Chen, Dianrui Mu, Changchun Hua, Xi Luo, Yu Zhang, Fuchun Sun
Abstract
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.