Arbitrary Convergence Time Control for Aerial Manipulator with TSK Estimator

This paper investigates the stable control problem of unmanned aerial manipulator (UAM) in the presence of lumped disturbance, including modelling uncertainties and external inferences. These disturbances typically involve limited prior knowledge and change rapidly, presenting considerable challenges to real-time control accuracy. To address this issue, a Takagi-Sugeno-Kang estimator (TSKE) with K-closest fuzzy rules interpolation (K-FRI) is proposed to derive an approximation for the uncertain disturbances. The incorporation of K-FRI enhances the accuracy and convergence rate of the estimation under the conditions of a sparse fuzzy rule base with an incomplete fuzzy quantity space. Subsequently, a backstepping controller with arbitrary convergence time is introduced to guarantee the rapid and precise control of the UAM. The stability of both the TSKE and the controller with arbitrary convergence time is analysed through Lyapunov theory. The feasibility and performance of the proposed control strategy are validated via comparative experimental simulations, demonstrating its ability for robust estimation capability with stable control performance, at any convergence time of the UAM working under lumped disturbance.