Adaptive Robust Control and Optimal Design for Fuzzy Unmanned Helicopter Tail Reduction
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Adaptive Robust Control and Optimal Design for Fuzzy Unmanned Helicopter Tail Reduction Han Zhao1,2 • Zicheng Zhu1,2 • Hao Sun1,2
Received: 27 December 2019 / Revised: 27 February 2020 / Accepted: 19 April 2020 Ó Taiwan Fuzzy Systems Association 2020
Abstract This paper develops an adaptive robust control scheme combined with optimal design for the unmanned helicopter tail reduction (UHTR) system. The dynamical model of the UHTR system with uncertainties is established. The uncertainties are assumed to be bounded and expressed by fuzzy set theory. With this prerequisite, an adaptive robust controller is proposed to drive the system to meet the trajectory requirements approximately. The adaptive law with leakage and dead zone is performance based and flexibly adjustable. By means of Lyapunov stability theorem, the UHTR system is both uniform bounded and uniform ultimate bounded with the proposed controller. The control scheme is deterministic rather than fuzzy if-then rules-based control. Moreover, the fuzzy performance index which contains the steady-state system performance and control cost is presented. In this way, the optimal design problem can be replaced by minimizing the performance index. Overall, the resulting control scheme can guarantee deterministic performance of the UHTR system and minimize the fuzzy performance index simultaneously.
& Hao Sun [email protected] Han Zhao [email protected] Zicheng Zhu [email protected] 1
School of Mechanical Engineering, Hefei University of Technology, 230009 Hefei, People’s Republic of China
2
AnHui Key Laboratory of Digital Design and Manufacturing, Hefei University of Technology, 230009 Hefei, People’s Republic of China
Keywords Fuzzy set theory Unmanned helicopter tail reduction system Adaptive robust control Fuzzy performance index Optimal design
1 Introduction Flight control and electric powertrain system has improved significantly in the past decades and intelligent algorithm and reliable electricity supply have offered great opportunities for the development of unmanned helicopters [1]. As an important component in the helicopter’s transmission system, the unmanned helicopter tail reduction (UHTR) system which aims to reduce weight, decouple with main rotor and further improve the dynamic performance and the reliability of unmanned helicopters have attracted the attention of numerous researchers both from the field of automatic and flight control. Whether in the military or civil application, the UHTR system is required to track the prescribed trajectory quickly and precisely. However, due to the complicated aerodynamics, nonlinear factors, dynamic couplings, and modeling uncertainties, it is still a challenging focus for the control design. In [2, 3], the fuzzy-PID control approach was adopted for improving the robustness of unmanned helicopters. To deal with the system uncertainties and external disturbances, some advanced control methodologies such as finite-time control [4], inverse optimal control [5, 6], fuzzy sliding mode contro
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