Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorith
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Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorithm YUAN Dongdong (),
WANG Yankai ∗ ()
(School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China)
© Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 Abstract: In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor, a data driven model-free adaptive control method based on the improved sliding mode control (ISMC) algorithm is designed, which does not depend on the precise dynamic model of the quadrotor. The design of the general sliding mode control (SMC) algorithm depends on the mathematical model of the quadrotor and has chattering problems. In this paper, according to the dynamic characteristics of the quadrotor, an adaptive update law is introduced and a saturation function is used to improve the SMC. The proposed control strategy has an inner and an outer loop control structures. The outer loop position control provides the required reference attitude angle for the inner loop. The inner loop attitude control ensures rapid convergence of the attitude angle. The effectiveness and feasibility of the algorithm are verified by mathematical simulation. The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective, and it can effectively realize the trajectory tracking control of the quadrotor. The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle (UAV), and has high control accuracy, stability, and robustness. Key words: quadrotor, trajectory tracking, improved sliding mode control (ISMC), data driven model-free adaptive control CLC number: V 279 Document code: A
0 Introduction With the development of artificial intelligence and avionics technology, the unmanned aerial vehicles (UAVs) are becoming an important part of intelligent transportation systems. The quadrotor has the advantages of small size and convenient control in target search, environmental monitoring, and forest fire prevention, which has been extensively researched and applied[1-2] . Compared with the fixed-wing aircraft, the quadrotor not only has the advantage of vertical takeoff and landing, but also can perform large-angle maneuvers in any direction, and has low requirements for landing sites, so it occupies a very important position in the UAV system. Trajectory tracking control is one of the basic control issues for the aircraft to achieve unmanned flight. It requires the aircraft to reach a given or planned trajectory point at a specified time. Since the quadrotor is a complex system with strong coupling, strong nonlinearity, multi-input and multi-output (MIMO), multiple operating conditions, variable load, Received: 2020-05-11 Accepted: 2020-07-30 ∗E-mail: [email protected]
and time-varying[3] , it is difficult to obtain or cannot establish an accurat
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