Multi-variable adaptive high-order sliding mode quasi-optimal control with adjustable convergence rate for unmanned helicopters subject to parametric and external uncertainties

This paper presents a novel multi-variable high-order sliding mode quasi-optimal control method for unmanned helicopters. In order to facilitate the theoretical design and engineering implementation, the control system is divided into attitude and position subsystem, and the latter is further subdiv...

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Bibliographic Details
Published inNonlinear dynamics Vol. 108; no. 4; pp. 3671 - 3692
Main Author Zhou, Bin
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.06.2022
Springer Nature B.V
Subjects
Adaptive control
Attitudes
Automotive Engineering
Classical Mechanics
Closed loop systems
Continuity (mathematics)
Control
Control methods
Control theory
Controllers
Convergence
Design
Dynamical Systems
Engineering
Equilibrium
Experiments
Helicopter control
Helicopters
Mechanical Engineering
Neural networks
Optimal control
Original Paper
Performance indices
Robustness
Simulation
Sliding mode control
Subsystems
Unmanned helicopters
Vertical orientation
Vibration
Quasi-optimal
Nonlinear adaptive control
Multi-variable control, Sliding mode control
Small-scale unmanned helicopter
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Summary:This paper presents a novel multi-variable high-order sliding mode quasi-optimal control method for unmanned helicopters. In order to facilitate the theoretical design and engineering implementation, the control system is divided into attitude and position subsystem, and the latter is further subdivided into two parts, horizontal and vertical position control. Then the multi-variable adaptive high-order continuous sliding mode controllers are designed for attitude and position, respectively, based on integral sliding mode surface. A new quadratic performance index is proposed in the design process, which enables the control system to converge in finite time, and the convergence rate can be adjusted by control parameters. Finally, the effectiveness and robustness of the proposed method are verified and compared with existing literature by simulation and practical experiments. The comparison results show that the proposed method has higher tracking accuracy and better robustness.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-022-07433-3