Adaptive control based on neural networks for an uncertain 2-DOF helicopter system with input deadzone and output constraints

• Published in: IEEE/CAA journal of automatica sinica Vol. 6; no. 3; pp. 807 - 815
• Main Authors: Ouyang, Yuncheng, Dong, Lu, Xue, Lei, Sun, Changyin
• Format: Journal Article
• Language: English
• Published: Piscataway Chinese Association of Automation (CAA) 01.05.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Computer simulation; Control design; Control stability; Degrees of freedom; Helicopters; Liapunov direct method; Liapunov functions; Mathematical analysis; Mathematical models; Neural networks; Stability analysis; Systems stability; Tracking errors; Uncertainty
• ISSN: 2329-9266; 2329-9274
• DOI: 10.1109/JAS.2019.1911495

In this paper, a study of control for an uncertain 2-degree of freedom &#x0028 DOF &#x0029 helicopter system is given. The 2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function &#x0028 IBLF &#x0029 is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser &#x02BC s 2-DOF helicopter.