Observer-based adaptive robust stabilization of dynamic positioning ship with delay via Hamiltonian method. (15th February 2021)

• Record Type: Journal Article
• Authors: Cui, Jiankuo; Yang, Renming; Pang, Chengcheng; Zhang, Qiang
• Is Part Of: Ocean engineering. Volume 222(2021)
• Publication Date: 2021-02-15
• Subjects: Time-delay dynamic positioning ship -- Hamiltonian model -- Observer design -- Adaptive robust control; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2020.108439
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: In this paper, by applying the Hamiltonian function method, we study the observer-based adaptive robust stabilization problem for dynamic positioning (DP) ship with time delay, and present several new results on the issue. Firstly, the three degree of freedoms DP ship model with time delay is transformed into a Port-Controlled Hamiltonian (PCH) one, based on which we design its observer system. Then, by using the augmented technology and the Lyapunov stability theory, several observer-based robust stabilization controllers and observer-based adaptive robust stabilization controllers are designed for the DP ship with time delay, and some delay-independent and delay-dependent robust stabilization results are obtained. Finally, the simulation results show the effectiveness of the observer-based robust stabilization controller proposed in this paper. Highlights: The present paper develops adaptive robust control results based on the observer by applying Hamiltonian method. Although the few literature have considered the observer design problem for the ship system, the systems under study in the existing papers do not contain time-delay term. Therefore, the studied system in the present paper is more general. Different from traditional observer design method, the present paper applies expansion technology rather than the error method. That is to say, the method of the present paper can be applied to study general nonlinear system not only linear model and/or approximate linear model.