期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 26, 期 11, 页码 2775-2786出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2015.2396044
关键词
Adaptive robust control; dynamic positioning (DP); high-gain observer; neural networks; output feedback
类别
资金
- Macau Science and Technology Development [008/2010/A1]
- National Natural Science Foundation of China [51079013, 61173035, 61472058]
- Applied Basic Research Program through Ministry of Transport, China [2012-329-225-070]
- Fundamental Research Funds for Central Universities [3132014332]
- Program for New Century Excellent Talents in University [NCET-11-0861]
- University of Macau Multiyear Research Grants
This paper develops an adaptive robust output feedback control scheme for dynamically positioned ships with unavailable velocities and unknown dynamic parameters in an unknown time-variant disturbance environment. The controller is designed by incorporating the high-gain observer and radial basis function (RBF) neural networks in vectorial backstepping method. The high-gain observer provides the estimations of the ship position and heading as well as velocities. The RBF neural networks are employed to compensate for the uncertainties of ship dynamics. The adaptive laws incorporating a leakage term are designed to estimate the weights of RBF neural networks and the bounds of unknown time-variant environmental disturbances. In contrast to the existing results of dynamic positioning (DP) controllers, the proposed control scheme relies only on the ship position and heading measurements and does not require a priori knowledge of the ship dynamics and external disturbances. By means of Lyapunov functions, it is theoretically proved that our output feedback controller can control a ship's position and heading to the arbitrarily small neighborhood of the desired target values while guaranteeing that all signals in the closed-loop DP control system are uniformly ultimately bounded. Finally, simulations involving two ships are carried out, and simulation results demonstrate the effectiveness of the proposed control scheme.
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