Robust Fuzzy Sampled-Data Control for Dynamic Positioning Ships

doi:10.1007/s12204-018-1931-z

Abstract

Abstract: A robust H∞ sampled-data stabilization problem for nonlinear dynamic positioning (DP) ships with Takagi-Sugeno (T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system’s asymptotical stability and achieve H∞ performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.

Key words: dynamic positioning (DP) ships| sampled-data control| Lyapunov-Krasovskii functional| Takagi- Sugeno (T-S) fuzzy models

摘要： A robust H∞ sampled-data stabilization problem for nonlinear dynamic positioning (DP) ships with Takagi-Sugeno (T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system’s asymptotical stability and achieve H∞ performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.

关键词: dynamic positioning (DP) ships| sampled-data control| Lyapunov-Krasovskii functional| Takagi- Sugeno (T-S) fuzzy models

CLC Number:

TP 13

ZHENG Minjie (郑敏杰), ZHOU Yujie (周玉洁), YANG Shenhua (杨神化). Robust Fuzzy Sampled-Data Control for Dynamic Positioning Ships[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(2): 209-217.

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