以分散式智慧型感測器為基礎的可變結構分散控制於自走車

在本篇論文發展出一套自走車應用混合與的分散式可變結構控制的軌跡追蹤與避障。應用於動態障礙的閃避與目標，兩部分開架設的CCD將自走車的位置與動態障礙的位置標示出來，並且計算最適合路徑由權重較高的CCD所抓取的資訊經由無線模組傳輸至自走車並且對自走車下達參考的控制訊號。在自走車控制器方面，部分是將系統輸出訊號與參考輸出訊號的誤差和控制訊號，一起加以極小化達成用最少的能量達到符合要求的系統性能。然而，輸出的干擾是因為自走車次系統之間的相互作用、建模誤差與外部負載。為能有效抵抗，所以又加入的觀念，將系統輸出對雜訊的敏感性乘上一個權重加以極小化，有效降低雜訊對系統的影響。為了改善系統的表現，再加入切換模式控制，提高強健性，穩定性分析是根據李雅普諾夫穩定性的法則。根據後面的實驗，能證明控制器的有效能力。

關鍵字

感測器為基礎之控制；分散式控制；可變結構控制；自走車；混合H2/ H∞最佳化

並列摘要

In this thesis, the trajectory tracking and obstacle avoidance of a car-like mobile robot (CLMR) within sensor networks via mixed decentralized variable structure control (DVSC) was developed. For implementing (dynamic) obstacle avoidance and target tracking, two distributed CCD (charge-coupled device) cameras were set up to realize the dynamic position of the CLMR and the obstacle. Based on the authority of these two CCD cameras, a suitable reference input for the proposed controller of the CLMR was planned by the CCD camera with higher authority and transmitted to CLMR by a wireless module. As for the controller design of the CLMR, the norm of the output error (i.e., the difference between the output of the reference model and system output) and weighted control input was first minimized to obtain a control such that smaller energy consumption with bounded tracking error was assured. However, an output disturbance caused by the interactions among subsystems of CLMR, modeling error, and external load deteriorated system performance. In this situation, the norm of weighted sensitivity between output disturbance and system output was minimized to attenuate the effect of output disturbance. For further improving system performance, a switching control for every subsystem of CLMR was designed. The stability of the overall system was verified by Lyapunov stability criterion. The experiments were also carried out to evaluate the usefulness of the proposed control system.

並列關鍵字

Decentralized control ； Distributed control ； Mixed H2/ H∞ optimization ； Mobile robot ； Sensor based control ； Variable structure control.

參考文獻

[1] B. Sinopoli, C. Sharp, L. Schenato, S. Schaffert and S. S. Satry, “Distributed control applications within sensor networks,” Proceedings of the IEEE, vol. 91, no. 8, pp. 1235-1246, 2003.

[2] T. Yamaguchi, E. Sato and Y. Takama, “Intelligent space and human centered robotics,” IEEE Trans. Ind. Electron., vol. 50, no. 5, pp. 881-889, 2003.

[3] J. H. Lee, and H. Hashimoto, “Controlling mobile robots in distributed intelligent sensor network,” IEEE Trans. Ind. Electron., vol. 50, no. 5, pp. 890-902, 2003.

[4] S. X. Yang, Y. Hu, P. X. Liu, X. Yuan and M. Q.-H. Meng, “A neural dynamics Based approach to real-time path planning and tracking control of a mobile robot,” IEEE proceedings Industrial Symposium on intelligent control, pp. 258-263 2003

[5] K. Briechle and U. D. Hanebeck, “Location of a mobile robot using relative bearing measurements,” IEEE Trans. Robot. & Automat., vol. 20, no. 1, pp. 36-44, 2004.

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以分散式智慧型感測器為基礎的可變結構分散控制於自走車

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