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ROBUST STRICTLY POSITIVE REAL SYNTHESIS BASED ON GENETIC ALGORITHM
Liangjun Xie1 Long Wang2 Wensheng Yu1 Yuhuang Qiu1
1 Laboratory for Complex Systems, Institute of Automation, Chinese Academy of
Sciences, Beijing 100080, P. R. China
2 Center for Systems and Control, Department of Mechanics and Engineering
Science, Peking University, Beijing 10087, P. R. China
In this paper, a new numerical method based on Genetic Algorithm (GA) for robust Strictly Positive Real (SPR) synthesis is presented. The algorithm works well in coefficient space of continuous-time systems and is computationally efficient for some types of polynomial families, such as polynomial segments, interval polynomials and polytopic polynomials et al.. The method can be easily extended to the discrete-time systems. Illustrative examples are provided showing that the method is rather effective for arbitrary given high-order systems.
Keywords: Robustness, Strict Positive Realness (SPR), Genetic Algorithm (GA), Robust Analysis and Synthesis
Session slot T-Th-A21: Posters of Robotics and Robust Control/Area code 2e : Robust Control
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