| Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm |
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| 作者单位： | Department of Optical and Electronic Engineering Ordnance Engineering College，Department of Optical and Electronic Engineering，Ordnance Engineering College，Army 65185，Shijiazhuang 050003，China，Shijiazhuang 050003，China，Shenyang 110000，China |
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| 摘 要： | The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.
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Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm |
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| LI Jimin,SHANG Chaoxuan,ZOU Minghu. Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm[J]. Tsinghua Science and Technology, 2007, 12(Z1): 208-211 |
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| Authors: | LI Jimin SHANG Chaoxuan ZOU Minghu |
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| Abstract: | The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach. |
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| Keywords: | genetic algorithm weighting matrix linear quadratic controller parameter optimization |
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