Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm
A method is designed to optimize the weight matrix of the LQR controller by using the simulated annealing algorithm. This method utilizes the random searching characteristics of the algorithm to optimize the weight matrices with the target function of suspension performance indexes. This method impr...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/420719 |
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| _version_ | 1832562060800557056 |
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| author | Jie Meng Qingzhang Chen Ren He |
| author_facet | Jie Meng Qingzhang Chen Ren He |
| author_sort | Jie Meng |
| collection | DOAJ |
| description | A method is designed to optimize the weight matrix of the LQR controller by using the simulated annealing algorithm. This method utilizes the random searching characteristics of the algorithm to optimize the weight matrices with the target function of suspension performance indexes. This method improves the design efficiency and control performance of the LQR control, and solves the problem of the LQR controller when defining the weight matrices. And a simulation is provided for vehicle active chassis control. The result shows that the active suspension using LQR optimized by the genetic algorithm compared to the chassis controlled by the normal LQR and the passive one, shows better performance. Meanwhile, the problem of defining the weight matrices is greatly solved. |
| format | Article |
| id | doaj-art-838724cd6ae3490aa0b1731ec9ef3906 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-838724cd6ae3490aa0b1731ec9ef39062025-02-03T01:23:34ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/420719420719Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing AlgorithmJie Meng0Qingzhang Chen1Ren He2Department of Automotive Engineering, Changshu Institute of Technology, Changshu 215500, ChinaDepartment of Automotive Engineering, Changshu Institute of Technology, Changshu 215500, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaA method is designed to optimize the weight matrix of the LQR controller by using the simulated annealing algorithm. This method utilizes the random searching characteristics of the algorithm to optimize the weight matrices with the target function of suspension performance indexes. This method improves the design efficiency and control performance of the LQR control, and solves the problem of the LQR controller when defining the weight matrices. And a simulation is provided for vehicle active chassis control. The result shows that the active suspension using LQR optimized by the genetic algorithm compared to the chassis controlled by the normal LQR and the passive one, shows better performance. Meanwhile, the problem of defining the weight matrices is greatly solved.http://dx.doi.org/10.1155/2014/420719 |
| spellingShingle | Jie Meng Qingzhang Chen Ren He Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm Journal of Applied Mathematics |
| title | Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm |
| title_full | Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm |
| title_fullStr | Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm |
| title_full_unstemmed | Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm |
| title_short | Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm |
| title_sort | research on optimal control for the vehicle suspension based on the simulated annealing algorithm |
| url | http://dx.doi.org/10.1155/2014/420719 |
| work_keys_str_mv | AT jiemeng researchonoptimalcontrolforthevehiclesuspensionbasedonthesimulatedannealingalgorithm AT qingzhangchen researchonoptimalcontrolforthevehiclesuspensionbasedonthesimulatedannealingalgorithm AT renhe researchonoptimalcontrolforthevehiclesuspensionbasedonthesimulatedannealingalgorithm |