Genetic algorithm based on receding horizon control for real-time implementations in dynamic environments
| Authors: | Hu XiaoBing, Loughborough University, United Kingdom
Chen Wen-Hua, Loughborough University, United Kingdom |
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| Topic: | 3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.) |
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| Session: | Soft Sensors and Predictive Control |
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| Keywords: | Receding horizon control, genetic algorithm, chromosome, fitness function, terminal penalty |
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Abstract
This paper introduces the concept of Receding Horizon Control (RHC) to Genetic Algorithm (GA) for real-time implementations in dynamic environments. The methodology of the new genetic algorithm is presented with the emphases on how to effectively integrate the RHC strategy by following some RHC practices in control engineering, particularly, how to choose the length of receding horizon and how to design terminal penalty. Simulation results show that, when the RHC based GA is applied in dynamic environments, the online computational burden is significantly reduced and the performance is satisfactorily improved compared with existing GAs.
