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Introducing the Accelerating Coordination Operator Multi-Objective Co-evolutionary Algorithms and Its Application in Inverted Pendulum Control

Author: ZhangZhanLi
Tutor: LiZuShu
School: Chongqing University of Technology
Course: Applied Computer Technology
Keywords: Genetic Algorithms Coevolution algorithm Multi-objective optimization The kinesthetic intelligence Schema theory Ring double inverted pendulum Acceleration operator Accelerated co - operator
CLC: TP13
Type: Master's thesis
Year: 2011
Downloads: 11
Quote: 0
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Abstract


In this paper, from the three parts to write the first part of the annular double inverted pendulum simulation model realization ; second part of the study of bionic intelligent algorithm ; Part III is the application improved Letting smart algorithm on the ring double inverted pendulum control for multi- objective optimization . The following were introduced from the three aspects . The ring two inverted pendulum realization of the simulation model . Ring two inverted pendulum relative an inverted pendulum complex multi- Newtonian mechanics mathematical model has been very difficult , so it is necessary to apply analytical mechanics Lagrangian mechanics , energy to achieve its mathematical model to obtain a two order matrix differential equations by the reduced-order into first-order differential equations , and then apply the fourth-order the the Long Ge Kuta law , the establishment of a computer simulation model to build a a good simulation test platform for the subsequent multi- objective optimization . Bionic intelligent algorithm . Genetic algorithm based research , design improved genetic algorithm introduced accelerated operators greatly improve the operating speed of the genetic algorithm , the calculation speed by at least an order of magnitude compared with traditional genetic algorithm . The acceleration operator there is insufficient is to be used only for single-objective optimization , and later designed a more complete accelerated co - operator . Acceleration operator in the case of a single objective , enhanced search capabilities . In multi-objective optimization also showed a good performance , not only search speed and passed the test high Victoria the target test function DTLZ3 in the case of the 10 target 19 variables . Coevolution algorithm based on further research, more complex hierarchical multi-objective coevolutionary algorithm . Ring double inverted pendulum multi-objective optimization . This part must first select the target to be optimized to design appropriate fitness function , and then based on the selected target , the last application of the improved design of earlier multi-objective optimization algorithm to optimize and achieved good results .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Automatic control theory
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