Title : 
PID Tuning Based on Improved Quantum Genetic Algorithm
         
        
            Author : 
Jian Zhang ; Li Liu ; Huanzhou Li ; Zhangguo Tang
         
        
            Author_Institution : 
Sch. of Phys. & Electron. Eng., Sichuan Normal Univ., Chengdu, China
         
        
        
        
        
        
        
            Abstract : 
Parameters tuning is the key of the design of PID controller, for the PID parameters tuning, a PID parameters tuning method based on improved quantum genetic algorithm is proposed in this study. This study proposes an improved genetic algorithm (IQGA) which introduces a dynamic adjustment strategy of population and search intervals to improve the convergence speed, search ability and stability of quantum genetic algorithm-based PID parameters tuning method. Experimental results show that the proposed algorithm can obtain a good performance in PID parameters tuning problem.
         
        
            Keywords : 
control system synthesis; genetic algorithms; search problems; three-term control; IQGA; PID controller design; PID parameters tuning method; dynamic adjustment strategy; improved quantum genetic algorithm; search ability; search intervals; Genetic algorithms; PD control; Quantum computing; Sociology; Statistics; Tuning; PID parameters; quantum genetic algorithm; tuning;
         
        
        
        
            Conference_Titel : 
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
         
        
            Conference_Location : 
Hangzhou
         
        
        
            DOI : 
10.1109/ISCID.2013.125