Design Of Fractional Order Controller For Thermal Systems

Fractional order PIλDμ controller appling the theory of fractional calculus to control fields, extends the order of traditional PID from integer to fractional. The introduction of fractional order λ and μ makes the design of PIλDμ controller more flexible, and it also makes the control system with better robustness and stronger disturbance rejection ability. Practice has proved that in the application of control theory, fractional calculus can produce better results than integer order calculus. In thermal power plants, the control performance of the main steam temperature of circulating fluidized bed boiler plays a conclusive part. However, it is difficult to control main steam temperature of circulating fluidized bed boiler, for its features such as strong coupling, large lag and nonlinearity. In order to improve the control level, Fractional order controllers PIλDμ is proposed and its parameters are tuned by chaos particle swarm optimization method (CPSO) and genetic algorithm (GA).Main contributions of this article are given as follows:(1) Describe the development of fractional calculus, its application and research in control fields. Introduce fractional calculus theory and systematic properties, and also introduce fractional order differential equations and its numerical solution.(2) Analyze fractional order control system from the perspective of stability and frequency domain, and describe the definition and structure of fractional order PIλDμ. It is analyzed and appraised how the control performance is influenced by the control parameters in PIλDμ controller through theoretical analysis and simulation experiments.(3) The introduction of integral order λ and differential order μ increases difficulties for parameter verification. Whether the control performance is stand or fall, parameters play a conclusive part. In this article, fractional order controller PIλDμ is designed based on two Intelligence Optimization Algorithms that is CPSO and GA. The theory, process and implementation steps of CPSO and GA are described, and fractional PiλDμ programs based on CPSO and GA are written which adapts discrete fractional order numerical methods with memory length to fractional differential equations.(4) Take main steam temperature of circulating fluidized bed boiler as the controlled object, and tune PIλDμ parameters by particle swarm optimization (PSO), CPSO and GA. Simulation results verify that, Fractional order PIλDμ controller, whose parameters are tuned by CPSO and GA, is applied to main steam temperature of circulating fluidized bed boiler. The system has good level of control, reflected in the fast response, high control accuracy, high anti-interference ability and strong robustness.