Performance Assessment For Fractional-order Temperature Control System

Control performance assessment is an important branch of control theory research.The controllers in industrial control loops generally maintain high performance in the initial stage of production.However,due to the influence of complex industrial environment,the loop controller cannot keep stable operation for a long time,so that the performance of the control system cannot meet the production requirements,ultimately leading to a decline in product quality and even serious consequences such as production safety incidents.Therefore,it is of great practical significance to design a reasonable control performance assessment technology for evaluating the performance of the loop controller.And then the high-performance operation of the loop controller and the safety and efficient operation of the industrial production process can be ensured.Temperature control systems are a class of processes with large time-delay and nonlinear characteristics.Studies have shown that such processes can be better controlled by the use of fractional order modeling and fractional order control methods.At the same time,the existing studies for control performance assessment are almost committed to the integer order control systems,the methods used in few literatures on performance assessment of fractional order systems are also one-sided.Therefore,this paper starts from the LQG assessment benchmark that consider both input and output performance,and applies the LQG benchmark and the newly proposed fractional order LQG benchmark to the performance assessment study of fractional order control system for the first time.In this paper,the temperature control system of industrial electric heating furnace is taken as the research object.From the perspective of fractional model identification,control performance assessment method and controller performance optimization,the following three parts are mainly studied:(1)Firstly,the structure of the industrial electric heating furnace and its working flow are introduced.Then,the heating furnace heating experiment is carried out.By collecting the input and output data,the new Luus-Jaakola(NLJ)method based on time domain information is used to identify the fractional order model of the heating furnace.(2)Based on the fractional order model of furnace,the LQG benchmark is used to obtain the LQG performance tradeoff curve.Then,for the furnace control system with model matching and mismatch,the performance assessment of fractional predictive functional controller(FO-PFC)with different parameters is studied by using the LQG benchmark.(3)On the basis of the conventional LQG benchmark,a fractional order LQG is designed by adding a fractional calculus operator to the LQG object function and simultaneously discretizing the furnace fractional order model with the GrünwaldLetnikov fractional order calculus definition,which is further used to obtain the fractional order LQG performance tradeoff curve.It is proved by simulation that the fractional order LQG benchmark is more referable and more reasonable than the conventional LQG benchmark.Finally,By using the proposed benchmark,the performance of fractional order PID(FO-PID)controller with different parameters is evaluated for the furnace control system with model matching and mismatch.