Constrained Optimal Model Predictive and Disturbance Rejection Control Method for Outlet Temperature Control of Parabolic Trough Solar Fields
The control of outlet temperature of parabolic trough solar fields is crucial to the safety and economy of parabolic trough concentrating solar power plants.In general,the outlet temperature is required to be maintained near the setpoint or to track setpoint changes.But the existence of variable constraints and multiple field disturbances increases the difficulty of achieving this control goal.To address this issue,this paper proposes a constrained optimal model predictive and disturbance rejection control method,where the field disturbances are first reconstructed into a single lumped one through model transformation and an extended state observer is designed to estimate the lumped disturbance.Based on this,a dynamic optimization method of steady-state target value is proposed to compromise constraints satisfying,disturbance rejection,and set-point tracking.Then a maximum controlled admissible set with disturbance compensation is constructed to convert infinite constraints into finite number constraints,and an equivalent quadratic programming constrained optimization problem is solved by using dual-mode control strategy.Finally,the simulation results show that the proposed method can effectively compensate the adverse influence of field disturbances(like direct normal irradiation,field inlet temperature,heat transfer fluid flowrate and field parameters perturbations)and track given references under the premise that the control variable and its rate of change meet the constraints but sacrificing operating speed compared with the other two controllers.The proposed method can be used to solve the problems of multiple disturbance rejection,setpoint tracking and limited variables of a class of thermal objects,including the parabolic trough solar fields.
model predictive controlconstrained disturbance rejection controlextended state observerdual-mode controlparabolic trough solar field
万方数据
维普
