论文部分内容阅读
A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under net work environment.Under the distributed control structure ,online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication.By iterating on modified distributed lin ear optimal control problems on the basis of est imating parameters at every iteration the correct op timal control action of the nonlinear model predicti ve control problem of the cascade system could b e obtained,assuming that the algorithm was convergen t.This approach avoids solving the complex nonlinear optimi zation problem and significantly reduces the computation al burden.The simulation results of the fossil f uel power unit are illustrated to verify the eff ectiveness and practicability of the proposed algorithm.
A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under net work environment. Unit of the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication.By iterating on modified distributed lin ear optimal control problems on the basis of est imating parameters at every iteration the correct op timal control action of the nonlinear model predicti ve control problem of the cascade system could be obtained, assume that the algorithm was convergen t.This approach avoids solving the complex nonlinear optimization zation problem and significantly reduces the computation al burden. the simulation results of the fossil f uel power unit are illustrated to verify the eff ectiveness and practicability of the proposed algorithm.