This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller fo...This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller for a laser beam steering system.The proposed technique uses the ADRC philosophy to lump disturbances and model uncertainties into a total disturbance.Then,the total disturbance is estimated via a discrete extended state disturbance observer(ESO),and it is used to(1)handle the system constraints in a quadratic optimization problem and(2)injected as a feedforward term to the plant to reject the total disturbance,together with the feedback term obtained by the MPC.The main advantage of the proposed approach is that the MPC is designed based on a straightforward integrator-chain model such that a simple convex optimization problem is performed.Several experiments show the real-time closed-loop performance regarding trajectory tracking and disturbance rejection.Owing to simplicity,the self-contained approach MPC+ESO becomes a Frugal MPC,which is computationally economical,adaptable,efficient,resilient,and suitable for applications where on-board computational resources are limited.展开更多
This paper proposes a dual alternative iter-ation algorithm-based hierarchical MPC(DAMPC)strategy to realize frequency regulation control and active power allocation of wind-storage coupling system.The proposed DAMPC ...This paper proposes a dual alternative iter-ation algorithm-based hierarchical MPC(DAMPC)strategy to realize frequency regulation control and active power allocation of wind-storage coupling system.The proposed DAMPC strategy involves a top-level grid fre-quency model predictive control(FMPC)strategy and a bottom-level multi-objective model predictive control(MMPC)strategy.In the FMPC strategy,to improve the frequency regulation performance,the active power ref-erence of the wind-storage coupling system is generated by minimizing the frequency deviation,where the fre-quency reference is calculated by considering the active power deviation and its integral.In the MMPC strategy,the active power reference is optimally allocated to the wind turbine generators(WTGs)and battery energy storage system(BESS)by raising the minimum rotor speed,minimizing the pitch angle deviation and state of charge(SOC)deviation.To solve the multi-objective al-location optimization problem with high efficiency,a dual alternative iteration algorithm(DAIA)is proposed to update the global and local control vectors with the dual vector.Extensive simulations validate the effectiveness of the proposed DAMPC strategy in frequency regulation and active power allocation.展开更多
基金support through his Master scholarshipThe Vicerrectoría de Investigación y Estudios de Posgrado(VIEP-BUAP)partially funded this work under grant number 00593-PV/2025.
文摘This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller for a laser beam steering system.The proposed technique uses the ADRC philosophy to lump disturbances and model uncertainties into a total disturbance.Then,the total disturbance is estimated via a discrete extended state disturbance observer(ESO),and it is used to(1)handle the system constraints in a quadratic optimization problem and(2)injected as a feedforward term to the plant to reject the total disturbance,together with the feedback term obtained by the MPC.The main advantage of the proposed approach is that the MPC is designed based on a straightforward integrator-chain model such that a simple convex optimization problem is performed.Several experiments show the real-time closed-loop performance regarding trajectory tracking and disturbance rejection.Owing to simplicity,the self-contained approach MPC+ESO becomes a Frugal MPC,which is computationally economical,adaptable,efficient,resilient,and suitable for applications where on-board computational resources are limited.
文摘This paper proposes a dual alternative iter-ation algorithm-based hierarchical MPC(DAMPC)strategy to realize frequency regulation control and active power allocation of wind-storage coupling system.The proposed DAMPC strategy involves a top-level grid fre-quency model predictive control(FMPC)strategy and a bottom-level multi-objective model predictive control(MMPC)strategy.In the FMPC strategy,to improve the frequency regulation performance,the active power ref-erence of the wind-storage coupling system is generated by minimizing the frequency deviation,where the fre-quency reference is calculated by considering the active power deviation and its integral.In the MMPC strategy,the active power reference is optimally allocated to the wind turbine generators(WTGs)and battery energy storage system(BESS)by raising the minimum rotor speed,minimizing the pitch angle deviation and state of charge(SOC)deviation.To solve the multi-objective al-location optimization problem with high efficiency,a dual alternative iteration algorithm(DAIA)is proposed to update the global and local control vectors with the dual vector.Extensive simulations validate the effectiveness of the proposed DAMPC strategy in frequency regulation and active power allocation.
