Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on line computational effort limits ...Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.展开更多
Focused on several problems during robot target tracking, and proposed a new kind of scheme and algorithm for it. The hybrid systematic structure reduces the control complexity and guarantees the tracking effectivenes...Focused on several problems during robot target tracking, and proposed a new kind of scheme and algorithm for it. The hybrid systematic structure reduces the control complexity and guarantees the tracking effectiveness as well as the control stability. The convergence and the feasibility of the algorithm are analyzed and proofed thoroughly. An on-line updating method for navigation coefficient is presented. Finally, the control scheme and proposed algorithm is applied to the real robotic system. The simulation and experimental results show its effectiveness.展开更多
文摘Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.
文摘Focused on several problems during robot target tracking, and proposed a new kind of scheme and algorithm for it. The hybrid systematic structure reduces the control complexity and guarantees the tracking effectiveness as well as the control stability. The convergence and the feasibility of the algorithm are analyzed and proofed thoroughly. An on-line updating method for navigation coefficient is presented. Finally, the control scheme and proposed algorithm is applied to the real robotic system. The simulation and experimental results show its effectiveness.
