An Effective Dynamic Optimization Method Based on Modified Orthogonal Collocation and Reduced SQP
An effective dynamic optimization solution method based on the modified orthogonal collocation (mOC) and reduced successive quadratic programming (rSQP) is proposed, where the mOC is proposed to decrease the approximation error of the discrete optimal problem while traditional OC method converts the dynamic optimization problem to a regular but discrete nonlinear programming (NLP) problem, and the rSQP method is introduced to solve the resulting NLP problem in the reduced space of the independent variables. A classic benchmark of dynamic optimization problem is explored as demonstration, where the detailed comparative researches between the literature reports and the proposed method are carried out. The research results illustrate the efficiency of the proposed method.
Xinggao Liu Long Chen Yunqing Hu
Industrial Control Technology, Institute of Industrial Control, Department of Control Science & Engineering, Zhejiang University, Hangzhou 310027, China
国际会议
2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)
杭州
英文
503-507
2011-05-01(万方平台首次上网日期,不代表论文的发表时间)