An approach for parameter estimation of proportional-integral-derivative(PID) control system using a new nonlinear programming(NLP) algorithm was proposed.SQP/IIPM algorithm is a sequential quadratic programming(SQP) ...An approach for parameter estimation of proportional-integral-derivative(PID) control system using a new nonlinear programming(NLP) algorithm was proposed.SQP/IIPM algorithm is a sequential quadratic programming(SQP) based algorithm that derives its search directions by solving quadratic programming(QP) subproblems via an infeasible interior point method(IIPM) and evaluates step length adaptively via a simple line search and/or a quadratic search algorithm depending on the termination of the IIPM solver.The task of tuning PI/PID parameters for the first-and second-order systems was modeled as constrained NLP problem. SQP/IIPM algorithm was applied to determining the optimum parameters for the PI/PID control systems.To assess the performance of the proposed method,a Matlab simulation of PID controller tuning was conducted to compare the proposed SQP/IIPM algorithm with the gain and phase margin(GPM) method and Ziegler-Nichols(ZN) method.The results reveal that,for both step and impulse response tests,the PI/PID controller using SQP/IIPM optimization algorithm consistently reduce rise time,settling-time and remarkably lower overshoot compared to GPM and ZN methods,and the proposed method improves the robustness and effectiveness of numerical optimization of PID control systems.展开更多
The present paper deals with a multiobjective optimization of truss topology by either Sequential Linear Programming （SLP） method or Linear Programming （LP） method. The ground structure approach is often used to s...The present paper deals with a multiobjective optimization of truss topology by either Sequential Linear Programming （SLP） method or Linear Programming （LP） method. The ground structure approach is often used to solve this kind of design problems. In this paper, the topology optimization is formulated as a Multiobjective Optimization Problem （MOP）, which is to find the cross-sectional area of truss members, such that both the total volume of members and the weighted mean compliance are minimized. Based upon the Karush-Kuhn-Tucker conditions （the optimality condition）, the Pareto optimal front of this problem can be obtained theoretically. The truss topology optimization under multiple load cases can be solved by the SLP. On the other hand, the LP such as the Simplex method or the interior point method can be applied to find one of the Pareto optimal solutions of the MOP under single load case. The applications of either the SLP or the LP are illustrated in numerical examples with discussion on characteristics of design results.展开更多
In this paper, new approaches for chaotic time series prediction areintroduced. We first summarize and evaluate the existing local prediction models, then proposeoptimization models and new algorithms to modify proced...In this paper, new approaches for chaotic time series prediction areintroduced. We first summarize and evaluate the existing local prediction models, then proposeoptimization models and new algorithms to modify procedures of local approximations. Themodification to the choice of sample sets is given, and the zeroth-order approximation is improvedby a linear programming method. Four procedures of first-order approximation are compared, andcorresponding modified methods are given. Lastly, the idea of nonlinear feedback to raise predictingaccuracy is put forward. In the end, we discuss two important examples, i.e. Lorenz system andRoessler system, and the simulation experiments indicate that the modified algorithms are effective.展开更多
基金Project(60874070) supported by the National Natural Science Foundation of ChinaProject(20070533131) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education of China
文摘An approach for parameter estimation of proportional-integral-derivative(PID) control system using a new nonlinear programming(NLP) algorithm was proposed.SQP/IIPM algorithm is a sequential quadratic programming(SQP) based algorithm that derives its search directions by solving quadratic programming(QP) subproblems via an infeasible interior point method(IIPM) and evaluates step length adaptively via a simple line search and/or a quadratic search algorithm depending on the termination of the IIPM solver.The task of tuning PI/PID parameters for the first-and second-order systems was modeled as constrained NLP problem. SQP/IIPM algorithm was applied to determining the optimum parameters for the PI/PID control systems.To assess the performance of the proposed method,a Matlab simulation of PID controller tuning was conducted to compare the proposed SQP/IIPM algorithm with the gain and phase margin(GPM) method and Ziegler-Nichols(ZN) method.The results reveal that,for both step and impulse response tests,the PI/PID controller using SQP/IIPM optimization algorithm consistently reduce rise time,settling-time and remarkably lower overshoot compared to GPM and ZN methods,and the proposed method improves the robustness and effectiveness of numerical optimization of PID control systems.
文摘The present paper deals with a multiobjective optimization of truss topology by either Sequential Linear Programming （SLP） method or Linear Programming （LP） method. The ground structure approach is often used to solve this kind of design problems. In this paper, the topology optimization is formulated as a Multiobjective Optimization Problem （MOP）, which is to find the cross-sectional area of truss members, such that both the total volume of members and the weighted mean compliance are minimized. Based upon the Karush-Kuhn-Tucker conditions （the optimality condition）, the Pareto optimal front of this problem can be obtained theoretically. The truss topology optimization under multiple load cases can be solved by the SLP. On the other hand, the LP such as the Simplex method or the interior point method can be applied to find one of the Pareto optimal solutions of the MOP under single load case. The applications of either the SLP or the LP are illustrated in numerical examples with discussion on characteristics of design results.
文摘In this paper, new approaches for chaotic time series prediction areintroduced. We first summarize and evaluate the existing local prediction models, then proposeoptimization models and new algorithms to modify procedures of local approximations. Themodification to the choice of sample sets is given, and the zeroth-order approximation is improvedby a linear programming method. Four procedures of first-order approximation are compared, andcorresponding modified methods are given. Lastly, the idea of nonlinear feedback to raise predictingaccuracy is put forward. In the end, we discuss two important examples, i.e. Lorenz system andRoessler system, and the simulation experiments indicate that the modified algorithms are effective.
