Nonlinear programming approach for optimal control problems

Sie-Long, Kek (2013) Nonlinear programming approach for optimal control problems. In: Proceedings the 2nd International Conference on Global Optimization and Its Applications 2013 (ICoGOIA2013) , 28-29 August 2013, Melaka, Malaysia .

[img]
Preview
PDF
114Kb

Abstract

Optimal control problem, which is a dynamic optimization problem over a time horizon, is a practical problem in determining control and state trajectories to minimize a cost functional. The applications of this optimization problem have been well-defined over past decades. However, the use of nonlinear programming (NLP) approach for solving optimal control problems is still a potential research topic. In this paper, a formulation of NLP model for optimal control problems is done. In our model, a class of the difference equations, which is nature in discrete time or is discretized by using the approximation scheme, is considered. Based on the control parameterization approach, the optimal control problem is generalized in the canonical form as a mathematical optimization problem. The control variables are defined as control parameters and their values are then calculated. In doing so, the gradient formula of the cost function and the corresponding constraints is derived and is presented as an algorithm. The optimal solution of NLP model approximates closely to the true solution of the original optimal control problem at the end of the computation procedure. For illustration, four examples are studied and the results show the efficiency of the approach proposed.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:optimal control; nonlinear programming; control parameterization; canonical form; optimal solution
Subjects:Q Science > QA Mathematics > QA75 Calculating machines
Divisions:Faculty of Science, Technology and Human Development > Department of Science and Mathematics
ID Code:4432
Deposited By:Normajihan Abd. Rahman
Deposited On:24 Oct 2013 16:29
Last Modified:21 Jan 2015 16:20

Repository Staff Only: item control page