Control parametrization: a unified approach to optimal control problems with general constraints
Automatica (Journal of IFAC)
A Chebyshev polynomial method for optimal control with state constraints
Automatica (Journal of IFAC)
Direct and indirect methods for trajectory optimization
Annals of Operations Research - Special issue on nonlinear methods in economic dynamics and optimal control: Gmo¨or-series No. 2
Journal of Global Optimization
Application of a novel IWO to the design of encoding sequences for DNA computing
Computers & Mathematics with Applications
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm
Applied Computational Intelligence and Soft Computing
Information Sciences: an International Journal
Hi-index | 0.00 |
An optimal control problem can be formulated through a set of differential equations describing the trajectory of the control variables that minimize the cost functional (related to both state and control variables). Direct solution methods for optimal control problems treat them from the perspective of global optimization: i.e. perform a global search for the control function that optimizes the required objective. In this article we use a recently developed ecologically inspired optimization technique called Invasive Weed Optimization (IWO) for solving such optimal control problems. Usually the direct solution method operates on discrete n-dimensional vectors and not on continuous functions. Consequently it can become computationally expensive for large values of n. Thus, a parameterization technique is required to represent the control functions using a small number of real-valued parameters. Typically, direct methods based on evolutionary computing techniques parameterize control functions with a piecewise constant approximation. This has obvious limitations both for accuracy in representing arbitrary functions, and for optimization efficiency. In this paper a new parameterization is introduced using Bezier curves, which can accurately represent continuous control functions with only a few parameters. It is combined with IWO into a new evolutionary direct method for optimal control. The effectiveness of the new method is demonstrated by solving a wide variety of optimal control problems.