Title

Sequential virtual motion camouflage method for nonlinear constrained optimal trajectory control

Authors

Authors

Y. J. Xu;G. Basset

Comments

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Abbreviated Journal Title

Automatica

Keywords

Nonlinear constrained optimization; Bio-inspired control; Optimal; trajectory design; PSEUDOSPECTRAL METHOD; COSTATE ESTIMATION; OPTIMIZATION; ALGORITHM; ROBOT; CONVERGENCE; COLLOCATION; STATE; STABILITY; DESIGN; Automation & Control Systems; Engineering, Electrical & Electronic

Abstract

Nonlinear constrained optimal trajectory planning is a challenging and fundamental area of research. This paper proposes bio-inspired fast-time approaches for this type of problems based on the inspiration drawn from the natural phenomenon known as the motion camouflage. Two algorithms are proposed: the virtual motion camouflage (VMC) subspace method and the sequential VMC method. As a hybrid approach, the sequential VMC method works through a two-step structure in each iteration. First, the VMC subspace method will solve for an optimal solution over a selected subspace. Second, an algorithm consisting of a linear programming and a line search will vary the subspace so that the next VMC subspace result will be guaranteed not to be worse than that of the current step. The dimension and time complexities of the algorithms will be analyzed, and the optimality of the solution via the sequential VMC approach will be studied. Through the VMC approaches, the state and control variables in the kinematics or dynamics models of vehicles in the selected subspace can be represented by a single degree-of-freedom vector, called the path control parameter vector. The reduction in dimension and no involvement of equality constraints will in practice make the convergence faster and easier, and a much smaller computational cost is expected. Two simulation examples, the Breakwell problem and a minimum time robot obstacle avoidance problem with different numbers of obstacles, are used to demonstrate the capabilities of the algorithms. (C) 2012 Elsevier Ltd. All rights reserved.

Journal Title

Automatica

Volume

48

Issue/Number

7

Publication Date

1-1-2012

Document Type

Article

Language

English

First Page

1273

Last Page

1285

WOS Identifier

WOS:000306615800006

ISSN

0005-1098

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