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Journal ArticleDOI

Trajectory planning and collision avoidance for underwater vehicles using optimal control

I. Spangelo, +1 more
- 01 Oct 1994 - 
- Vol. 19, Iss: 4, pp 502-511
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TLDR
In this article, an energy-optimal trajectory for underwater vehicles was computed using a numerical solution of the optimal control problem using a performance index consisting of a weighted combination of energy and time consumption.
Abstract
Energy-optimal trajectories for underwater vehicles be computed using a numerical solution of the optimal control problem. A performance index consisting of a weighted combination of energy and time consumption is proposed. Collision avoidance is solved by including path constraints. Control vector parameterization with direct single shooting is used in this study. The vehicle is modeled with six-dimensional nonlinear and coupled equations of motion. Optimal trajectories are computed for a vehicle controlled in all six degrees of freedom by dc-motor-driven thrusters. Good numerical results are achieved. >

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Citations
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Journal ArticleDOI

An overview of simultaneous strategies for dynamic optimization

TL;DR: This study provides background information, summarizes the underlying concepts and properties of this approach, discusses recent advances in the treatment of discrete decisions and illustrates the approach with two process case studies.
Journal ArticleDOI

Nonlinear Formation-Keeping and Mooring Control of Multiple Autonomous Underwater Vehicles

TL;DR: In this paper, a nonlinear formation-keeping and mooring control of multiple autonomous underwater vehicles (AUVs) in chained form is considered. But the authors focus on the formation of the AUVs and not on the control of the moorings.
Journal ArticleDOI

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

TL;DR: The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.
Journal ArticleDOI

3D path planning for underwater vehicles using five evolutionary optimization algorithms avoiding static and energetic obstacles

TL;DR: Five intelligent evolutionary algorithms (EAs), which include genetic algorithm, memetic algorithm, particle swarm optimization, ant colony optimization and shuffled frog leaping algorithm, are applied to solve the NOCP to show that the trajectories obtained by the intelligent methods are better than those of conjugate gradient method.
Journal ArticleDOI

Robust trajectory control of underwater vehicles using time delay control law

TL;DR: In this paper, a new control scheme for robust trajectory control based on direct estimation of system dynamics is proposed for underwater vehicles, which can work satisfactorily under heavy uncertainty that is commonly encountered in the case of underwater vehicle control.
References
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Journal ArticleDOI

A Multiple Shooting Algorithm for Direct Solution of Optimal Control Problems

TL;DR: A condensing algorithm for the solution of the approximating linearly constrained quadratic subproblems, and high rank update procedures are introduced, which are especially suited for optimal control problems and lead to significant improvements of the convergence behaviour and reductions of computing time and storage requirements.
Journal ArticleDOI

Real-time obstacle avoidance for fast mobile robots

TL;DR: A real-time obstacle avoidance approach for mobile robots that permits the detection of unknown obstacles simultaneously with the steering of the mobile robot to avoid collisions and advance toward the target.
Journal ArticleDOI

Direct trajectory optimization using nonlinear programming and collocation

TL;DR: In this article, an algorithm for the direct numerical solution of an optimal control problem is given, which employs cubic polynomials to represent state variables, linearly interpolates control variables, and uses collocation to satisfy the differential equations.
Book

Optimal control

Book

Optimization Methods

H. Tolle
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