Euan McGookin

Ship steering control system optimisation using genetic algorithms

The optimisation of non-linear control systems by genetic algorithm is studied in this paper. It involves the performance of two systems for regulating the motion of a ship model. These systems allow Course Changing and Track Keeping through the implementation of a sliding mode controller. The genetic algorithm is used to optimise the performance of the complete system under various operating conditions by optimising the parameters of the sliding mode controller. The type of vessel considered is an oil tanker. ( 2000 Elsevier Science ‚td. All rights reserved.

A LEGO-based control experiment

A nice feature of the LEGO system is that, although the mechanical, electrical, and structural construction is good enough for successful results, there are enough discrepancies between theory and practice to introduce the student to real-world problems of controller. This article concentrates on implementing the feedback controller within the RCX, with the host computer used for compiling, downloading, and data display. However, an interesting research project is to implement part of the controller on the host computer and communicate by means of the IR channel. The bandwidth restriction that this approach imposes can provide the basis for a research project on control through a restricted bandwidth channel.

Optimisation of the weighting functions of an H ∞ controller using genetic algorithms and structured genetic algorithms

In this article, the optimisation of the weighting functions for an H ∞ controller using genetic algorithms and structured genetic algorithms is considered. The choice of the weighting functions is one of the key steps in the design of an H ∞ controller. The performance of the controller depends on these weighting functions since poorly chosen weighting functions will provide a poor controller. One approach that can solve this problem is the use of evolutionary techniques to tune the weighting parameters. The article presents the improved performance of structured genetic algorithms over conventional genetic algorithms and how this technique can assist with the identification of appropriate weighting functions’ orders.

The optimization of a tanker autopilot control system using genetic algorithms

A genetic algorithm (GA) optimization application is presented in this paper. It involves the performance optimization of a navigation system for a nonlinear tanker model. This navigation system is fully autonomous and regulates the heading of the vessel with reference to a desired course made up of waypoints. The system consists of two components. The first is a line of sight (LOS) autopilot, which determines the desired heading of the tanker from positional information. The second is a heading control system that is derived from sliding mode (SM) control theory. In this investigation the GA is used to optimize the parameters for the SM controller so that the performance of the complete system satisfies specific design criteria. The resulting optimized navigation system is evaluated for different operating conditions for the tanker, e.g., different course, different forward velocities.

Genetic Programming for the Automatic Design of Controllers for a Surface Ship

In this paper, the implementation of genetic programming (GP) to design a controller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the commanded forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships.

Segmented Simulated Annealing Applied to Sliding Mode Controller Design

Abstract This paper develops an optimisation technique based on Simulated Annealing (SA). It outlines conventional SA theory and then describes a variation which has been called Segmented Simulated Annealing (SSA). SSA is a method which selects the best results from numerous conventional SA runs where each SA starts at a different point in the search space. Conventional SA and SSA are compared by applying these techniques to the optimisation of two decoupled sliding mode controllers for a submarine simulation. These results are also compared with hand-tuned responses, which show that these optimisation techniques are more convenient to use than conventional hand-tuning methods.

Genetic algorithm optimisation of a supply ship propulsion and navigation systems

Two different control configurations have been designed for the navigation and propulsion systems of CyberShip I, a scale model of an oil platform supply ship. The first configuration consists of two classical linear PID controllers (one for the navigation system and the other for the propulsion). In the second configuration, a nonlinear sliding mode controller provides the navigation control and a PI control regulates the propulsion. Both control methodologies have parameters that need to be tuned to improve their performance. These parameters have been optimised using genetic algorithms. The performance of these two control methods has been compared and their robustness has been evaluated through the simulation of environmental disturbances. This investigation has been carried out through computer-generated simulations based on a non-linear hydrodynamic model of CyberShip I.

Modelling and control of a biomimetic autonomous underwater vehicle

This paper presents the mathematical modelling of a biomimetic underwater vehicle with the propulsion system based on fish-like undulation motion. The model has been developed based on conventional underwater vehicle concepts to determine the performance of this robotic fish. Maneuverability is an important aspect in designing this system. The maneuvering approach that has been employed in this study is to change the vehicle heading by altering the tail centreline. A PID based controller is used to act as steering system which controls the tails deflection angle. Finally a line of sight autopilot provides a position based outer loop around the PID controller in order to navigate autonomously through a course of predefined waypoints. The performance of each of these systems is analysed and discussed.

Sliding mode based inverse model control for oil tanker guidance

Abstract An inverse model based controller application is presented in this paper. In this application, inverse model control is implemented as a feedforward controller with assistance from a feedback controller. A comparison of performance is deduced between the proposed combined control structure, and that of a conventional feedback controller on its own. The corrective and feedback controller are designed using sliding mode control theory in order to regulate the heading dynamic for a nonlinear tanker model. In order to provide a more realistic evaluation, wave disturbances are implemented to provide a better comparison for the proposed control structure.

Reconfigurable sliding mode control for submarine manoeuvring

The design of a sliding mode controller for the heading manoeuvres of a nonlinear submarine model is presented. The performance of this control algorithm is evaluated for zigzag course changing manoeuvres at high speed. Also presented are reconfiguration processes based on sliding mode observers. These allow the control system to compensate for feedback sensor failures. Both the controller and the observer systems are evaluated for specific simulated manoeuvres in terms of performance and compensation in the presence of minor and major sensor faults.