A Design Methodology for Adaptive Open-Seas Course-Keeping Control of Containerships (Adaptive, Steering, Ship)
Tugcu, Ahmet Kemal
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https://hdl.handle.net/2142/70126
Description
Title
A Design Methodology for Adaptive Open-Seas Course-Keeping Control of Containerships (Adaptive, Steering, Ship)
Author(s)
Tugcu, Ahmet Kemal
Issue Date
1984
Department of Study
Mechanical Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Mechanical
Abstract
During the seventies, the greatly increased price of fuel oil and substantial over-capacity in available tonnage of the world's merchant shipping have combined to cause a major problem for the maritime industry. This has stimulated an increasing interest in research on autopilots for ships. Much of this research effort is directed to the problem of automatic steering of merchant ships to minimize propulsion losses. The recent availability of small and inexpensive microprocessor-based digital computers enables practical application of modern, optimal, and adaptive control strategies.
The goal of this research is to formulate an adaptive control system design methodology for online minimization of steering related losses aboard ship. Previous research has resulted in the achievement of the formulation and general characterization of the problem over the range of ship types of commercial importance. It included the application of classical and modern control theories, namely PID (Proportional plus Integral plus Derivative) and LQG (Linear Quadratic Gaussian) control techniques, respectively. The knowledge gained about the ship, steering, and seaway disturbance system dynamics established the firm background for the design of adaptive steering autopilots. Additional information on the seaway disturbance dynamics were gathered by sensitivity analysis studies.
A time series model of the combined ship/steering and disturbance dynamics has been identified. The identification and a posteriori diagnostic check of the model required the use of extensive statistical methods including multivariable regression and residual analysis. The parameters of this model are estimated "online" by recursive least-squares techniques and the ship's heading angle is controlled by rudder commands generated by employing self-tuning control theory to minimize a performance index representative of steering related propulsion losses. The design includes the formulation and synthesis of a statistically optimal observer (Kalman Filter) to estimate the ship states which can adapt to changing seaway and ship's speed and loading conditions.
Quantitative evaluation of performance is provided by time-domain simulation techniques. Comparisons between the adaptive self-tuning controller and the PID and LQG controllers have shown that significant improvement in steering can be achieved by the implementation of an adaptive autopilot designed by the methodology presented.
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