The Study And Application Of Hybrid Error Adaptive Model For Ship Control Systems

The multi-process characteristics and interaction effects of ship control systems are studied in this thesis.A hybrid error feedback controller is applied to controlling the ship multi-process systems.This controller has the abilities of self-learning and the adaptability of asymptotically convergent characteristics.These abilities enable to improve the performance of the ship control systems.These characteristics are important for practical application to ship controls systems.In order to analyze the characteristics of generalized errors and their inherent behavior of the process information,a generalized error model is used to study hybrid error control systems.A fuzzy-neuro hybrid error model(FNHEM) is proposed for the ship multi-process systems.The structure learning of FNHEM is conduced with the degree measure and the parameter learning of the model is carried out with the ordered derivative algorithm.To increase memory abilities of FNHEM,the feedback connection elements are embedded in FNHEM,which has the advantage of dynamically recurrent error compensatory and needs few self-tuning parameters.A hybrid error model is established under the situation that the ship goes along the desired trajectory.The hybrid error model integrates the influences of the ship's environmental disturbances,of ship nonlinearly dynamic process,of thrust's propulsion and of speed of rudder angle on ship manoeuvre.Based on the hybrid error model,a generalized speed regulator of integrated ship-diesel engine system using self-learning and adaptive error model is researched,by which the closed-loop ship speed control is achieved.The main feature of the hybrid error control model is that the abilities of learning,identification and adaptation of the ship pilots are all integrated into the seaman ship systems for ship movement control scheme.A hardware-in-loop simulation system for marine propulsion-shaft electric generator is implemented.This system can feedback energy to the ship electrical network,so that the saving technology is realized.Integrated analysis of AVR using robust sliding mode self-tuning control method is carried out.Some intelligent control methods also are taken into consideration including the paralleling generators dynamic behavior error state-space,the hybrid error control of electric propulsion motor which consists of a parallel connected sliding mode controller and a fuzzy-neural controller, and the augmented linear quadratic Gaussian control scheme for exhaust turbine generator.Optimal control methods of multi-task automatic control for ship electric propulsion system is proposed,and its hybrid error control model is established and analyzed by Lyapunov stability Theory.A benchmark system for marine autopilot training with,semi-physical simulator is established,of which the generalized speed regulator of integrated ship-diesel engine system is achieved.Siemens Sinamics S120 and Simotion D Scout are used for hardware-in-loop simulation system of marine propulsion-shaft electric generator and energy feedback saving technology being realized.The hybrid error control method is tested on the benchmark system.The results show that hybrid error control model can enhance the stability for ship control process,has good adaptability and robustness.