Research On Fuzzy PID Track Control Technology For Unmanned Vessel Based On CMAC

As an intelligent marine motion platform,unmanned ship is not only used in modern military warfare,but also widely used in watercourse measurement,hydrological and water quality environmental monitoring.Unmanned ship is widely used and has become a research hotspot of intelligent marine equipment at home and abroad.Because of the complexity of unmanned ship's navigation conditions,how to ensure its fast and accurate tracking of the set track under the premise of safe navigation has become the basis of completing other strategic and tactical objectives of unmanned ship.Therefore,the design of an unmanned ship's track motion controller that can adapt to complex navigation environment is an important part of the Research of unmanned ship's motion control.In this paper,the unmanned experimental ship is taken as the research object.In order to obtain a fast,accurate and anti-jamming track controller,the track control algorithm is designed and optimized.A fuzzy adaptive PID control method based on CMAC neural network is adopted,which makes the unmanned experimental ship have better track tracking performance and dynamic and static response,and satisfies the engineering requirements of the unmanned ship control system well.? Its main research contents and achievements are as follows:(1)A linearized mathematical model of three-degree-of-freedom planar motion of unmanned ship is established based on the idea of integral modeling.The Nomoto control model of ship is obtained by designing a Labview parameter calculation platform.(2)The control principles of the fuzzy control algorithm and the classical PID algorithm are analyzed,and a fuzzy adaptive PID track controller is designed.Then the classical PID track control and the fuzzy adaptive PID track control are simulated with or without disturbance of wind,wave and current.The simulation results show that the fuzzy-PID control algorithm has better adaptive performance,but after adding disturbance,the ability of the fuzzy-PID control algorithm to suppress anti-interference is not strong because of the limited fuzzy rules.(3)To solve the problems of limited fuzzy rules and weak anti-jamming ability of the fuzzy PID control algorithm,CMAC cerebellar neural network algorithm is introduced.By using the advantage of the algorithm of "self-learning",a fuzzy adaptive PID controller based on CMAC neural network is designed combining with the fuzzy adaptive PID and CMAC neural network algorithm.A corresponding simulation model is established on Simulink,and the simulation is carried out in the environment without disturbance and given disturbance factors such as wind,wave and current.The simulation results show that the Fuzzy Adaptive PID Controller(FCMAC-PID)based on CMAC is better than the Fuzzy PID control in response speed,overshoot,rudder angle change and interference suppression.(4)According to the hardware schematic diagram,the designed track motion controller is applied to the track motion control of the unmanned ship in Hubei University of Technology,and the ship is validated in Gaohu Lake,Caidian District,Wuhan City.The experimental results show that although the track errors of the two controllers designed in this paper are less than 5 m of the project performance requirements,the FCMAC-PID controller has better performance and is more suitable for the project requirements.At the same time,the good performance of the designed controller is verified.