Research On Trajectory Planning And Sliding Mode Control For An Underactuated Ship Based On Integrated Navigation Data

With the increasing focus on development of marine resources and maritime rights and interests, as well as expectations and requirements of ship intelligent control and autonomous navigation are also getting higher and higher, to a large extent, route planning and sliding mode control technique are directly related to the automation and intelligence level. It has numerous navigational instruments on board, such as GPS, AIS, radar, depth sounder, log, autopilot and so on, meanwhile these navigational aids provide a variety of navigation data. As different sensors provide the same type of data, then the sensor navigation information may be optimized through information processing method, ship’s route planning and trajectory control accuracy, and at the same time, navigation safety, saving energy can be improved effectively.(1)In order to solve the low-quality particles and degeneration in the process of particle filter, a particle filtering algorithm based on two stage adaptive adjusted weight is proposed. The process is divided into two steps, On the one hand, Multi-sensor data is sent to the appropriate particle filter calculation module in order to optimize the particle distribution for the purpose updating the proposed distribution density. On the other hand, Incorporate the likelihood model structured by multi-sensor data, meanwhile, this algorithm can adaptively adjust the weight function according to the euclidean distance and the accuracy factor constructed from statistic performance of measurement information, thus high-quality particles and, consequently, a more accurate estimate can be obtained. Simulation and sea trial experiment verify the effectiveness of the multi sensor information fusion algorithm based on adaptive weight particle filter.(2)In the case of 2D path planning, the path divides the space into two regions. This suggests a dual problem of first dividing the whole space into such two regions and then picking up the boundary as a path. We develop a method of solving this dual problem using support vector machine (SVM). SVM generates a non-linear separating surface based on the margin maximization principle. This property is suitable for the purpose of usual path planning problems. Two-dimensional space overall situation track planning algorithm is proposed for ships sailing safety and frugally using fuzzy logic particle swarm theory. This method designs the fuzzy controller and puts forward the particle swarm optimization algorithm based on fuzzy logic, Moreover, it sets up a fitness evaluation function according to discuss the navigable track and unnavigable track separately and describes the environment modeling of ship track planning, the algorithm is proposed due to the heuristic knowledge is led into track planning. Simulation experiment indicate that the effectiveness and the applicability of the proposed method.(3)We propose a network optimization approach, focusing on the generation of a special randomized network which is adapted to the maneuverability of the ship. The paths in the network correspond to smooth tracks consisting of clothoids and straight line segments. The approach allows to set restrictions on the track including turn radius constraints, thus avoiding too sharp maneuvers, but also other restrictions such as the exclusion of long-lasting weak maneuvers. The change of velocity during turning maneuvers is taken into account. The random structure of the network allows a large variety of maneuvers of different strengths and without turn degree limitations.By applying standard shortest-path methods, we can determine routes which avoid regions of risk higher than a given threshold. With appropriate costs defined on the edges, different objectives can be considered such as minimizing route length, traveling time, the number of maneuvers, or some compromise of these. Like all network-based methods, our approach is of a heuristic nature. On the other hand, the quality of the solutions can be continually improved by increasing the size of the network.(4)To address the problem of stabilization of underactuated surface vessels with parameter uncertainties and external disturbances, a stabilization control based on Backstepping control method is designed. Eventually, Simulations of the stabilization control for the underactuated surface vessel with disturbances or without disturbances are performed. Then, learning the properties of cascaded of the trajectory tracking mathematical model. The cascade system theory is considered when trajectory tracking controller is designed. Model predictive controller can effectively combine fast calculation performance of and adjust controller parameters sliding mode tracking controller. Do the simulation experiment of the ship trajectory tracking controller resp- -ectively and prove not only fulfill the input saturation constraint control law but also real-time computation. Compare with PID controller, it shows that the cascade system has better control performance.