Research On Path Tracking For Mobile Robots Based On Predictive Control

With the development of science and control technology,mobile robots have been widely used in scientific research,military,industrial,civil and logistics applications due to their dexterous structure and strong environmental adaptability.As one of the three basic issues in the motion control of mobile robots,path tracking has been received extensive attention.The research on path tracking control is not limited to the field of mobile robots,but also relates to tracking grinding of numerical control machine,track control of aircrafts and ships,and other fields.Therefore,the research on path tracking control for mobile robots has significant theoretical and engineering,because it not only enriches the theoretical results of mobile robot motion control,but also satisfies the increasingly high requirements of motion control technology in many other fields.In addition,by introducing the network teleoperation technology,the ability range of mobile robots has been extended,which can effectively satisfy the needs of human being unable to work in specific scenes directly.However,under the network environment,especially the wireless network,data packets loss and data quantization inevitably exist in the communication network,which brings new challenges to the path tracking control of mobile robots.In this thesis,the moving horizon estimation method,robust predictive control method and experimental platform design are studied for the path tracking of mobile robots with the influence of communication constraints such as packet dropouts and quantization.The main work and results are as follows:1.A moving horizon estimation method is proposed for mobile robots with the packet dropouts,quantization and disturbances.Firstly,considering the effects of packet dropouts and data quantization,the path tracking problem is modeled as a kind of tracking error state space model with random variables and parameter uncertainties.Using the least squares estimation method,the min-max design criterion and stochastic system method,the parameterized design process of the state estimator is derived.Finally,the simulation example is given to verify the validity of the proposed algorithm.2.A robust predictive tracking control method is proposed for path tracking control of mobile robots with communication constraints.Firstly,a state space prediction model for mobile robots is established.Based on the prediction model,the optimization problem is presented with random parameters and uncertain parameters constraints in the quadratic performance indexes.Using the method of robust least squares regulation,the parameter-dependent predictive controller is designed by solve the predictive optimization problem.Finally,the simulation example is given to verify the validity of the proposed algorithm.3.Based on visual navigation,we design and build a smart car experiment platform,which has the functions of autonomous navigation and attitude calculation.The software of the upper computer of the mobile robot is programmed,which is fulfilled the task of sending the order information of the mobile robot and drawing the graphic of the state information for the mobile robot.Based on the proposed robust predictive control algorithm,the path tracking experiment of mobile robot is designed,and the effectiveness of the proposed algorithm is verified.