Study On The Dynamics Analysis And Path Tracking Control For Articulated Tracked Vehicles

Articulated tracked vehicles(ATVs)are two section tracked vehicles that are connected and the articulated steering is achieved through articulated mechanisms.The ATVs have high passability and strong terrain adaptability in various off-road terrains;and are therefore widely used in emergency rescue and disaster relief situations.Due to the complex off-road conditions involved in disaster relief,research on path planning and path tracking control systems for offroad environments can ensure the safety of the ATVs.At the same time,the prerequisite for controlling the ATVs is to have a deep understanding of the dynamic characteristics of the steering motion of ATVs.Therefore,this dissertation studies the dynamic characteristics of the steering motion,path planning and path tracking control of the ATVs.When studying the dynamic characteristics of ATVs,a dynamic model of the steering condition of the ATVs is established,and the dynamic characteristics of steady-state and nonstationary steering of the ATVs are simulated and analyzed.The relationship between steering radius and track slip rate,driving force,and steering resistance torque is analyzed.Through virtual prototype simulation of ATVs,the effects of track speed difference and articulation angle on steering accuracy and track slip rate is analyzed.When optimizing the dynamic characteristics of ATVs,the coupling simulation model of multi-body dynamics of the ATVs and discrete element method is built.The real vehicle tests are conducted on the ATVs,including driving steering motion and stationary steering motion.By comparing the test values with the simulation values of the coupled simulation model,the coupled simulation model of the ATVs is validated.Then,the coupled simulation model is used to analyze the effects of track pre tension,load wheel spacing,and track plate width on steering performance indicators such as track grounding pressure,track tension,track driving torque,and steering resistance torque.A steering performance prediction model is established using the Kriging method,and the steering performance indicators are optimized using multiobjective genetic algorithm.The optimization results are sorted,screened,and verified.Research is conducted on path planning for ATVs by establishing an off-road path planning method for ATVs and simulating the method on an off-road grid map.On this basis,a local obstacle-avoidance path planning method is proposed,which combines with the ATVs kinematic model to optimize the process of obstacle avoidance planning.Simulation is conducted on a multi obstacle map to verify the rationality of the path planning method.In the research of the path tracking control system for ATVs,a control system scheme is proposed,which takes the deviation between the actual path and the preset path as input,adaptively changes the path deviation prediction model through the reference path,and controls the vehicle’s movement by changing the track speed and articulation angle.Based on the adaptive model predictive control method,a model predictive controller for the path tracking system of an ATVs is designed.The actual deviation of travel is used as the input variable of the controller,and the vehicle’s posture is adjusted by controlling the driving speed of multiple tracks and the articulation angle.Multiple path tracking simulations are conducted.The results show that,under the control of the adaptive model predictive controller,the ATVs can quickly and accurately track the reference path,verifying the reasonable design of the model predictive controller and its good control effect.A model predictive control algorithm based on Gaussian process model is proposed to address the problem of significant deviation between the linear model used in the dynamic control of ATVs and the actual vehicle dynamics in steering,lane changing,and other scenarios.The algorithm learns deviation data and designs a hierarchical control system.In the hierarchical control framework,the upper controller adopts a path tracking controller at the kinematic level,while the lower controller adopts a dynamic control algorithm based on learning MPC.The Gaussian process model is used to predict modeling deviation,and the combination of the two effectively improves the performance of articulated tracked vehicle dynamic control.The articulated tracked prototype and a path tracking system based on indoor positioning technology are designed,and the practicality of the established model prediction tracking method and path tracking control system is verified through path tracking experiments on different paths.This dissertation establishes a discrete-multi-body-dynamic model for dynamics analysis of ATVs and verifies it through experiments.The steering performance of ATVs is optimized using the coupling model.A path planning method and path tracking control method suitable for ATVs are designed,and the path tracking method is verified through path-tracking control experiments on experimental prototypes.The research work of this dissertation provides a solution for the dynamic performance analysis and optimization of ATVs,as well as solving the problem of vehicle path tracking control.