| Wall-climbing robots have been increasingly applied to large tank surface operations.However,its motion control becomes complex because of its particularity of motion and tank surface environment,.In order to solve the problem of motion control in tank operation,this article takes the wall-climbing robot with magnetically adsorbed wheels as the carrier.the research were taken as follows:Firstly,aiming at the problem of tracking desired path on tank surface by wallclimbing robot,a kinematics and dynamics model was established.Based on sliding mode control theory,the assistant velocity and angular velocity,which were derived from the constraints of kinematics error state equation,expected angular velocity and stability function,subtract the actual speed and angular velocity.And the errors were taken as the sliding mode switching surface.Then the sliding mode controller was obtained by Backstepping method.Considering the influence of environment,adaptive control was proposed to estimate uncertain parameters.The controller was improved and the asymptotic stability of Lyapunov was verified.Compared with general sliding mode control and self-adaptive fuzzy control simulation.The results indicates that the improved controller significantly improve the tracking accuracy and response speed of the desired path,and shows strong robustness.Aiming at obstacle avoidance during tank surface operation,a solution of obstacle avoidance by fuzzy control was proposed and a fuzzy controller was designed.The distance between the wall-climbing robot and the obstacle,the angle between the wallclimbing robot and the target point were taken as inputs,and the speed and angular speed of the wall-climbing robot were taken as outputs.The domain and membership degree of each parameter were determined,and the fuzzy rule table was established.The center of gravity method was used to solve the fuzzification.Considering the complexity and variability of tank environment,an elegant downgrading obstacle avoidance control strategy was proposed,which can still cross the obstacle to reach the target point when the detection sensor was temporarily malfunctioning due to the environmental impact.Through simulation with artificial potential field obstacle avoidance method,the fuzzy control method can avoid obstacles more effectively,and it also ensures that the wall-climbing robot reaches the target point in the case of detecting sensor anomalies.According to the requirement of motion control algorithm,the control system of the wall-climbing robot was designed.In order to improve the control flexibility,the master-slave control structure was used in the wheel motor control module and the wallclimbing robot can walk freely on the surface of the tank.In addition,the design of sensor module enabled that the wall-climbing robot locate itself and detect obstacles in the process of operation.The wireless communication module was designed to facilitate the interaction between the wall climbing robot and the remote computer.As mentioned above,the software design of the whole motion control system was completed.Finally,the experiments of straight-line trajectory tracking and obstacle avoidance for were carried out.Wall-climbing robot performed accuracy in tracking the straight line trajectory had a good function.On the other hand,it can avoid the obstacles ahead in time.From the experiments mentioned above,the validity of control system,the path tracking controller and the obstacle avoidance controller were well-verified. |
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