Multi-Mode Switched And Active Disturbance Rejection Control For Mobile Robot With Four Independently Controlled Wheels In Industrial Scenes

The mobile robot with four independently controlled wheels has excellent adaptability and maneuverability.Industrial scenarios with restricted operating spaces require it to be highly flexible.At the same time,the complex conditions such as ditch,sill and oil/water mixing on the ground put forward requirements for the accuracy and stability of its operation.The research object of this paper is the self-developed mobile robot with four independently controlled wheels in industrial scene.The methods of multi-mode switching,gain adaptive adjustment and disturbance self compensation under active disturbance rejection control framework are studied to improve the flexibility,accuracy and stability of operation.The research contents of this paper are as follows:Aiming at the operational efficiency issues of a single-mode in sharp turns in industrial scenarios,a multi-mode asynchronous switching method based on time-varying delay estimation is proposed to improve the flexibility of operation.Firstly,by designing a monotonic external signal and a high-order sliding mode tracking control scheme,a delay estimation scheme is proposed to realize the dynamic acquisition of delay information.Secondly,to improve the switching strategy of the system,a supervision criterion with dynamic thresholds is introduced based on the exponentially stable state observer to realize the trigger mechanism of autonomous switching.Finally,with the help of piecewise Lyapunov function,estimated time-varying delay and switching supervision criterion,the average dwell time in the process of autonomous switching is optimized,and the flexibility of the system and the adaptability to complex scenes are improved.In response to the problems of insufficient tracking accuracy during operation caused by system uncertainty and external interference that exist in industrial scenarios,gaining adaptive robust finite-time control is proposed to improve the stability in time-varying disturbance scenarios.To enhance the control performance of the system,a hierarchical control method is designed.On one hand,the nonlinear model predictive control method is used to reduce the overshoot and eliminate the steady-state error.On the other hand,the super-twisting controller realizes the continuous input of the control law to ensure the anti-interference performance of the system.Combined with theoretical analysis,the progressive convergence of the proposed hierarchical control scheme is verified to achieve the accuracy of the lateral motion of the system.Focusing on industrial scenarios where severe time-varying disturbances and system state coupling can easily lead to instability problems such as slippage and sideslip,an active disturbance rejection control method based on inverse system decoupling is proposed to realize unbiased estimation and dynamic compensation of external disturbances.Firstly,based on the inverse system decoupling strategy,the lateral dynamics model of the four-wheel omnidirectional mobile robot is decoupled to obtain a linear system.Secondly,a multi-layer network disturbance estimator with gain learning ability is designed to realize the unbiased estimation of disturbance through the dynamic adjustment of gain parameters.Finally,a self-compensating integrated control scheme is proposed to compensate for the estimated disturbance to further suppress the system disturbance.The stability of lateral motion is guaranteed by the integrated decoupling control method.Finally,the control performance of the proposed method is comprehensively verified by using the self-developed mobile robot with four independently controlled wheels,in the industrial scene.By analyzing the dynamic tracking characteristics and experimental results,the superiority of the proposed control method are verified,which provides a solid foundation for the application of the platform.