Backstepping Sliding Mode Hover Control Based on Nonlinear Disturbance Observer for Spherical Robot
Aiming at the hovering control problem of spherical robot used in transformer internal detection, a Backstepping sliding mode control method based on nonlinear disturbance observer was proposed to estimate and compensate the interference in robot motion direction. Firstly established the robot motion model, then the disturbance observer was constructed according to the system state equation, and the inverse sliding mode controller was proposed based on the Lyapunov stability theory. The simulation results showed that the designed nonlinear disturbance observer can effectively reduce the instability caused by the external disturbances in the horizontal and depth directions during the hovering process of the robot, it has strong robustness. Introduction Transformer internal inspection robot is a micro spherical robot which can enter the transformer internal for fault detection directly, it equipped with camera, lighting, depth gauge and attitude sensor, can be used to film the fault condition of oil-immersed transformer, such as the inner winding deformation and insulation degradation, and the internal image real-time transmission to the control side, the realization of transformer internal fault accurate identification. The robot is spherical in shape and structure, propelled by 6 channel injection pumps, capable of 4-dof operation, with zero turning radius and flexible movement [1,2,3,4,5]. It is very suitable for the complex environment with such special structure inside the transformer and narrow area. For underwater robot's motion control problems, the researchers conducted a lot of research and put forward a variety of adaptive control methods, such as fuzzy control, sliding mode control, neural network control and a variety of control mode combined with compound control method, etc., to a certain extent solved the error due to such as modeling, hydrodynamic parameter uncertainty caused by the robot control problems. A neural network cerebellar model definition control (CMAC) and a fuzzy controller is respectively adopted to optimize the design of the PID controller of AUV in [6,7], which enhanced the stability and anti-interference of the controller. For the AUV motion control problem with non-complete constraints, the point stabilization control model of AUV is established based on decoupling transformation, inverse step control, power integral, logic control and other methods in [8,9,10,11], and the global asymptotic stability of AUV is effectively achieved; In [12], taking into account of unknown disturbance factors of nonlinear system, a dynamic disturbance compensator is introduced to design the sliding mode controller, which realized the motion control of AUV. In [13], the AUV three-dimensional path tracking sliding mode controller is designed by using feedback correction and Backstepping optimization, which has good tracking performance. In [14], a fuzzy sliding mode controller is designed, which effectively improves the stability and robustness of AUV. Although the above controllers have relatively good control performance, the complexity of the controllers is not suitable for direct application of the underlying control of the robot, and there is still no optimal control method for the precise motion control of the micro-underwater robot in the