Abstract
This paper discusses the stabilization and position tracking control of the linear motion of an underactuated spherical robot. Including the actuator dynamics, the complete dynamic model of the robot is deduced, which is a third order, two-variable nonlinear differential system that holds underactuation, strong coupling characteristics brought by the mechanism structure of the robot. Different from traditional treatments no linearization is applied, whereas a single-input multiple-output PID (SIMO_PID) controller is proposed with a neural network controller to compensate the actuator nonlinearity. A six-input single-output CMAC_GBF (Cerebellar Model Articulation Controller with General Basis Function) neural network is employed, while the Credit Assignment (CA) learning method is adopted to obtain faster convergence rate than the classical backpropagation (BP) learning method. The proposed controller can be generalizable to other single-input multiple-output system with good real-time capability. MATLAB simulations are used to validate the control effects.
Highlights
A spherical robot is a new type of mobile robot that has a ball‐shaped outer shell to include all its mechanisms, control devices and energy sources inside it
By considering a spherical robot as a chained system Javadi et al (Javadi and Mojabi, 2002) established its dynamic model with the Newton method and discussed its motion planning with experimental validations
Et al (Antonio B. et al, 1997), (Antonio and Alessia, 2002) established a simplified dynamic model for a spherical robot and discussed its motion planning on a plane with obstacles
Summary
A spherical robot is a new type of mobile robot that has a ball‐shaped outer shell to include all its mechanisms, control devices and energy sources inside it. By considering a spherical robot as a chained system Javadi et al (Javadi and Mojabi, 2002) established its dynamic model with the Newton method and discussed its motion planning with experimental validations. Liu and Sun et al (Liu, Sun and Jia, 2008) deduced a simplified dynamic model for the driving ahead motion of a spherical robot through input‐state linearization and derived the angular velocity controller and angle controller respectively with full feedback linearized form. In view of that case, the representive linear motion control of an underactuated spherical robot BHQ‐1 developed in our lab is researched in this paper including the stabilization and position tracking issues.
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