Abstract
To achieve the goal of driver-less underground mining truck, a fuzzy hyperbolic tangent model is established for path tracking on an underground articulated mining truck. Firstly, the sample data of parameters are collected by the driver controlling articulated vehicle at a speed of 3 m/s, including both the lateral position deviation and the variation of heading angle deviation. Then, according to the improved adaptive BP neural network model and deriving formula of mediation rate of error estimator by the method of Cauchy robust, the weights are identified. Finally, H-infinity control controller is designed to control steering angle. The results of hardware-in-the-loop simulation show that lateral position deviation, heading angle deviation, and steering angle of the vehicle can be controlled, respectively, at 0.024 m, 0.08 rad, and 0.21 rad. All the deviations are asymptotically stable, and error control is in less than 2%. The method is demonstrated to be effective and reliable in path tracking for the underground vehicles.
Highlights
Articulated vehicle is widely used in underground mining
This article provides a method used in unmanned systems based on the way of fuzzy hyperbolic pole control act for articulated vehicle trajectory tracking accurately
(1) Fuzzy hyperbolic tangent model can well describe the quantitative relation among lateral displacement error, the orientation error, and the articulated angle
Summary
Articulated vehicle is widely used in underground mining. Researches on driver-less articulated vehicle have been carried out for many years to prompt efficiency and safety in underground mine. Literature [12] considers the influence of articulated vehicle dynamics on sideslip, but there would be a big deviation as they only consider one aspect and the lack of system modeling To solve these problems above and to deal with this multivariable, strong coupling, highly complex nonlinear dynamical systems of underground mining vehicles, we use fuzzy hyperbolic model and design a nonlinear quadratic controller through testing field experiments by hardware-in-the-loop. (HIL) simulation to ensure the quality of control, aiming at achieving the goal of unmanned underground mining articulated vehicles This method is to obtain kinematic relations of vehicle via the driver information, and the fact that driver repeatedly driving the process can make the relationship dynamics of the vehicle which are included in those data becomes increasingly evident. Hardware verification control which results in the final loop (HIL) simulation is done in order to ensure quality control
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