Predictive Control for Small Unmanned Ground Vehicles via a Multi-Dimensional Taylor Network

Abstract

Tracking control of Small Unmanned Ground Vehicles (SUGVs) is easily affected by the nonlinearity and time-varying characteristics. An improved predictive control scheme based on the multi-dimensional Taylor network (MTN) is proposed for tracking control of SUGVs. First, a MTN model is used as a predictive model to construct a SUGV model and back propagation (BP) is taken as its learning algorithm. Second, the predictive control law is designed and the traditional objective function is improved to obtain a predictive objective function with a differential term. The optimal control quantity is given in real time through iterative optimization. Meanwhile, the stability of the closed-loop system is proved by the Lyapunov stability theorem. Finally, a tracking control experiment on the SUGV model is used to verify the effectiveness of the proposed scheme. For comparison, traditional MTN and Radial Basis Function (RBF) predictive control schemes are introduced. Moreover, a noise disturbance is considered. Experimental results show that the proposed scheme is effective, which ensures that the vehicle can quickly and accurately track the desired yaw velocity signal with good real-time, robustness, and convergence performance, and is superior to other comparison schemes.

Computational Simulation of an Agricultural Robotic Rover for Weed Control and Fallen Fruit Collection—Algorithms for Image Detection and Recognition and Systems Control, Regulation, and Command

“…A suitable autonomous movement strategy, in addition to precisely controlling the robot in the desired direction, allows eliminating the effects of disturbances and factors that reduce the robot's accuracy in performing a certain operation. Different robot control approaches can be found in [8][9][10][11][12][13][14][15]. Specifically, in [16], an autonomous robot used modelbased control considering the vehicle's motion, including the effects of wheel sideslip, to calculate speed and steering commands.…”