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Predictive Control for Small Unmanned
Ground
Vehicles via a Multi-Dimensional Taylor Network
Wu, Yuzhan ; Li, Chenlong ; Yuan, Changshun ; Li, Meng ; Li, Hao
Applied sciences, 2022-01, Vol.12 (2), p.682
[Peer Reviewed Journal]
Basel: MDPI AG
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Title:
Predictive Control for Small Unmanned
Ground
Vehicles via a Multi-Dimensional Taylor Network
Author:
Wu, Yuzhan
;
Li, Chenlong
;
Yuan, Changshun
;
Li, Meng
;
Li, Hao
Subjects:
Accuracy
;
Algorithms
;
Approximation
;
Artificial intelligence
;
Closed loop systems
;
Control stability
;
Control theory
;
Design
;
Distance learning
;
Feedback control
;
Ground
based control
;
Literature reviews
;
Mathematical models
;
Methods
;
multi-dimensional Taylor network
;
Neural networks
;
Noise prediction
;
nonlinear system
;
Objective function
;
Online instruction
;
Optimal control
;
Optimization
;
Prediction models
;
predictive control
;
predictive model
;
Radial basis function
;
Real time
;
SUGV
;
Tracking control
;
Unmanned
ground
vehicles
;
Vehicles
;
Yaw
Is Part Of:
Applied sciences, 2022-01, Vol.12 (2), p.682
Description:
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.
Publisher:
Basel: MDPI AG
Language:
English
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