Track Tracking Control of Unmanned Intelligent Sweeping Vehicles Based on Improved MFAC

Yao, Wenlong; Pang, Zhen; Chi, Ronghu; Shao, Wei

doi:10.1007/978-981-15-8458-9_54

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…As the most widely used DDC method in path tracking algorithms, PID has been proven to be effective by many researchers. 32 the PID controller is as follows:…”

Section: Simulation Verificationmentioning

confidence: 99%

“…28 Modelfree adaptive control (MFAC) method, proposed by Hou Zhongsheng in 1994, 29 has been successfully applied in many practical systems, such as linear motor control 30 and traffic prediction. 31 A few scholars have applied the MFAC method to driverless vehicle path tracking 32 and unmanned surface vehicle heading control. 33 However, it has rarely been applied to tractor path tracking.…”

Section: Introductionmentioning

confidence: 99%

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Path tracking of autonomous tractor based on model-free adaptive control

Zhang

Cheng

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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Autonomous tractors, with path tracking as one of the key technologies, have become a research hotspot in recent years. However, the nonlinearity of and uncertainties in the autonomous tractor path tracking process can lead to challenges in terms of control. Although the model-based control method has been widely used in path tracking and achieved good results, only a limited number of model-free adaptive control (MFAC) methods have been developed for path tracking. This paper proposes an MFAC path tracking controller for autonomous tractors based on the use of a preview heading deviation method in which the preview heading angle is used as an input to control the steering, enabling the controller to achieve a small lateral error and stable control. In the simulation, the tracking effects of the designed controller, proportional integral differential (PID) and pure pursuit controllers at different speeds were compared. The results show that the proposed controller has good tracking ability and adaptability and can achieve high tracking accuracy. Finally, the tracking errors of the designed and PID controllers were compared in a real vehicle test, with the results verifying the effectiveness and practicality of the designed controller.

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“…As the most widely used DDC method in path tracking algorithms, PID has been proven to be effective by many researchers. 32 the PID controller is as follows:…”

Section: Simulation Verificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Path tracking of autonomous tractor based on model-free adaptive control

Zhang

Cheng

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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Autonomous Navigation Technology for Low-Speed Small Unmanned Vehicle: An Overview

Yin

et al. 2022

WEVJ

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In special locations (scenes) such as campuses and closed parks, small unmanned vehicles have gained more attention and application. Autonomous navigation is one of the key technologies of low-speed small unmanned vehicles. It has become a research hotspot, but there are still many problems, such as perception sensitivity, navigation, and positioning accuracy, motion planning accuracy, and tracking control accuracy. In order to sort out the research status of the key technologies of autonomous navigation for small unmanned vehicles more clearly, this paper firstly reviews the key technologies of autonomous navigation and presents an analysis and summary. Finally, future research trends of small unmanned vehicles with low speed are given.

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Track Tracking Control of Unmanned Intelligent Sweeping Vehicles Based on Improved MFAC

Cited by 2 publications

References 9 publications

Path tracking of autonomous tractor based on model-free adaptive control

Path tracking of autonomous tractor based on model-free adaptive control

Autonomous Navigation Technology for Low-Speed Small Unmanned Vehicle: An Overview

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