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Hierarchical Rule-Base Reduction Fuzzy Control for Constant Velocity Path Tracking of a Differential Steer Vehicle
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  • Samuel R. Dekhterman,
  • Maxwel Cichon,
  • William R. Norris,
  • Dustin Nottage,
  • Ahmet Soylemezoglu
Samuel R. Dekhterman
University of Illinois Urbana-Champaign Department of Industrial and Enterprise Systems Engineering

Corresponding Author:[email protected]

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Maxwel Cichon
University of Illinois Urbana-Champaign Department of Industrial and Enterprise Systems Engineering
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William R. Norris
University of Illinois Urbana-Champaign Department of Industrial and Enterprise Systems Engineering
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Dustin Nottage
US Army Corps of Engineers Construction Engineering Research Laboratory
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Ahmet Soylemezoglu
US Army Corps of Engineers Construction Engineering Research Laboratory
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Abstract

A new form of waypoint navigation controller for a skid-steer vehicle is presented, which consisted of a multiple input-single output nonlinear fuzzy angular velocity controller. The mem- bership functions of the fuzzy controller employed a trape- zoidal structure with a completely symmetric rule-base. No- tably, Hierarchical Rule-Base Reduction (HRBR) was incorpo- rated into the controller to select only the rules most influen- tial on state errors. This was done by selecting inputs/outputs and generating a hierarchy of inputs using a Fuzzy Relations Control Strategy (FRCS). Similar to some traditional fuzzy con- trollers, the system provided coverage for the global operat- ing environment. However, a rule for every possible combi- nation of variables and states was no longer necessary. Con- sequently, HRBR fuzzy controllers effectively increase both the number of inputs and their associated fidelity without the rule-base dramatically increasing. To contextualize the performance of the controller, a background on vehicle dy- namic modeling methodologies and an in-depth explanation of the related simulation model are provided. An examina- tion of the proposed controller is then completed employing test courses. The test courses examine the effects of steer- ing disturbance, phase lag, and overshoot as expressed in Root Mean Square Error (RMSE), Max Error (ME), and Course Completion Time (CCT). Finally, simulation and experimental results for the controller’s performance were compared with a state-of-the-art waypoint navigation vehicle controller, ge- ometric pure pursuit. The fuzzy was found to outperform the pure pursuit experimentally by 52.1 percent in RMSE, 26.8 percent in ME, and 1.07 percent in CCT, on average, validat- ing the viability of the controller.
02 May 2023Submitted to Journal of Field Robotics
02 May 2023Submission Checks Completed
02 May 2023Assigned to Editor
10 May 2023Review(s) Completed, Editorial Evaluation Pending
16 May 2023Reviewer(s) Assigned
08 Jul 2023Editorial Decision: Revise Major
23 Aug 20231st Revision Received
23 Aug 2023Submission Checks Completed
23 Aug 2023Assigned to Editor
23 Aug 2023Review(s) Completed, Editorial Evaluation Pending
23 Aug 2023Reviewer(s) Assigned
28 Oct 2023Editorial Decision: Revise Major
14 Nov 20232nd Revision Received
14 Nov 2023Review(s) Completed, Editorial Evaluation Pending
14 Nov 2023Submission Checks Completed
14 Nov 2023Assigned to Editor
15 Nov 2023Reviewer(s) Assigned