This thesis entails motor control system analysis, design, and optimization for the University of Arkansas NASA Robotic Mining Competition robot. The open-loop system is to be modeled and simulated in order to achieve a desired rapid, yet smooth response to a change in input. The initial goal of this work is to find a repeatable, generalized step-by-step process that can be used to tune the gains of a PID controller for multiple different operating points. Then, sensors are to be modeled onto the robot within a feedback loop to develop an error signal and to make the control system self-corrective to account for slippage upon the Martian terrain with unknown soil parameters. Then, the closed loop system will be simulated again subject to an input disturbance that would account for the undulations and inconsistencies of the Martian terrain.
Using the analysis techniques established in the first two phases of this thesis, methods of immediate optimization with regards to motor output performance and wheel slip correction are presented for the purpose of implementation upon the next iteration of the robot build. This work also presents a general algorithm for robot autonomy in competition runs, which comes along with specific sensor configuration and pseudocode for the basic commands that the algorithm is built upon.
Future work for the analysis and design phases of this work would involve several iterations of custom motor control boards to be manufactured and tested on the robot build to verify the proposed generalized process of the PID tuning method. Future work for the automation phase of this work would involve the construction of a practice pit for the robot to build upon the primary automation strategy presented in the latter sections of this thesis.
","abstract_html":"<p>This thesis entails motor control system analysis, design, and optimization for the University of Arkansas NASA Robotic Mining Competition robot. The open-loop system is to be modeled and simulated in order to achieve a desired rapid, yet smooth response to a change in input. The initial goal of this work is to find a repeatable, generalized step-by-step process that can be used to tune the gains of a PID controller for multiple different operating points. Then, sensors are to be modeled onto the robot within a feedback loop to develop an error signal and to make the control system self-corrective to account for slippage upon the Martian terrain with unknown soil parameters. Then, the closed loop system will be simulated again subject to an input disturbance that would account for the undulations and inconsistencies of the Martian terrain. </p> <p>Using the analysis techniques established in the first two phases of this thesis, methods of immediate optimization with regards to motor output performance and wheel slip correction are presented for the purpose of implementation upon the next iteration of the robot build. This work also presents a general algorithm for robot autonomy in competition runs, which comes along with specific sensor configuration and pseudocode for the basic commands that the algorithm is built upon. </p> <p>Future work for the analysis and design phases of this work would involve several iterations of custom motor control boards to be manufactured and tested on the robot build to verify the proposed generalized process of the PID tuning method. Future work for the automation phase of this work would involve the construction of a practice pit for the robot to build upon the primary automation strategy presented in the latter sections of this thesis. </p>","abstract_has_math":false,"creators":["Crawford, Austin Jerold"],"institution":null,"degree_name":"Master of Science in Mechanical Engineering (MSME)","degree_level":"Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Arnold, Mark E.","Chen, Yue"],"advisors":["Wejinya, Uche C."],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-05-01T07:00:00Z","date_published":"2019-05-01T07:00:00Z","updated_at":"2026-07-24T01:00:28Z","subjects":["Automation","Control Systems","Excavation","Robotics","Acoustics, Dynamics, and Controls","Applied Mechanics","Artificial Intelligence and Robotics","Computer-Aided Engineering and Design"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.uark.edu/etd/3308","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Arnold, Mark E.","Chen, Yue"]},{"key":"dc:contributor.advisor","label":"Advisor","values":["Wejinya, Uche C."]},{"key":"dc:creator","label":"Author","values":["Crawford, Austin Jerold"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-02-06T08:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Mechanical Engineering (MSME)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Automation","Control Systems","Excavation","Robotics","Acoustics, Dynamics, and Controls","Applied Mechanics","Artificial Intelligence and Robotics","Computer-Aided Engineering and Design"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.uark.edu/etd/3308"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis entails motor control system analysis, design, and optimization for the University of Arkansas NASA Robotic Mining Competition robot. The open-loop system is to be modeled and simulated in order to achieve a desired rapid, yet smooth response to a change in input. The initial goal of this work is to find a repeatable, generalized step-by-step process that can be used to tune the gains of a PID controller for multiple different operating points. Then, sensors are to be modeled onto the robot within a feedback loop to develop an error signal and to make the control system self-corrective to account for slippage upon the Martian terrain with unknown soil parameters. Then, the closed loop system will be simulated again subject to an input disturbance that would account for the undulations and inconsistencies of the Martian terrain.
Using the analysis techniques established in the first two phases of this thesis, methods of immediate optimization with regards to motor output performance and wheel slip correction are presented for the purpose of implementation upon the next iteration of the robot build. This work also presents a general algorithm for robot autonomy in competition runs, which comes along with specific sensor configuration and pseudocode for the basic commands that the algorithm is built upon.
Future work for the analysis and design phases of this work would involve several iterations of custom motor control boards to be manufactured and tested on the robot build to verify the proposed generalized process of the PID tuning method. Future work for the automation phase of this work would involve the construction of a practice pit for the robot to build upon the primary automation strategy presented in the latter sections of this thesis.
"]},{"key":"dc:title","label":"Title","values":["Motor Control Systems Analysis, Design, and Optimization Strategies for a Lightweight Excavation Robot"]}]}],"canonical_facts":{"dc:contributor":["Arnold, Mark E.","Chen, Yue"],"dc:contributor.advisor":["Wejinya, Uche C."],"dc:creator":["Crawford, Austin Jerold"],"dc:date":["2019"],"dc:date.available":["2024-02-06T08:00:00Z"],"dc:description.abstract":["This thesis entails motor control system analysis, design, and optimization for the University of Arkansas NASA Robotic Mining Competition robot. The open-loop system is to be modeled and simulated in order to achieve a desired rapid, yet smooth response to a change in input. The initial goal of this work is to find a repeatable, generalized step-by-step process that can be used to tune the gains of a PID controller for multiple different operating points. Then, sensors are to be modeled onto the robot within a feedback loop to develop an error signal and to make the control system self-corrective to account for slippage upon the Martian terrain with unknown soil parameters. Then, the closed loop system will be simulated again subject to an input disturbance that would account for the undulations and inconsistencies of the Martian terrain.
Using the analysis techniques established in the first two phases of this thesis, methods of immediate optimization with regards to motor output performance and wheel slip correction are presented for the purpose of implementation upon the next iteration of the robot build. This work also presents a general algorithm for robot autonomy in competition runs, which comes along with specific sensor configuration and pseudocode for the basic commands that the algorithm is built upon.
Future work for the analysis and design phases of this work would involve several iterations of custom motor control boards to be manufactured and tested on the robot build to verify the proposed generalized process of the PID tuning method. Future work for the automation phase of this work would involve the construction of a practice pit for the robot to build upon the primary automation strategy presented in the latter sections of this thesis.
"],"dc:identifier":["https://scholarworks.uark.edu/etd/3308"],"dc:subject":["Automation","Control Systems","Excavation","Robotics","Acoustics, Dynamics, and Controls","Applied Mechanics","Artificial Intelligence and Robotics","Computer-Aided Engineering and Design"],"dc:title":["Motor Control Systems Analysis, Design, and Optimization Strategies for a Lightweight Excavation Robot"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science in Mechanical Engineering (MSME)"]},"updated_at":"2026-07-24T01:00:28Z"}