{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/99408"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/99408","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Adaptive Torque Control of a Novel 3D-Printed Humanoid Leg","abstract":"In order to function safely in a dynamic environment with humans and obstacles, robots require active compliance control with force feedback. In these applications the control law typically includes full dynamics compensation to decouple the joints and cancel out nonlinearities, for which a high-fidelity model of the robot is required. In the case of a 3D-printed robot, components cannot be easily modeled due non-uniform densities, inconsistencies among the 3D printers used in manufacturing, and the use of different plastics with mechanical properties that are not widely known. To address this issue, this thesis presents an adaptive control framework which modifies the model parameters online in order to achieve satisfactory tracking performance. The inertial properties are estimated by adapting with respect to functions of the unknown parameters. This is achieved by rewriting the robot dynamics equations as the product of a matrix of known nonlinear functions of the joint states and a vector of constant unknowns. The result is a nonlinear system linearly parameterized in terms of the of the unknowns, which can be estimated using adaptation laws derived from Lyapunov stability theory. The proposed control system consists of an outer-loop impedance controller to regulate deviations from the nominal trajectory in the presence of disturbances, and an inner-loop force controller to track the joint torques commanded by the outer-loop. The proposed system is evaluated on an early prototype consisting of a 3DOF leg, and two actuator test setups for the low-level controller.","abstract_html":"In order to function safely in a dynamic environment with humans and obstacles, robots require active compliance control with force feedback. In these applications the control law typically includes full dynamics compensation to decouple the joints and cancel out nonlinearities, for which a high-fidelity model of the robot is required. In the case of a 3D-printed robot, components cannot be easily modeled due non-uniform densities, inconsistencies among the 3D printers used in manufacturing, and the use of different plastics with mechanical properties that are not widely known. To address this issue, this thesis presents an adaptive control framework which modifies the model parameters online in order to achieve satisfactory tracking performance. The inertial properties are estimated by adapting with respect to functions of the unknown parameters. This is achieved by rewriting the robot dynamics equations as the product of a matrix of known nonlinear functions of the joint states and a vector of constant unknowns. The result is a nonlinear system linearly parameterized in terms of the of the unknowns, which can be estimated using adaptation laws derived from Lyapunov stability theory. The proposed control system consists of an outer-loop impedance controller to regulate deviations from the nominal trajectory in the presence of disturbances, and an inner-loop force controller to track the joint torques commanded by the outer-loop. The proposed system is evaluated on an early prototype consisting of a 3DOF leg, and two actuator test setups for the low-level controller.","abstract_has_math":false,"creators":["Hancock, Philip Jackson"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Leonessa, Alexander"],"committee_members":["Akbari Hamed, Kaveh","Asbeck, Alan T."],"year":2020,"date_issued":"2020-07-23","date_published":"2020-07-23","updated_at":"2026-07-22T22:19:04Z","subjects":["Adaptive Control","Impedance Control","Robotics","Force Control","Humanoid","Compliance","3D Printed"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:27089"],"render_values":[{"text":"vt_gsexam:27089","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/99408","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Leonessa, Alexander"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Akbari Hamed, Kaveh","Asbeck, Alan T."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Hancock, Philip Jackson"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-07-24T08:00:28Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-07-24T08:00:28Z"]},{"key":"dc:date.issued","label":"Date","values":["2020-07-23"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Adaptive Control","Impedance Control","Robotics","Force Control","Humanoid","Compliance","3D Printed"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:27089"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/99408"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In order to function safely in a dynamic environment with humans and obstacles, robots require active compliance control with force feedback. In these applications the control law typically includes full dynamics compensation to decouple the joints and cancel out nonlinearities, for which a high-fidelity model of the robot is required. In the case of a 3D-printed robot, components cannot be easily modeled due non-uniform densities, inconsistencies among the 3D printers used in manufacturing, and the use of different plastics with mechanical properties that are not widely known. To address this issue, this thesis presents an adaptive control framework which modifies the model parameters online in order to achieve satisfactory tracking performance. The inertial properties are estimated by adapting with respect to functions of the unknown parameters. This is achieved by rewriting the robot dynamics equations as the product of a matrix of known nonlinear functions of the joint states and a vector of constant unknowns. The result is a nonlinear system linearly parameterized in terms of the of the unknowns, which can be estimated using adaptation laws derived from Lyapunov stability theory. The proposed control system consists of an outer-loop impedance controller to regulate deviations from the nominal trajectory in the presence of disturbances, and an inner-loop force controller to track the joint torques commanded by the outer-loop. The proposed system is evaluated on an early prototype consisting of a 3DOF leg, and two actuator test setups for the low-level controller."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["In order to function safely in a dynamic environment with humans and obstacles, a robot must be able to actively control its interaction forces with the outside environment. In these applications a high-fidelity model of the robot is required. In the case of a 3D-printed robot, the components in the robot cannot be easily modeled due non-uniform densities, inconsistencies among the 3D printers used in manufacturing, and the use of different plastics with mechanical properties that are not widely known. To address this issue, this thesis presents an adaptive control framework which actively modifies the model parameters in order to achieve satisfactory tracking performance. In this work, the equations of motion of the robot are manipulated in such a way that the unknown quantities are separated from the known quantities. The unknowns are updated in real time using adaptive laws derived from Lyapunov stability theory. The proposed control system consists of a high-level torque controller to regulate deviations from the nominal trajectory, and a low-level force controller to track the joint torques commanded at the high-level. The proposed system is evaluated on an early prototype of the robot consisting of a 3 degree of freedom leg, and two actuator test setups for the low-level controller."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Adaptive Torque Control of a Novel 3D-Printed Humanoid Leg"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Leonessa, Alexander"],"dc:contributor.committeemember":["Akbari Hamed, Kaveh","Asbeck, Alan T."],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Hancock, Philip Jackson"],"dc:date.accessioned":["2020-07-24T08:00:28Z"],"dc:date.available":["2020-07-24T08:00:28Z"],"dc:date.issued":["2020-07-23"],"dc:description.abstract":["In order to function safely in a dynamic environment with humans and obstacles, robots require active compliance control with force feedback. In these applications the control law typically includes full dynamics compensation to decouple the joints and cancel out nonlinearities, for which a high-fidelity model of the robot is required. In the case of a 3D-printed robot, components cannot be easily modeled due non-uniform densities, inconsistencies among the 3D printers used in manufacturing, and the use of different plastics with mechanical properties that are not widely known. To address this issue, this thesis presents an adaptive control framework which modifies the model parameters online in order to achieve satisfactory tracking performance. The inertial properties are estimated by adapting with respect to functions of the unknown parameters. This is achieved by rewriting the robot dynamics equations as the product of a matrix of known nonlinear functions of the joint states and a vector of constant unknowns. The result is a nonlinear system linearly parameterized in terms of the of the unknowns, which can be estimated using adaptation laws derived from Lyapunov stability theory. The proposed control system consists of an outer-loop impedance controller to regulate deviations from the nominal trajectory in the presence of disturbances, and an inner-loop force controller to track the joint torques commanded by the outer-loop. The proposed system is evaluated on an early prototype consisting of a 3DOF leg, and two actuator test setups for the low-level controller."],"dc:description.abstractgeneral":["In order to function safely in a dynamic environment with humans and obstacles, a robot must be able to actively control its interaction forces with the outside environment. In these applications a high-fidelity model of the robot is required. In the case of a 3D-printed robot, the components in the robot cannot be easily modeled due non-uniform densities, inconsistencies among the 3D printers used in manufacturing, and the use of different plastics with mechanical properties that are not widely known. To address this issue, this thesis presents an adaptive control framework which actively modifies the model parameters in order to achieve satisfactory tracking performance. In this work, the equations of motion of the robot are manipulated in such a way that the unknown quantities are separated from the known quantities. The unknowns are updated in real time using adaptive laws derived from Lyapunov stability theory. The proposed control system consists of a high-level torque controller to regulate deviations from the nominal trajectory, and a low-level force controller to track the joint torques commanded at the high-level. The proposed system is evaluated on an early prototype of the robot consisting of a 3 degree of freedom leg, and two actuator test setups for the low-level controller."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:27089"],"dc:identifier.uri":["http://hdl.handle.net/10919/99408"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Adaptive Control","Impedance Control","Robotics","Force Control","Humanoid","Compliance","3D Printed"],"dc:title":["Adaptive Torque Control of a Novel 3D-Printed Humanoid Leg"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:04Z"}