Active compliance control of a hip exoskeleton robot for stoop lifting with muscle fatigue effect compensation
| dc.contributor.advisor | Gopura, RARC | |
| dc.contributor.advisor | Lalitharatne, SWHMTD | |
| dc.contributor.advisor | Ranaweera, RKPS | |
| dc.contributor.author | Dasanayake, NP | |
| dc.date.accept | 2025 | |
| dc.date.accessioned | 2026-08-12T04:39:42Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Compliance control has emerged as a control feature for robotic devices to ensure safe human-robot interaction and more versatile dynamic adaptation for changing environments. User intention estimation is essential when it comes to compliance control of exoskeleton robots. One prominent method of user intention estimation for exoskeleton robot is Electromyography (EMG). However, due to the non-stationarity of EMG signals, the user intention estimation is not accurate during dynamic musculoskeletal movements. Hence, compliance control will not work as intended. As a solution to this problem, a novel muscle fatigue effect compensation scheme is proposed and integrated with the compliance control algorithm. First, a human muscle fatigue index based on spatial, spectral and temporal features of EMG signals was developed. Dynamic cyclic flexion-extension experiments on four human subjects showed accuracy in estimating the fatigue level with an average coefficient of determination greater than 0.65. Furthermore, an EMG-based trunk muscle torque estimation method was developed using an Artificial Neural Network (ANN). Upon testing on four different human subjects, the trunk muscle torque estimator showed average coefficient of determination of 0.76 against measured muscle torque. Then Model Reference Adaptive Control (MRAC) system was developed for compliance control. The novel fatigue index and muscle torque estimator was incorporated with the controller to compensate for the effect of muscle fatigue. The MRAC was designed to refer to a low impedance reference model of an exoskeleton and human combined plant, thus ensuring the assistance needed for human trunk flexion-extension. System identification schemes for the actuators and, exoskeleton and human combined system were performed separately. The proposed controller was deployed on an existing hip exoskeleton robot and was tested on a single subject. A comparison of the system with and without fatigue compensation showed an improvement in human fatigue level and assistance given by the exoskeleton. | |
| dc.identifier.accno | TH6129 | |
| dc.identifier.citation | Dasanayake, N.P. (2025). Active compliance control of a hip exoskeleton robot for stoop lifting with muscle fatigue effect compensation [Master’s theses, University of Moratuwa]. Institutional Repository University of Moratuwa. https://dl.lib.uom.lk/handle/123/25477 | |
| dc.identifier.degree | Master of Philosophy (MPhil) | |
| dc.identifier.department | Department of Mechanical Engineering | |
| dc.identifier.faculty | Engineering | |
| dc.identifier.uri | https://dl.lib.uom.lk/handle/123/25477 | |
| dc.language.iso | en | |
| dc.subject | ROBOTIC EXOSKELETONS | |
| dc.subject | ROBOTICS ENGINEERING-Compliance Control | |
| dc.subject | ROBOTICS ENGINEERING-Fatigue Estimation | |
| dc.subject | MODEL REFERENCE ADAPTIVE CONTROL | |
| dc.subject | ELECTROMYOGRAPHY | |
| dc.subject | MASTER OF PHILOSOPHY-Dissertations | |
| dc.subject | MECHANICAL ENGINEERING-Dissertations | |
| dc.subject | Master of Philosophy (MPhil) | |
| dc.title | Active compliance control of a hip exoskeleton robot for stoop lifting with muscle fatigue effect compensation | |
| dc.type | Thesis-Abstract |
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