Control strategies for high inertia servo systems
(2025)Department of Automatic Control
- Abstract
- Automated servo systems are widely used in today’s industry. Therefore, there is high value in improving the reliability and accuracy of these systems and reducing costs. One way to achieve this is to remove the gearbox component, since it typically represents a large fraction of the system’s cost, and it contains many moving parts which will wear and eventually fail. However, removing the gearbox often leads to issues in controllability due to factors such as the increased moment of inertia discrepancy between the motor and load. This thesis evaluates the performance of different control strategies applied to such a system, tested on two physical testing rigs. The evaluated controller architectures are PID, cascaded P-PI, cascaded P-P... (More)
- Automated servo systems are widely used in today’s industry. Therefore, there is high value in improving the reliability and accuracy of these systems and reducing costs. One way to achieve this is to remove the gearbox component, since it typically represents a large fraction of the system’s cost, and it contains many moving parts which will wear and eventually fail. However, removing the gearbox often leads to issues in controllability due to factors such as the increased moment of inertia discrepancy between the motor and load. This thesis evaluates the performance of different control strategies applied to such a system, tested on two physical testing rigs. The evaluated controller architectures are PID, cascaded P-PI, cascaded P-P with real-time trajectory planning, and MPC. These were coupled with feedforward control based on a model derived from different system identification methods. The results show that it is possible to control the tested system using a variety of methods. PID and cascaded P-PI performed well if coupled with feedforward and gain scheduling. The cascaded P-P controller with a real-time trajectory planner had great resilience against large disturbances, although more difficult to implement. The MPC was difficult to implement and very computationally heavy, resulting in poor control. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9207957
- author
- Kugelberg, Erik and Lennartsson, Victor
- supervisor
- organization
- year
- 2025
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6281
- other publication id
- 0280-5316
- language
- English
- id
- 9207957
- date added to LUP
- 2025-08-08 15:08:51
- date last changed
- 2025-08-08 15:08:51
@misc{9207957,
abstract = {{Automated servo systems are widely used in today’s industry. Therefore, there is high value in improving the reliability and accuracy of these systems and reducing costs. One way to achieve this is to remove the gearbox component, since it typically represents a large fraction of the system’s cost, and it contains many moving parts which will wear and eventually fail. However, removing the gearbox often leads to issues in controllability due to factors such as the increased moment of inertia discrepancy between the motor and load. This thesis evaluates the performance of different control strategies applied to such a system, tested on two physical testing rigs. The evaluated controller architectures are PID, cascaded P-PI, cascaded P-P with real-time trajectory planning, and MPC. These were coupled with feedforward control based on a model derived from different system identification methods. The results show that it is possible to control the tested system using a variety of methods. PID and cascaded P-PI performed well if coupled with feedforward and gain scheduling. The cascaded P-P controller with a real-time trajectory planner had great resilience against large disturbances, although more difficult to implement. The MPC was difficult to implement and very computationally heavy, resulting in poor control.}},
author = {{Kugelberg, Erik and Lennartsson, Victor}},
language = {{eng}},
note = {{Student Paper}},
title = {{Control strategies for high inertia servo systems}},
year = {{2025}},
}