Date of Award
Master of Applied Science (MASc)
Belt drives have been serving the industry for a long period. Certain features of belt drives such as slippage, tension fluctuations, and sliding of the belt on the pulleys lead to highly nonlinear deformation, large rigid body motion, dynamical contact with sticking and slipping zones and cyclic tension. The performance of motion control for belt drives is important in many industrial fields and is affected by these factors. Advanced control can improve robustness of belt drive and result in a faster dynamic response and more accuracy. The Purpose of this project is to develop a mathematical model of an experimental belt drive system through physical modeling and system identification. This model is then used for the design of an advanced robust discrete-time controller. An extensive literature review is provided, covering modeling and control of belt drive system as well as sliding mode control (SMC) theory. Physical modeling is carried out for an experimental system followed by system identification. Both the physical and the identified models are used to analyze and investigate the characteristics of the system. Different control approaches such as discrete-time proportional integral derivative (DPID) and discrete-time sliding mode control (DSMC) are designed and implemented. The results are compared and conclusions are drawn from both control approaches.
Zhu, Shenjin, "Modeling. System Identification and Control of a Belt Drive System" (2011). Open Access Dissertations and Theses. Paper 4969.
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