CDM Based Servo State Feedback Controller with Feedback Linearization for Magnetic Levitation Ball System
| Main Authors: | Ma'arif, Alfian; Universitas Gadjah Mada, Cahyadi, Adha imam; Universitas Gadjah Mada, Wahyunggoro, Oyas; Universitas Gadjah Mada |
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| Other Authors: | Adha Imam Cahyadi & Oyas Wahyunggoro, Department of Electrical Engineering and Information Technology, Engineering Faculty, Universitas Gadjah Mada |
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
International Journal on Advanced Science, Engineering and Information Technology
, 2018
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| Subjects: | |
| Online Access: |
http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/1218 http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/1218/pdf_749 |
Daftar Isi:
- This paper explains the design of Servo State Feedback Controller and Feedback Linearization for Magnetic Levitation Ball System (MLBS). The system uses feedback linearization to change the nonlinear model of magnetic levitation ball system to the linear system. Servo state feedback controller controls the position of the ball. An integrator eliminates the steady state error in servo state feedback controller. The parameter of integral gain and state feedback gains is achieved from the concept of Coefficient Diagram Method (CDM). The CDM requires the controllable canonical form, because of that Matrix Transformation is needed. Hence, feedback linearization is applied first to the MLBS then converted to a controllable form by a transformation matrix. The simulation shows the system can follow the desired position and robust from the position disturbance. The uncertainty parameter of mass, inductance, and resistance of MLBS also being investigated in the simulation. Comparing CDM with another method such as Linear Quadratic Regulator (LQR) and Pole Placement, CDM can give better response, that is no overshoot but a quite fast response. The main advantage of CDM is it has a standard parameter to obtain controller’s parameter hence it can avoid trial and error.