Microsystem Technologies

, Volume 17, Issue 5–7, pp 1135–1143 | Cite as

Design and implementation of LQG\LTR controller for a magnetic telemanipulation system-performance evaluation and energy saving

  • Moein Mehrtash
  • Mir Behrad KhameseeEmail author
Technical Paper


This paper deals with designing a telemanipulation system (TMS) for microrobotics applications. The TMS uses magnetic levitation technology for the three-dimensional (3-D) manipulation of a microrobot. The TMS is made up of two separate components: a magnetic drive unit and a microrobot. The magnetic drive unit is developed to generate the magnetic field for propelling the microrobot in an enclosed environment. The drive unit consists of electromagnets, a disc pole-piece for connecting the magnetic poles, and a yoke. To handle the 3-D high precision motion control of the microrobot, experimental magnetic field measurements coupled with numerical analysis were done to identify the dynamic model of levitation. This approach leads to the design of a linear quadratic gaussian (LQG) control system, based on the derived state-space model. Based on the PID controller performance, the LQG controller provides considerable improvement in transient response and cross coupling errors. The 3-D motion control capability of the LQG control method is verified experimentally, and it is demonstrated that the microrobot can be operated in the TMS workspace, vertical range of 30 mm and the horizontal range of \(32\times 32\,{\text{mm}}^2\), with RMS error on the order of \(10\,\upmu {\text{m}}\) in the vertical and \(2.2\,\upmu {\text{m}}\) in the horizontal direction. In the vertical motion, the cross coupling error of the LQG controller is nine times smaller than that of the PID controller. A pre-magnetized pole-piece is proposed to compensate for gravity effect and reduces the system’s energy consumption. This pole-piece provides 66% energy saving for the system’s workspace operations.


Permanent Magnet Kalman Filter Levitation Force Linear Quadratic Regulator Cross Coupling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors gratefully acknowledge the Canada Foundation for Innovation (CFI) and the Natural Science and Engineering Research Council of Canada (NSERC) for financial support.


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Mechanical and Mechatronics Engineering DepartmentUniversity of WaterlooWaterlooCanada

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