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Fei Long_Dissertation Final.pdf (8.38 MB)

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Three-Dimensional Motion Control and Dynamic Force Sensing of a Magnetically Propelled Micro Particle Using a Hexapole Magnetic Actuator

Long, Fei
http://rave.ohiolink.edu/etdc/view?acc_num=osu1452093964

Abstract Details

2016, Doctor of Philosophy, Ohio State University, Mechanical Engineering.
This dissertation presents the development of a hexapole 3D magnetic actuator that can be used as a probing system by actively controlling a magnetic bead in three dimensional space. The magnetic force, which is a noncontact force, is an ideal force for biological applications due to its biocompatibility and magnetic susceptibility. This magnetic actuator can achieve magnetic bead stabilization, trajectory tracking, accurate force modeling and dynamic force sensing. These capabilities will transform the magnetic actuator from the traditional force applier to a three-dimensional scanning probe system, which is not achieved in other magnetic actuator systems. An over-actuated Hexapole magnetic actuator is employed to realize 3D motion control of the magnetic bead. A lumped parameter magnetic force model is derived to characterize the nonlinear relationship from the input current to the output magnetic force. This electromagnetic actuating system achieves significantly greater force generation capability compared with existing magnetic actuators [1, 2]. These improvements are accomplished through enhanced design and optimization of the current allocation of the over-actuated system. A magnetic bead can be stably controlled and steered and the magnetic force model is experimentally validated. The fundamental issues in this over-actuated multi-pole actuator are caused by the following four characteristics of the magnetic force: a) redundancy and coupling, b) instability, c) nonlinearity, and d) position dependency. An optimal inverse model of the over-actuated hexapole electromagnetic actuating system over the 3-D workspace is derived to minimize 2-norm of the six input currents when applied to produce the desired 3-D magnetic force on the magnetic bead. This inverse model greatly facilitate the feedback linearization in the feedback control. Due to the compact form of the optimal inverse model, it can be implemented in high speed real-time control to achieve stable magnetic bead trapping and precise motion control. Another challenge in electromagnetic actuation system is the hysteresis effect. The existing current-based magnetic force model relies on the assumption that the magnetic flux generation is proportional to the input current, which is not valid under hysteresis effect. The hysteresis effect will greatly degrade the magnetic force model accuracy. As soft magnetic material is used in this magnetic actuator, the hysteresis effect is not only nonlinear but also rate-dependent. Moreover, the magnetic coupling among six magnetic poles will make the hysteresis issue beyond the capability of modeling. To solve this problem, Hall sensors are introduced to directly measure the magnetic field in each pole and a so called Hall-Sensor-based magnetic force model is proposed. Owning to the 3-D motion control capability, the Hall-Sensor-based and current-based magnetic force models can be experimentally calibrated and compared by steering the magnetic bead wherein the viscous force can serve as the reference force. It is clearly seen that the Hall-Sensor-based magnetic force model greatly outperforms the current-based magnetic force model in term of force modeling accuracy. When the magnetic field becomes larger, the magnetization saturation of the magnetic bead begin to emerge and a more accurate Hall-sensor based model is proposed in which the nonlinear magnetization effect of the magnetic bead is modeled. With accurate magnetic force model, a dynamic force sensing estimator can be developed to achieve real-time dynamic force sensing and parameter estimation simultaneously. With the measurement information of the magnetic bead and the Hall-sensor based magnetic force model, the bead-sample interaction force can be dynamically estimated. Moreover, the drag coefficient can be also estimated, which is an indication of the environment change such as the wall effect, fluid property change and etc. The Kalman filter algorithm is used to estimate the state variables since the dynamics subject to random thermal force and measurement noises. Combined with motion control capability, this magnetic actuator can achieve force control application and automatic scanning of an unknown environment.
Chia-Hsiang Menq (Advisor)
Manoj Srinivasan (Committee Member)
Rama Yedavalli (Committee Member)
Vadim Utkin (Committee Member)
166 p.
Mechanical Engineering
over-actuated system, electromagnetic actuator, magnetic particle control, magnetic force generation, optimal current allocation, Hall sensor based magnetic force model, hysteresis, dynamic force sensing

Recommended Citations

Citations

  • Long, F. (2016). Three-Dimensional Motion Control and Dynamic Force Sensing of a Magnetically Propelled Micro Particle Using a Hexapole Magnetic Actuator [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1452093964

    APA Style (7th edition)

  • Long, Fei. Three-Dimensional Motion Control and Dynamic Force Sensing of a Magnetically Propelled Micro Particle Using a Hexapole Magnetic Actuator. 2016. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1452093964.

    MLA Style (8th edition)

  • Long, Fei. "Three-Dimensional Motion Control and Dynamic Force Sensing of a Magnetically Propelled Micro Particle Using a Hexapole Magnetic Actuator." Doctoral dissertation, Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1452093964

    Chicago Manual of Style (17th edition)

osu1452093964
536
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This open access ETD is published by The Ohio State University and OhioLINK.