About Me

My research field generally involves mechatronics, automatic control of dynamic systems, and their application in manufacturing applications. Currently I'm working as a PhD candidate in Smart and Sustainable Automation Research Lab in University of Michigan, Ann Arbor.

    My specific research goals are to:
  • Reduce the tradeoff between the performance, energy efficiency, productivity in manufacturing applications,
  • Provide physical insights into the dynamic systems and propose appropriate control methods,
  • Apply the insights to propose novel machine design concept and new manufacturing process.

Research Projects

Over-Actuated Hybrid Feed Drive

Hybrid feed drive (HFD) is a precise and energy efficient solution for motion delivery in machining applications. The hybrid concept arises from two basic machining operations: rapid positioning and cutting. The rapid positioning desires high speed; while in cutting the speed is relatively slower, however stringent tolerance is required under significant cutting force. To address the drastic different needs of the two operations, actuators of different types are employed. As shown in the figure, a fast, precise, but energy costly linear motor drive (LMD), is combined with an energy efficient screw drive (SD) with lower speed and precision. This combination of SD and LMD is reconfigurable based on operations. For rapid motion, the LMD drives the table alone to achieve high speed; for cutting motion, both LMD and SD are synergistically employed–SD provides the holding force to reduce energy consumption while the LMD fine-tunes the tracking performance for precision. The (dis)engagement of the rotary motor in the SD is achieved through a reconfigurable friction drive device Roh’lix. The Roh’lix translates the rotation to linear motion like traditional screw drive, however (dis)engages freely across the shaft with the help of pneumatic actuated toggle mechanism.

This dual-input-single-output over-actuated system requires dedicate control design for the two actuators to collaborate desirably. A computational-efficient energy optimal control allocation scheme is proposed. The optimal control ratio between the actuators is derived and an energy efficiency metric (proxy) is defined accordingly. The proxy is theoretically shown to measure the deviation from the optimal ratio, and thus the regulation of the proxy allocates the control efforts. The proxy-based control allocation is compatible with various regulator design methodologies and saturation-type input constraints. This method has been further extended to multi-input multi-output system; a robust control allocation scheme which considers the model uncertainty is currently under investigation.

Intelligent Trajectory Generation

Tracking control aims to minimize the errors of a system’s output in following a desired trajectory. This is achieved through both feedback (FB) control and feedforward (FF) control. A FF controller uses a priori knowledge of a given system and its input(s) to influence the system’s output(s) in a pre-defined way, and is often used to augment the FB controller, which has limited tracing performance since it must wait for the error to develop before reaction. One general structure of the FF control is to modify the reference trajectory according to the desired trajectory and the system dynamics. Theoretically, perfect tracking can be achieved through direct inversion of a sufficiently accurate system model. However, direct inversion may not be applied to system with non-minimum phase (NMP) zeros, which is prevalent in practice. To address the tracking control problem within NMP system through trajectory generation, I proposed the filtered basis functions (FBF) method. It decomposes the modified trajectory into a set of basis function with unknown coefficients, which are selected to minimize the error in tracking the desired trajectory. This method avoids direct inversion, can incorporate additional constraints on the modified trajectory, and is shown to be less susceptible to NMP zero locations compared to other methods. Moreover, constraints on the trajectory can be conveniently embedded into FBF. The proposed FBF method is validated in experiment to effectively reduce the vibration-induced tracking error, and thus allows production of high quality part with less time.



  1. Duan, M., and Okwudire, C. E., “Connections between control allocation and linear quadratic control for weakly redundant systems,” Submitted to Automatica.
  2. Duan, M., and Okwudire, C. E., “Proxy-based energy optimal dynamic control allocation for dual-input, single-output over-actuated systems,” IEEE/ASME Transaction on Mechatronics (Accpeted).
  3. Duan, M., Yoon, D., and Okwudire, C. E., “A limited-preview filtered B-spline approach to tracking control – with application to vibration-induced error compensation of a 3D printer,” Mechatronics. [PDF]
  4. Ramani, K. S., Duan, M., Okwudire, C. E., and Ulsoy, A. G., 2017, “Tracking control of linear time- invariant nonminimum phase systems using filtered basis functions,” Journal of Dynamic System, Measurement and Control, 139(1), pp. 11001(1–11). [PDF]
  5. Duan, M., and Okwudire, C. E., 2016, “Energy-efficient controller design for a redundantly actuated hybrid feed drive with application to machining,” IEEE/ASME Transaction on Mechatronics, 21(4), pp. 1822–1834. [PDF]
  6. Duan, M., and Okwudire, C. E., 2016, “Correction to ‘Energy-efficient controller design for a redundantly-actuated hybrid feed drive with application to machining,’” IEEE/ASME Transaction on Mechatronics, 21(6), pp. 2999–3000. [PDF]
  7. Okwudire, C., Ramani, K., and Duan, M., 2016, “A trajectory optimization method for improved tracking of motion commands using CNC machines that experience unwanted vibration,” CIRP Annals - Manufacturing Technolog, 65(1), pp. 373–376. [PDF]
  8. Duan, M., and Okwudire, C., 2016, “Minimum-time cornering for CNC machines using an optimal control method with NURBS parameterization,” International Journal of Advanced Manufacturing Technology, 85(5–8), pp. 1405–1418. [PDF]


  1. Ramani, K. S., Duan, M., Okwudire, C. E., and Ulsoy, A. G., 2018, “A lifted domain-based metric for performance evaluation of LTI and LTV discrete-time tracking controllers,” American Control Conference, Milwaukee, WI, USA. (Submitted)
  2. Duan, M., and Okwudire, C. E., 2017, “Proxy-based energy optimal dynamic control allocation for multi-input, multi-output over-actuated systems,” ASME Dynamic Systems and Control Conference, Tyson, VA, USA. [PDF]
  3. Yoon, D., Duan, M., and Okwudire, C. E., 2017, “Software-based compensation of vibration-induced errors of a commercial desktop 3D printer,” 6th International Conference on Virtual Machining Process Technology, Montréal, Canada. [PDF]
  4. Lin, B., Duan, M., Okwudire, C. E., and Wou, J. S., 2017, “A simplified analytical model of rolling/sliding behavior and friction in four-point-contact ball bearings and screws,” ASME International Mechanical Engineering Congress and Exposition, Tampa, FL, USA. [PDF]
  5. Duan, M., and Okwudire, C. E., 2016, “Modeling and observer-based compensation of slip in a friction drive for servo positioning,” International Symposium on Flexible Automation, Cleveland, OH, USA. [PDF]
  6. Duan, M., and Okwudire, C. E., 2016, “Near energy optimal control allocation for dual-input over-actuated systems,” ASME Dynamic Systems and Control Conference, Minneapolis, MN, USA. [PDF]
  7. Duan, M., Ramani, K. S., and Okwudire, C. E., 2015, “Tracking control of non-minimum phase systems using filtered basis functions: a NURBS-based approach,” ASME Dynamic Systems and Control Conference, Columbus, OH, USA. [PDF]
  8. Duan, M., and Okwudire, C. E., 2015, “Energy efficiency and performance optimized control of a hybrid feed drive,” ASME International Manufacturing Science and Engineering Conference, Charlotte, NC, USA. [PDF]
  9. Duan, M., and Okwudire, C. E., 2014, “Minimum-time cornering for manufacturing machines using optimal control,” ASME Dynamic Systems and Control Conference, San Antonio, TX, USA. [PDF]


  1. Duan, M., Okwudire, C. E., and Ramani, K. S. Use of filtered basis splines to compensate servo-induced motion errors. Patent Filing # PCT/US2016/044491. Filed July 28, 2016. (Pending).


  • Bachelor of Science
    Peking University, Beijing

    Theoretical and Applied Mechanics

  • Master of Science
    University of Michigan, Ann Arbor

    Mechatronics and Control

  • Doctor of Philosophy (expected)
    University of Michigan, Ann Arbor

    Mechatronics and Control


Tennis, soccer, piano