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Research Papers

J. Dyn. Sys., Meas., Control. 2018;140(12):121001-121001-12. doi:10.1115/1.4040440.

Hybrid analog/digital control of bilateral teleoperation systems can lead to superior performance (transparency) while maintaining stability compared to pure analog or digital control methods. Such hybrid control is preferable over pure analog control, which is inflexible and not ideal for realizing complex teleoperation control algorithms, and pure digital control, which restricts teleoperation performance due to a well-known stability-imposed upper bound on the product of the digital controller's proportional gain and the sampling period. In this paper, a hybrid controller combining a Field programmable analog array (FPAA) based analog controller and a personal computer-based digital controller is compared in terms of performance and stability to its analog and digital counterparts. A stability analysis indicates that the addition of analog derivative term widens the range of teleoperation controls gains that satisfy the stability conditions, paving the way for improving the teleoperation performance. We also show how the hybrid controller leads to better teleoperation performance. To this end, we study the human's performance of a switch flipping task and a stiffness discrimination task in the teleoperation mode. In both tasks, the hybrid analog/digital controller allows the human operators to achieve the highest task success rates.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(12):121002-121002-15. doi:10.1115/1.4040463.

This paper presents, compares, and tests two robust model reference adaptive impedance controllers for a three degrees-of-freedom (3DOF) powered prosthesis/test robot. We first present a model for a combined system that includes a test robot and a transfemoral prosthetic leg. We design these two controllers, so the error trajectories of the system converge to a boundary layer and the controllers show robustness to ground reaction forces (GRFs) as nonparametric uncertainties and also handle model parameter uncertainties. We prove the stability of the closed-loop systems for both controllers for the prosthesis/test robot in the case of nonscalar boundary layer trajectories using Lyapunov stability theory and Barbalat's lemma. We design the controllers to imitate the biomechanical properties of able-bodied walking and to provide smooth gait. We finally present simulation results to confirm the efficacy of the controllers for both nominal and off-nominal system model parameters. We achieve good tracking of joint displacements and velocities, and reasonable control and GRF magnitudes for both controllers. We also compare performance of the controllers in terms of tracking, control effort, and parameter estimation for both nominal and off-nominal model parameters.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(12):121003-121003-6. doi:10.1115/1.4040504.

This paper explains the control scheme that is to be used in the magnetic suspension mass comparator (MSMC), an instrument designed to directly compare mass artifacts in air to those in vacuum, at the United States National Institute of Standards and Technology. More specifically, the control system is used to apply a magnetic force between two chambers to magnetically suspend the mass artifacts, which allows for a direct comparison (i.e., a calibration) between the mass held in air and a mass held in vacuum. Previous control efforts that have been demonstrated on a proof-of-concept (POC) of this system utilized proportional-integral-derivative (PID)-based control with measurements of the magnetic field as the control signal. Here, we implement state-feedback control using a laser interferometric displacement measurement with a noise floor of approximately 5 nm (root-mean-square). One of the unique features and main challenges in this system is that, in order to achieve the necessary accuracy (relative uncertainty of 20 × 10−9 in the MSMC), the magnetic suspension must not impose appreciable lateral forces or moments. Therefore, in this design, a single magnetic actuator is used to generate a suspension force in the vertical direction, while gravity and the symmetry of the magnetic field provide the lateral restoring forces. The combined optical measurement and state-feedback control strategy presented here demonstrate an improvement over the previously reported results with magnetic field measurements and a PID-based control scheme.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2018;140(12):124501-124501-8. doi:10.1115/1.4040443.

In the current era of miniaturization for complex, ubiquitous, and energy efficient systems, micromanufacturing had become one of the most popular fields for engineering development. This paper introduces a modular robust cross-coupled controller design structure applied to a three axis micromachining system that can be extended to more axis systems and configurations. In order to develop a robust controller that can withstand the disturbances due to tool–workpiece interactions, a dynamic model of the whole system is needed. Developing control-oriented models for micromachining systems can be challenging. Using the sum of sines identification input, essential nonlinearities including the effects of assembly and slider orientation are included. Verification data show that these transfer function models represent the physical system satisfactorily while avoiding an over-fit. Using the transfer functions from the identified model, a controller structure with robust axis controllers with cross-coupled control (CCC) are developed and fine-tuned with simulations. Machining experiments are also done in order to compare the performance of the proportional-integral-derivative control design, an adaptive robust controller (ARC, both from earlier work in the literature) and the new H robust controller. According to results of experiments, the new robust controller showed the best tracking and contouring performance with improved surface quality due to reduced oscillations.

Commentary by Dr. Valentin Fuster

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