Search

Estimating contact force for a robot manipulator without an force/torque (F/T) sensor poses challenges due to uncertain torques, such as backlash and flexibility. To address this limitation, this article proposes a data-driven uncertain torque model and an overall gray-box structured approach. The contributions of this article are threefold. First, a joint domain unified neural networks (DUNNs)-based model is proposed to compensate for the uncertain torques. This model effectively captures uncertain torques beyond studies focusing solely on individual uncertainty. Second, the DUNNs model receives dynamic and joint domain information, enabling a single DUNNs model to estimate all joint uncertain torques through joint domain knowledge. This approach reduces the model size while maintaining performance. Third, the structure in which the DUNNs model works with conventional static friction models is introduced. This structure improves contact force estimation performance and enhances robustness against untrained data compared with the black-box model. Experimental results verify the method's effectiveness.

This article presents a modulation method for the series-resonant dual-active half-bridge (SR-DAHB) converter. The proposed method employs four control degrees of freedom: primary- and secondary-side duty ratios, voltage phase shift angle, and switching frequency. The proposed modulation method minimizes the rms current of the resonant tank while achieving complete zero-voltage switching of all primary and secondary switches for all operational ranges. Time-domain analysis of the SR-DAHB converter, which takes into account every harmonic, has been performed to obtain control value sets. Accurate steady-state values, such as half-bridge inverter switching current/voltage, output current, and rms current of the resonant tank, are derived in closed-form expressions. The derived expressions are utilized in numerical optimization algorithms to calculate optimal control value sets. Since closed-form equations are used, the computational burden of the numerical solver is relieved. The effectiveness of the proposed modulation method is verified through simulations and experiments on a 9.0 kW, 600 V full-SiC converter prototype. Compared to existing modulation methods, it is advantageous when primary- and secondary-side dc-link voltages have a large voltage difference. Particularly, in 0.25 voltage conversion ratio operation, the proposed modulation method presents an efficiency boost of up to 2% compared to the existing modulation methods.

This article presents a single shunt current sensing drive method for ultralow inductance permanent magnet synchronous motors that can reliably reconstruct phase currents even at very low speeds. Single current shunt inverters using dc current measurement entail the problem of having dead zones where the phase currents cannot be reconstructed. Voltage injection at the switching frequency can be a solution to avoid this, but at the expense of the newly introduced current ripple. That current ripple is exacerbated in ultralow inductance motors and can cause drive failure, especially at low speeds. To rule out voltage injection, this article presents a drive scheme that combines sequential two-phase excitation with a dc current averaging method using an RC low-pass filter. This permits three-phase current reconstruction from the average of dc current measurements per half-switching period, regardless of the active vector duration. Experimental demonstrations in this article show that the proposed driving method allows reliable current reconstruction at both startup and low speed without a significant current ripple. The current reconstruction and dynamic control performance are demonstrated with both steady-state and transient experiments.

In vector-controlled drive systems, a position sensorless drive with a single current sensor (SD-SCS) is an attractive system due to the minimum number of sensors. However, when the saliency-based SD-SCS is applied, the position estimation accuracy is deteriorated due to the errors in the injected pulsewidth-modulated voltage and the reconstructed current. This article proposes a current-derivative-based sensorless control using a three active vector pulsewidth modulation (TAVPWM) to enhance the saliency-based SD-SCS. First, the TAVPWM scheme, which eliminates the current reconstruction dead zone in the low-modulation region, is adopted to improve the low-speed drive. Next, the derivatives of the phase currents are utilized and analyzed to minimize the position estimation error in the overall operating regions. Finally, the transition strategy with respect to the speed is proposed for the full-speed sensorless drive. Owing to the proposed method, the switching frequency increases up to 16 kHz and the audible noise is virtually eliminated in the saliency-based SD-SCS. Furthermore, the enhanced dynamic performance is verified by various experimental results.

Wireless power transfer (WPT) technology has become increasingly popular due to its ability to transmit energy without mechanical contact, making it suitable for various industrial fields. This article deals with an inductive power transfer system, which is driven with a single-switch inverter such as Class E in several megahertz or higher frequencies. One of main issues with such systems is that the output and efficiency are significantly affected by the relative position of transmitter and receiver coils. Many existing solutions require additional tunable components and driving circuits, leading to increased cost and complexity. This article provides a systematic optimization procedure of two-port impedance matching networks for wireless power transfer systems to achieve constant output power characteristics even with misalignment or air-gap variation. Since the system itself has a characteristic that is robust against misalignment, the need for any control and tunable component can be significantly reduced. The effectiveness of the proposed method is verified through a prototype of 6.78 MHz/60 W and experimental results.