This article elaborates a novel online full parameter estimation method for permanent magnet synchronous motors (PMSMs). Usually, only two parameters can be estimated using voltage functions in the d-q frame due to the problem of rank deficiency. The α-β frame possesses the inherent advantage that full motor parameters can be estimated using voltage functions during steady and transient states. An algorithm based on recursive least squares in the α-β frame is proposed to estimate full motor parameters, including stator resistance, $d$ -axis and $q$ -axis inductances, and flux linkage simultaneously. Simulation and experimental results on the PMSM drive system are presented to verify the effectiveness of the proposed algorithm. Compared with the method in the d-q frame, the superiority of the proposed method in terms of faster convergence rate, less computational cost, and high accuracy is demonstrated.

Conventional industrial robots are unable to guarantee the inherent safety when working together with humans due to the use of rigid components and the lack of force sensation. To enhance the safety of human-robot collaboration (HRC), the new collaborative robot skin (CoboSkin) with the features of softness, variable stiffness and sensitivity is designed and studied in this paper. The CoboSkin is composed of an array of inflatable units and sensing units. The sensing units made of soft porous materials are capable of measuring distributed contact force in a real-time manner. By leveraging the foaming process, the sensing units are interconnected with inflatable units fabricated by the elastomer of which the deformation is limited by the textile wrapped around it. Variation of stiffness is enabled by adjusting the internal air pressure supplied to inflatable units, thereby changing the sensitivity of the sensing units and reducing the peak impact force. Soft porous materials endowed the CoboSkin with increased sensitivity, minimal hysteresis, excellent cycling stability, and response time in the millisecond range, which enabled sensing feedback for controlling a robot arm at different levels of stiffness. Finally, the validation of the CoboSkin for safer HRC was conducted with a robot arm to detect an unintended collision, illustrating its potential application in robotics.

Permanent magnet synchronous machines (PMSMs) work with controllers and controller parameters affect the machine's voltages and currents and thus the diagnosis of stator winding fault. One such parameter is the current controller bandwidth that affects the harmonic content in these signals. In the literature, the 2nd harmonics in both dq-axis currents and voltages have been used for fault detection, and the main advantage is that inter-turn short-circuit (ITSC) winding fault with a few shorted turns, specially one turn, can be detected. One indicator that combines the fault information in voltages and currents is the instantaneous reactive power (IRP). However, it has been shown that IRP does not perform robustly with respect to current controller bandwidth. The main contribution of this work is that it proposes and validates a new mathematical function for ITSCs detection, Rayleigh quotient, which combines the fault information present in voltages and currents to make ITSCs detection robust to current controller bandwidth. The validations from both co-simulation and experiment show that the proposed method is robust to the bandwidth and can detect ITSC faults faster than IRP.

As a senile chronic, progressive and currently incurable disease, dementia has an enormous impact on society and life quality of the elderly. The development of teleoperation technology has changed the traditional way of care delivery and brought a variety of novel applications for dementia care. In this paper, a telerobotic system is presented which gives the caregivers the capability of assisting dementia elderly remotely. The proposed system is composed of a dual-arm collaborative robot (YuMi) and a wearable motion capture device. The communication architecture is achieved by the robot operation system (ROS). The position-orientation data of the operator’s hand are obtained and used to control the YuMi robot. Besides, a path-constrained mapping method is designed for motion trajectory tracking between the robot and the operator in the progress of teleoperation. Meanwhile, corresponding experiments are conducted to verify the performance of the trajectory tracking using the path-constrained mapping method. Results show that the position tracking deviation between the trajectory of the operator and the robot measured by dynamic time warping distance is 1.05 mm at the sampling frequency of 7.5 Hz. Moreover, the practicability of the proposed system was verified by teleoperating the YuMi robot to pick up a medicine bottle and further demonstrated by assisting an elderly woman in picking up a cup remotely. The proposed telerobotic system has potential utility for improving the life quality of dementia elderly and the care effect of their caregivers.

This paper presents a nonlinear hybrid field model to predict the open-circuit magnetic field distribution in surface-mounted permanent-magnet machines. It combines the complex permeance model (CPM) with the magnetic equivalent circuit (MEC). The saturation effect is accounted for in the CPM by considering the magnetic potential distribution on the stator bore, which is calculated by the MEC and can be transformed to the virtual current on the slot. The proposed model significantly improves the calculation accuracy for saturated machines, which is verified by the finite-element analysis and the experimental results.

This paper develops an improved hybrid field model (IHFM) to predict the on-load performance of interior permanent-magnet (IPM) motors considering both iron saturation and slotting effect. It combines the air-gap analytical model based on modified conformal mapping with the reluctance mesh method for stator and rotor. The reluctance mesh method can accurately predict the rotor saturation and tooth-tip saturation even their field distribution is complicated due to armature reaction. Besides, IHFM will significantly accelerate computation speed using analytical model for air-gap region while keeping high accuracy. The finite-element analysis and experimental results of flat-type and V-type IPM motors are demonstrated to verify the effectiveness of the proposed model.