Fault diagnosis is currently considered a crucial method to enhance the reliability of permanent magnet synchronous motor (PMSM) drives. In this article, an open-circuit fault (OCF) diagnosis method of a voltage source inverter-fed PMSM with model predictive control is proposed. The developed approach mainly consists of fault detection and localization. Besides, the normalized cost function variation is designed as a fault detection indicator according to the impact of OCFs on current signatures. It can not only monitor drive system conditions, but also discriminate fault categories. Afterward, the polarities of normalized αβ -current average values and phase angles of residual current vectors are utilized to locate the exact faulty switch in each fault type. Consequently, a total of 21 possible combinations of faulty switches can be correctly detected and located. Finally, the effectiveness in fault diagnoses and the robustness against operating point variations are verified by the experimental results.

In this letter, a hybrid model-based diagnosis method is proposed for open-switch faults in permanent magnet synchronous motor drives by combining the advantages of both model predictive control (MPC) and mixed logical dynamic (MLD) models. This idea is based on the receding optimization of the MPC and the estimating capability of the MLD. The predictive current model and the MLD model are established to predict and estimate phase currents, respectively. Besides, the logical vectors are theoretically investigated under various faulty conditions. Derived from the cost function, a diagnosis function is designed to evaluate the consistency between the actual and estimated currents. Consequently, the logical vector minimizing the diagnosis function is selected to locate faulty switches. Finally, experiments are conducted to verify the effectiveness of the proposed method.

Microrobots have great application potential in the biomedical field, to realize the precision and efficiency of microrobots in vivo is research focus in this field. Microrobots are accompanied by various disturbances in complex environment. These disturbances will affect the motion control of microrobots, resulting in the inability of the micromanipulation tasks to be completed effectively. To this end, a robust motion control method is proposed for precise path tracking of microrobots in this paper. The extended state observer (ESO) is used to estimate the total disturbances and uncertainties of the system. A path tracking controller is designed by combining sliding mode control (SMC) and disturbances compensation, which is used to eliminate the total disturbances of the system and realize the fast and accurate path tracking of microrobots. Finally, the path tracking experiments are implemented in the gradient magnetic field drive system. The experimental results show that the mean absolute error of the path tracking for microrobots in a simulated vascular structure is less than 14 μm, and the root mean square error is less than 17 μm by using the robust control method proposed in this paper. Compared with the traditional PID control method, it can better suppress external disturbances and uncertainties of the system and improve the path tracking accuracy of microrobots effectively. It shows stronger anti-interference ability and robustness.

This article proposes a cost function error-based approach to diagnose open-circuit faults (OCFs) in permanent magnet synchronous machine drives with model predictive current control. The intrinsic relations of motor currents and cost functions under fault conditions are investigated. The residuals of the dq -axis currents are utilized to detect the fault type associated with the number of faulty devices. Instead of deriving the explicit values of cost functions, an estimation model is built according to the analytical expressions of currents and the optimal voltage vector. The error between the estimated cost function and the actual one is analyzed for fault localization. The faulty switch is finally diagnosed by assessing the minimum average absolute value of the cost function error. Simulated and experimental results confirm that the developed approach can achieve a fast diagnosis of single and multiple OCFs with good robustness to the motor parameter and operating power variations.

Pedestrian dead reckoning (PDR) systems based on a microelectromechanical-inertial measurement unit (MEMS-IMU) providing advantages of full autonomy and strong anti-jamming performance are becoming a feasible choice for pedestrian indoor positioning. In order to realize the accurate positioning of pedestrians in a closed environment, an improved pedestrian dead reckoning algorithm, mainly including improved step estimation and heading estimation, is proposed in this paper. Firstly, the original signal is preprocessed using the wavelet denoising algorithm. Then, the multi-threshold method is proposed to ameliorate the step estimation algorithm. For heading estimation suffering from accumulated error and outliers, robust adaptive Kalman filter (RAKF) algorithm is proposed in this paper, and combined with complementary filter to improve positioning accuracy. Finally, an experimental platform with inertial sensors as the core is constructed. Experimental results show that positioning error is less than 2.5% of the total distance, which is ideal for accurate positioning of pedestrians in enclosed environment.

The independent control of microrobot swarms is a major challenge in the field of micro/nano manipulation. In this paper, a new localized magnetic field generating system is presented that can be used for the independent control of multiple magnetic microrobots. Such a system will allow for cooperative or parallel microassembly tasks with teams of magnetic microrobots. Firstly, the performance of the novel circular microcoil is modeled by analyzing the effect of input current to study the magnetic field distribution characteristics in the workspace, which is validated by finite element analysis and simulation; then, an actuation and control strategy of microrobots for microcoil array is proposed. Meanwhile, the independent closed-loop control of the microrobot is realized based on visual feedback; finally, an experimental platform for the microcoil actuation system is built to validate the newly designed structure. The results show that the microrobot can move flexibly and accurately with the tracking error within 0.444mm. At the same time, the system is capable of independently controlling multiple microrobots and holds great potential in performing micromanipulation tasks.