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As a new power electronic equipment, energy routers (ERs) can realize the flexible distribution of electric energy in power systems. It is of great significance to analyze the influence of energy routers on the system and study the power flow calculation methods of AC-DC hybrid distribution networks with ERs as the distribution hub. In this paper, the steady state power flow model of ERs is established based on the improved alternating iteration method, and the droop control strategy is adopted for the DC port of the ERs. Combined with the traditional decoupling method, an AC-DC decoupling iterative power flow calculation method suitable for the power distribution network containing ERs is proposed. An IEEE 14-node and IEEE 69-node system with multiple ERs are used as examples to verify the correctness and convergence of the proposed method. In order to analyze the influence of ERs on the system operation, the simulation calculation of IEEE 69-node test system in different scenarios proves that ERs can support the node voltage in the system and reduce the system operation loss.

A decoupled model predictive control (MPC) power balancing strategy for a coupled inductor-based flying capacitor DC–DC converter (FCDC) is a proposed to solve the power imbalance caused by the parameter differences in the coupled inductor. The decoupled mathematical model of coupled inductor FCDC is firstly derived by analyzing the converter operation state under various modes. On this basis, the control relationship between inductor current and flying capacitor (FC) voltage is redefined and an MPC power balance strategy based on the inductor current with single-step optimization is proposed. The proposed MPC strategy not only achieves decoupled power balancing control but also solves multi-objective dynamic optimization control of the inductor current and FC voltage, greatly reducing the computation load. A detailed theoretical analysis of the proposed strategy is presented and the balancing performance is effectively verified through the experiments. [ABSTRACT FROM AUTHOR]

Unlike cells or embryos, zebrafish have a complex physiological structure, which poses challenges to posture recognition and adjustment during microinjection. Furthermore, zebrafish surface pigments exhibit strong interference with visual servo-based injection control, thus, affecting the success of microinjection and the subsequent survival rate. To address these challenges, we developed an automated microinjection system for the zebrafish heart that has advantages of high accuracy and success rate and avoids biological sample contamination. A convolutional neural networks (CNN) deep learning model is employed to determine the body axis posture. To solve the problems of blocked needle and abnormal tip positioning induced by zebrafish surface pigment during the injection process, an adaptive robust Kalman filter is proposed to suppress the abnormal values of visual feedback. Experimental results show that the success rate of body axis recognition based on the employed deep learning model exceeds 95%, and the proposed adaptive Kalman filter effectively suppresses the visual outliers, satisfying the requirements of high-precision injection for the zebrafish heart. [ABSTRACT FROM AUTHOR]

This paper proposes an improved SOC balancing strategy for the modular energy storage system (ESS) based on low bandwidth communication (LBC) technology, aiming at solving the drawbacks of the conventional balancing strategy based on droop control. The proposed control scheme can improve the SOC balancing efficiency and remove the current deviation by using the SOC slope-adjusting and current-shifting approaches simultaneously. The average value of SOC can be derived through the LBC line, and the droop coefficient based on SOC can be controlled in the local control layer. Thus, the SOC of each sub-module can converge to the average SOC value in system dynamic process, and the balancing speed under the condition of low SOC difference between sub-modules can be improved. Furthermore, the current regulation performance in steady and transient states can be enhanced by using the proposed method. At last the effectiveness of the proposed strategy is verified by experimental results. [ABSTRACT FROM AUTHOR]

In order to reduce the chattering and phase shift, this article proposes an enhanced sliding mode observer (SMO) for the sensorless control of permanent magnet synchronous motor (PMSM). In the conventional SMO, a low-pass filter (LPF) is commonly employed to extract the back electromotive forces (EMFs) from the sliding mode switching function, which brings the phase shift and degrades the precision of position and speed estimations. In this article, a frequency-adaptive complex-coefficient filter (FACCF) is adopted to replace the LPF. Since the FACCF has no phase shift and amplitude attenuation at the central frequency, it can be used to extract the EMFs without distortion while the chattering can also be suppressed. For an easy parameter design, the normalized phase-locked loop is used to obtain accurately the position and speed estimations. The experiments are carried out on a 3-kW PMSM drive, and the results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents an active state-of-charge (SOC) balancing control strategy for modular super capacitor energy storage system (ESS). The strategy has a master–slave structure, including a common dc bus voltage loop and individual slave current loop for each submodule. The common voltage loop ensures the ability of the system to stabilize dc bus voltage cannot be affected by SOC balancing control, and provides a same original current reference for all submodules. SOC information is introduced into current loops to achieve SOC balancing control. The highest SOC is taken as a reference for low SOC modules, thus, the low SOC modules can regulate the submodule average operation current according to the SOC reference and their own SOC. In order to minimize system current deviation caused by the introduction of SOC, a current correction method is proposed to improve system current regulate performance. The proposed strategy can achieve SOC balancing control during ESS charging and discharging process dynamically, in addition, the modularity of the system is improved and the proposed strategy has favorable stability. A modular ESS prototype consisting of three half-bridge submodules is tested in the laboratory, and the experimental results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This letter presents a fast open circuit diagnostic method for modular multilevel DC/DC converter (MMDDC), which is applied in super capacitor energy storage system. The proposed method is derived based on the analysis of submodule output characteristics under both normal and fault conditions. For MMDDC, different types of open circuit fault are reflected by the output voltage of submodule in certain operating modes, thus a simple and effective diagnostic method by the aid of a hardware circuit and a fast fault location algorithm is proposed. The hardware circuit is responsible for detecting submodule output voltage and its output result is transmitted to a processor to accomplish the final fault diagnosis along with drive signals. The proposed approach avoids complex mathematical operations and minimizes fault diagnostic time; moreover, it can achieve fault diagnosis under a wide super capacitor operating voltage range. Finally, the proposed diagnostic method is verified experimentally based on a laboratory-scale MMDDC energy storage prototype. [ABSTRACT FROM AUTHOR]

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  μ m, and the root mean square error is less than 17  μ m 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., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this article., (Copyright © 2022 Jiawei Lu et al.)