Alkaline water electrolyzers (AWEs) are widely utilized in the field of industrial electrolysis due to their low cost, simple structure, and mature technology. However, the low-load inefficiency of AWEs hinders the ability to effectively follow the fluctuating renewable energy in full range. Focusing on this issue, this paper reveals the electrolysis mechanism from the perspective of the distribution of the electric field. Moreover, an optimal power pulse-width modulation (OP-PWM) strategy is proposed to reconstruct the electric field under the low load state. Experimental results show that the OP-PWM strategy can greatly improve low-load electrolysis efficiency compared to the conventional dc power electrolysis mode.

The DC microgrid is connected to the AC utility by parallel bidirectional power converters (BPCs) to import/export large power, whose control directly affects the performance of the grid-connected DC microgrid. Much work has focused on the hierarchical control of the DC, AC, and hybrid microgrids, but little has considered the hierarchical control of multiple parallel BPCs that directly connect the DC microgrid to the AC utility. In this paper, we propose a hierarchical control for parallel BPCs of a grid-connected DC microgrid. To suppress the potential zero-sequence circulating current in the AC side among the parallel BPCs and realize feedback linearization of the voltage control, a d - q -0 control scheme instead of a conventional d - q control scheme is proposed in the inner current loop, and the square of the DC voltage is adopted in the inner voltage loop. DC side droop control is applied to realize DC current sharing among multiple BPCs at the primary control level, and this induces DC bus voltage deviation. The quantified relationship between the current sharing error and DC voltage deviation is derived, indicating that there is a trade-off between the DC voltage deviation and current sharing error. To eliminate the current sharing error and DC voltage deviation simultaneously, slope-adjusting and voltage-shifting approaches are adopted at the secondary control level. The proposed tertiary control realizes precise active and reactive power exchange through parallel BPCs for economical operation. The proposed hierarchical control is applied for parallel BPCs of a grid-connected DC microgrid and can operate coordinately with the control for controllable/uncontrollable distributional generation. The effectiveness of the proposed control method is verified by corresponding simulation tests based on Matlab/Simulink, and the performance of the hierarchical control is evaluated for practical applications.

The DC microgrid is connected to the utility by parallel bidirectional power converters (BPCs) to realize power exchange. This paper proposes a decentralized control method for BPCs of a grid-connected DC microgrid. The proposed control method consists of two parts, that is, the inner loop and the outer loop, and improves the performance of the system from the following three aspects. First, a d-q-0 three axis control strategy instead of the conventional d-q two axis control strategy is adopted to suppress the circulating current in the AC side generated by the parallel BPCs. Second, a feedback linearization control strategy based on the square of the DC voltage is adopted for the DC voltage control, which can make the control of the DC voltage linear and decoupled. Third, the decentralized DC droop control is adopted to realize the DC current sharing among the BPCs and to make the BPCs provide voltage support for the DC microgrid in coordination. The simulation confirms the effectiveness of the proposed control method.

The rapid development of distributed generation (DG) has deeply transferred the power utilization style. Microgrid is developed for better absorption of distributed generation and has been researched in recent years. Interruptible load (IL) is another method to absorb the randomness and waviness of wind and solar energy, and is considered in this paper for more reliable and efficient deployment of DGs and storage in microgrid. A multi-objective optimization model is proposed for microgrid power sources construction with distributed generation, storage and interruptible load. Objectives of the model are economic cost, environmental cost and annual interruption duration. The model is solved by employing improved NSGA-II with the input of temperature, light intensity, wind speed, and load curve. The case study shows that the Pareto optimal front which covers the optimal solutions under different circumstances is effectively obtained. Thus the supervisor can select the final scheme with full consideration of different objectives. The impacts of IL on economic and environmental cost are also analyzed and demonstrated with many aspects.

Conventional proportional-resonant controller is widely accepted and adopted in micro-grid applications. However, it's hard to design a satisfactory conventional proportion-resonant controller due to the contradictory nature of the inverter's stability, dynamic response speed and static tracking accuracy. Therefore, some trade-off strategies proposed in previous works are usually favored. This paper proposes a novel fuzzy proportional-resonant control strategy for a three-phase inverter, which can obtain better outcomes of three contradictory performance characteristics simultaneously. The detailed mathematical models and design procedure of the controller for the studied inverter are also presented. Compared with conventional proportional-resonant control strategy, the superiority of the proposed fuzzy proportional-resonant control strategy is significant for its better system stability, faster dynamic response speed and higher static tracking accuracy. Results from simulation are provided to verify the feasibility and effectiveness of the proposed approach.

In view of the high energy consumption and low response speed of the traditional hydraulic system for an injection molding machine, a servo motor driven constant pump hydraulic system is designed for a precision injection molding process, which uses a servo motor, a constant pump, and a pressure sensor, instead of a common motor, a constant pump, a pressure proportion valve, and a flow proportion valve. A model predictive control strategy based on neurodynamic optimization is proposed to control this new hydraulic system in the injection molding process. Simulation results showed that this control method has good control precision and quick response.

A varied weights (VW) method is proposed in this paper for the kinematic control of redundant manipulators with multiple constraints. A weight factor rule to reflect the transition of the state of constraint subtask between activeness and inactiveness is presented. Each constraint has a VW factor in such a way that every time only the main task and the active constraint subtasks are considered. A new concept of effective singular value is presented for the design of damping factors to avoid the pseudosingularity arising from the transition of weight factors. The experiments on the seven-degree-of-freedom (7-DOF) Ping-Pong manipulator illustrate the efficacy of the proposed VW method.

This paper proposed a task function method for the point-to-point (PTP) control problem of non-redundant robot manipulators. A task function to compress the conventional task space to a new one with lower dimensions increases the redundancy degree so that the original manipulator becomes a redundant one, such that we can apply redundant control laws to achieve online subtasks, such as obstacle avoidance without trajectory replanning. The four basic properties of the task function method which are necessary to ensure the good performance of the PTP control problem are presented. The experiment results verify the effectiveness of the presented method.

We describe a new tracking and predicting scheme applied to a lab-made ping pong robot. The robot has a monocular vision system comprised of a camera and a light. We propose an optimized strategy to calibrate the light center using the least square method. An ellipse fitting method is used to precisely locate the center of ball and shadow on the captured image. After the triangulation of the ball position in the world coordinates, a tracking algorithm based on a Kalman filter outputs an accurate estimation of the flight states including the ball position and velocity. Furthermore, a neural network model is constructed and trained to predict the following flight path. Experimental results show that this scheme can achieve a good predicting precision and success rate of striking an incoming ball. The robot can achieve a success rate of about 80% to return a flight ball of 5 m/s to the opposite court.

This paper presents the general-weighted least-norm (GWLN) method for the control of redundant manipulators by a new concept of virtual joints, which consist of the performance function of subtasks. The GWLN method enables the redundant manipulator to perform multiple subtasks with the assumption that all the subtasks can be represented by the inequalities as the joint limits avoidance subtask. The number of subtasks to be coped with might be even larger than the number of joints if they do not happen simultaneously. The simulations in contrast to the traditional gradient projection method (GPM) and the recent directional GPM have been made to manifest the advantages of the proposed method. An experiment on the seven-degree-of-freedom redundant manipulator illustrates the good performance for tracking a given trajectory of end-effector position, while both guaranteeing the obstacle free and not violating the joint limits.