Measurement and Control

Li, Duo; Wang, Xu; Wang, Juan; Zhou, Zhenxiong

doi: 10.1177/00202940231194108pmid: N/A

The use of maximum power point tracking (MPPT) technology has significantly increased the conversion efficiency of PV modules. However, the presence of partial shading in PV arrays can lead to multi-peaked output curves, which traditional MPPT methods struggle to track due to falling into local maximum power points. The paper proposes a MPPT control algorithm based on the combination of differential flat control (DFBC) and adaptive particle swarm optimization (APSO) algorithm. The PSO output value is used as the feed-forward feedback input of differential flat, and a second-order controller is used to track the reference flat trajectory, achieving global MPPT through differential flat control. The algorithm can overcome the system oscillation caused by the randomness of the PSO algorithm with the initialized particle position and the existence of control lag misjudgment. Simulation and experimental results show that the algorithm not only solves the problem that the traditional MPPT algorithm cannot find the global maximum power point, but also solves the problems that the traditional particle swarm algorithm has large randomness, slow convergence speed, and easy to produce large oscillations. The algorithm has greatly improved the tracking accuracy, tracking speed and response speed, realizing fast and accurate response to external changes, reducing energy loss, and improving the dynamic tracking performance of the system.

Duan, Zhijie; Sun, Chungeng; Li, Jipeng; Tan, Yin

doi: 10.1177/00202940231194115pmid: N/A

According to the unstable and nonlinear performances of the servo valve-controlled hydraulic motor, classical control methods based on linear theory are gradually unable to meet the high-performance requirements of the system. Using the servo valve-controlled hydraulic motor based on the third-order active disturbance rejection control (ADRC) to improve the dynamic performance of the system is feasible. The mathematical model and the simulation model of the third-order ADRC for the servo valve-controlled hydraulic motor system are established respectively. For the phase lag caused by the third-order ADRC controller, the control performance of the ADRC controller is significantly improved using the advance forecast. The simulation experiment results show that the designed ADRC controller has good tracking performance and stronger robustness of the system than the traditional PID controller.

Zhang, Jianjun; Han, Pengyang; Liu, Qunpo; Li, Shasha; Li, Bin

doi: 10.1177/00202940231194116pmid: N/A

The underwater tactile force measurement was prone to cross-sensitivity, causing the difficulty in distinguishing tactile force signal with the underwater complex environment of water pressure influence. For this problem, an underwater tactile force sensor whose sensing core was based on Microelectromechanical Systems (MEMS) was designed with differential pressure typed structure. The hollow hemispherical flexible contacts located at the upper and lower end, and the hollow cylindrical shell in the middle part composed the structure of the capsule-shaped sensor. The upper flexible contact could sense the compound signal composed of water pressure and tactile force, at the same time, the lower flexible contact could measure the water pressure information. The deformation signal of the upper and lower flexible contacts could be transformed to the force sensor core’s upper and lower surfaces with silicon oil filled in the inner hollow part of the sensor. The tactile force signal could be obtained with water pressure eliminated through vector superposition method under the influence of static pressure of water. The structure and manufacture technology were introduced, and the Backpropagation (BP) neural network data regression algorithm was designed for the cross sensitivity. The experiments are conducted to demonstrate the effectiveness of the differential pressure structure in eliminating the influence of water static pressure. The results indicated that the BP neural network data regression algorithm successfully produced real tactile force signals, which is highly beneficial for the intelligent operation of underwater dexterous hand. Additionally, the sensor has an accuracy of 5%.

Yang, Duo; Fu, Hanwen; Li, Junjun; Wang, Siyu

doi: 10.1177/00202940231195129pmid: N/A

The proton exchange membrane fuel cell gas control has been one key point in fuel cell management systems. The complexity and coupling of the air management system make it difficult to achieve precise air intake adjustment. In this paper, an accurate joint control method for the air flow and pressure regulation is proposed. The nonlinear mathematical model of the air management system is developed to describe the output characteristic and state change. Based on this, the feedback linearization method is proposed to obtain the direct correspondence between control variables and controlled variables. In addition, to solve the problem that the controlled variables cannot be measured directly, an extended state observer is applied to estimate the stack cathode pressure. The sliding mode predictive control method is proposed to control the oxygen excess ratio and cathode pressure simultaneously. The relative order of the system is used to design the sliding mode surface, and the corresponding predictive model is proposed. The results obtained by simulation experiments show that pressure and mass flow have little effect on each other through decoupling. The proposed algorithm has been verified to have high precision, fast response, and robustness through comparative experiments.

Wu, Jianfan; Xie, Zhengyu; Qin, Yong; Jia, Limin; Guan, Ling

doi: 10.1177/00202940231187922pmid: N/A

The normal operation of a integrated hub station is of great significance for the safe operation of the entire city’s transportation network. Accurately monitoring the passenger flow operation status of the station is the fundamental basis for achieving scientific management and control of passenger flow. In response to the urgent need for accurate and real-time detection of passenger flow in station passageways, a Yolov7-based improved Deep-Sort algorithm is proposed to detect and track bi-directional passenger flow in the passageways of integrated hub stations. Based on the Yolov7 detection algorithm, the SimAM attention mechanism was introduced to improve the accuracy of detecting passenger flow in the passageways. On the basis of the Deep-Sort tracking algorithm, the Kalman Filter (KF) method was optimized to make the tracking box of the target more accurate. Meanwhile, the Fast-ReID method was used to improve the long-term tracking of targets, thereby improving the value of IDF1. This algorithm can help to achieve real-time and accurate detection and tracking of bi-directional passenger flow in station passageways. In the event of an abnormal situation, the station staff can react rapidly to improve the station’s operational safety.

Mohankumar, Rajamani-Selvaraj; Selvaganesan, Narayanasamy; Jayakumar, Madhavanpillai; Sathishkumar, Perumal

doi: 10.1177/00202940231193000pmid: N/A

Design of centralised disturbance rejection controllers for an highly interacting MIMO quadruple tank process is tedious. Recently, centralised disturbance rejection Fractional Order LQI (FOLQI) controller is designed for such system to meet the desired specifications with better performance than various disturbance rejection controllers that are available in the literature. In this paper, an optimisation problem is formulated to obtain the optimal parameters of FOLQI controller providing minimum control effort by applying various widely used heuristic methods like Cuckoo Search (CS), Accelerated Particle Swarm Optimisation (APSO) and FireFly (FF) algorithms. A detailed simulation study is carried out to compare the performance of the FOLQI and Integer Order LQI (IOLQI) controllers obtained by these heuristic algorithms under disturbance and parameter uncertainty conditions. From the simulation study it is inferred that (i) FOLQI controller provides better time domain specifications % Mp, ts and J in comparison to IOLQI controllers and (ii) FF tuned FOLQI and IOLQI controllers provide better robustness characteristics compared to CS and APSO tuned controllers.

Liaqat, Marriam; Alsuwian, Turki; Amin, Arslan Ahmed; Adnan, Muhammad; Zulfiqar, Adil

doi: 10.1177/00202940231196193pmid: N/A

Multi-microgrids offer various benefits including the decreased overloading of a single microgrid, more options during faulty conditions, and more utilization of renewable energy resources. However, the implementation of a multi-microgrid brings the challenges such as power system complexity, interconnection issues, bidirectional power flow management, and power flow balancing. In the presence of these challenges, the power flow stability of the multi-microgrids is a challenging problem. In this context, this study evaluates a transient stability analysis model in multi-microgrids using solar photovoltaics, wind power, and a unified power flow controller (UPFC). UPFC offers a more robust power flow control strategy compared with other flexible alternating current transmission systems (FACTS) devices. First, a multi-microgrid structure consisting of the two microgrids was designed in DIgSILENT PowerFactory software. Second, the load flow calculation was performed in the absence and presence of UPFC, short circuit fault, and grid connection. Third, the electromagnetic transients (EMT) simulation was performed for all these situations. The results exhibited that the UPFC would offer significant power flow stability in the multi-microgrids. It was observed that the UPFC resulted in more transient stability in the microgrid where it was located. However, it improved the power flow quality at all the locations in the multi-microgrids. In addition, UPFC offered significant transient stability during the fault occurrence. The results offer various insights into power flow management in multi-microgrids.

Benbouhenni, Habib; Bizon, Nicu; Thounthong, Phatiphat; Colak, Ilhami; Mungporn, Pongsiri

doi: 10.1177/00202940231195117pmid: N/A

This paper proposes a new integral-synergetic controller for direct reactive and active powers control (DARPC) for a grid-connected doubly-fed induction generators (DFIGs) in dual-rotor wind power generation applications. The proposed DARPC strategy employs integral-synergetic control (ISC) to regulate the reactive and active powers of the DFIG-based variable speed dual-rotor wind turbine systems. The proposed ISC technique is the contribution of this work, where this strategy is a development of synergetic control and simplicity and robustness are the most prominent features. The main advantages of the proposed ISC-DARPC technique are ease of implement, good dynamic response, simple structure, and constant switching frequency operation. The Matlab software is used to validate the design of the ISC-DARPC technique, and the obtained results are compared with traditional DARPC. In addition, the ISC-DARPC technique is able to fully minimize ripples in both torque and active power during grid voltage imbalance or parametric changes on the DFIG.