International Journal of Automation and Control (24 papers in press)

Regular Issues

• Decentralized Event Triggered Receding Horizon Online Charge Management of Electric Vehicles  
  by Maryam Amirabadi Farahani, Mohammad Haeri 
  Abstract: In this work, energy management of home customers with electric vehicles and renewable resources is modelled in the form of multi-agent systems. The agent decisions affect the others and the mean field game theory could provide a good solution for decision-making and control in multi-agent systems with a large number of agents. Due to uncertainties in the number of cars, power consumption, and production, online optimisation process is proposed by using the receding horizon concept of predictive control. The main problem in such processes is the calculations each agent should perform every hour. Hence, an event-based optimisation is employed to reduce the computational load. The main contribution of the present work is to optimise electric vehicles charging level in a decentralised and online manner in order to keep the load profile smoother in certain interval while reducing the computational complexity.
  Keywords: decentralised control; predictive control; electric vehicles charging; mean field game; computation load.
  DOI: 10.1504/IJAAC.2024.10061047
   
  
• Real-time order picking of a robotic put wall: A simulation-based metaheuristic optimization  
  by Jianbin Xin, Ziyuan Kang, Andrea D’Ariano, Lina Yao 
  Abstract: A robotic put wall has the potential to significantly enhance picking productivity in the logistics industry. This paper introduces a new computational method for scheduling a robotic put wall system that processes randomly arriving items. The method comprises a simulation-based model and a customized metaheuristic that optimizes performance at regular intervals. The simulation model is developed using advanced discrete-event software that can include operational details of the picking process. The genetic algorithm with a new encoding scheme is tailored to solve the combinatorial optimization problem of determining the appropriate destinations. To evaluate the proposed method, case studies based on real-world applications in a put wall manufacturing company were used. The method outperforms three rule-based real-time scheduling methods, as demonstrated by the results. Moreover, the integrated approach can determine the minimum number of vehicles required.
  Keywords: Order picking system; Robotic put wall; Real-time scheduling; Simulation-based optimization.
  DOI: 10.1504/IJAAC.2024.10061126
   
  
• Research on Autonomous Operation Method for Minimally Invasive Surgical Robot  
  by Longwang Yue 
  Abstract: Autonomous minimally invasive surgical (MIS) robot is an important research content of surgical robot. In order to improve the intelligent operation level of the MIS robot, the authors made the research on autonomous operation method for the MIS robot. The autonomous operation method includes the following four steps: recording the manual surgical operation, extracting the surgical information, constructing the autonomous operation strategy performing autonomous surgical operation. With the designed symmetrical cable-driven MIS robot, which can record and extract the manual surgical skills, an autonomous control strategy was constructed for the MIS robot based on the back-propagation (BP) neural network. The feasibility of the control method was verified with the symmetrical cable-driven MIS robot platform. The research of this paper can not only improve the intelligent level of MIS by realising autonomous operation of complex operations, such as suturing, knotting and so on, but also improve the safety of MIS, the quality and efficiency of surgery, and reduce the burden on doctors and patients.
  Keywords: minimally invasive surgical; MIS; autonomous operation; control strategy; motion trajectory.
  DOI: 10.1504/IJAAC.2024.10061191
   
  
• Design of Integral Sliding Mode Control with Performance Comparison for Uncertain TITO process  
  by Vijaykumar Biradar, Gajanan Malwatkar 
  Abstract: In this paper, integral sliding mode control (I-SMC) law is designed and discussed for the two-input two-output (TITO) process. In the first step, the TITO process has been decoupled using ideal decoupler and each of the decoupled subsystem is reduced into first-order-plus-delay-time model. The reduced FOPDT model of each of the decoupled subsystems is extensively used to obtain decentralised sliding reaching laws. The designed I-SMC is used in decentralised fashion with decoupler to achieve the regulation performance of the process. The presented decentralised PID is used for performance comparison, in addition to prevalent methods. In the modified PID method, a second order plus delay time model is obtained by analytical method and the parameters of single-input-single-output decentralised controllers are obtained using reduced SOPDT model. The performance I-SMC method is compared with decentralised PID controllers and other prevalent methods and seems to be suitable for TITO process applications.
  Keywords: integral sliding mode control; decoupler; decentralised PID controller; model reduction; performance comparison.
  DOI: 10.1504/IJAAC.2024.10061269
   
  
• Bio-Inspired Evasion Strategies under Variable Evader Speed  
  by Obiroy Singh Lairenjam, Devanathan Rajagopalan 
  Abstract: The Pursuit Evasion Game (PEG) is a widely observed phenomenon in nature that has implications for both civilian and military applications. While a general solution for PEG dynamics remains complex and elusive, researchers have developed kinematic, geometric, and other methods to analyse various scenarios where the pursuer captures the evader or the evader escapes. The dynamics of PEG under various bio-inspired strategies have been analysed due to their proximity to nature, and this has provided valuable insight into possible applications. Typically, studies assume constant speeds for both the pursuer and evader, with the pursuer chasing at a higher speed. However, this makes the problem more complex as it may result in less agile pursuit compared to the evader which is slower but more agile. This paper explores the trade-off between higher speed and less agility when the more natural assumption is made that the evader will increase its speed as the pursuer approaches. By simulating PEG trajectories, we can analyse the trade-off under varying evader speeds and determine the capture time of the evader by the pursuer.
  Keywords: Bio-inspired; Closed Loop Control; Differential Game Theory; Feedback Laws; Pursuit Evasion Game.
  DOI: 10.1504/IJAAC.2024.10061771
   
  
• Error-based ADRC Approach of lower Knee Exoskeleton System for Rehabilitation  
  by Nasir Alawad, Amjad Jaleel Humaidi, Ahmed Alaraji 
  Abstract: In this study, active disturbance rejection control (ADRC) has been designed to control exoskeleton system for rehabilitation at knee level and to replace the exercises made by physicians with systematic training device. The time derivative of reference input and feed-back signals is an evitable in most ADRC schemes. To alleviate the burden due to derivative actions, the idea of proposing error-based ADRC (EADRC) has been introduced. In conventional ADRC scheme, the extended state observer (ESO) is the core element of controller to estimate both the states of the system and the exerted disturbance. The EADRC utilises the estimates in the error sense rather than the actual states. The EADRC technique is compared to traditional ADRC and the numerical results showed that the proposed EADRC outperforms the conventional ADRC in terms of tracking errors, noise and load rejection capabilities for the system subjected to noise and load uncertainties.
  Keywords: Exoskeleton system; ADRC; robustness; stability; disturbance rejection.
  DOI: 10.1504/IJAAC.2025.10061844
   
  
• Earthwork Allocation Optimization Based on Cut-fill Matching and Transportation Path Planning  
  by Jing Yu, You Huang, Lining Xing, Zizhou Zhao, MingShun Li 
  Abstract: Earthwork allocation is a critical component of engineering construction projects, with the objective of reducing costs and shortening the construction period. While previous research has focused on solving the cut-fill matching problem, there is a lack of study on mechanical transportation path planning. This study introduces a matching model for cut-fill that minimises construction costs and mechanical transfer distance. Moreover, a hybrid ant colony-greedy model and algorithm are proposed to address the transportation path planning problem. To demonstrate the effectiveness of the model and algorithm, an earthwork allocation project is examined using the earthwork allocation model and its solution algorithm. Experimental results show that the two-stage allocation model and algorithm successfully address earthwork allocation challenges. Additionally, the AC-GA algorithm provides a superior earthwork allocation scheme.
  Keywords: earthwork allocation; cut-fill matching; path optimisation; linear programming; ant colony-greedy algorithm.
  DOI: 10.1504/IJAAC.2024.10062009
   
  
• Exploring Reinforcement Learning Techniques in the Realm of Mobile Robotics  
  by Zeeshan Haider, Muhammad Zeeshan Sardar, Ahmad Taher Azar, Saim Ahmed, Nashwa Ahmad Kamal 
  Abstract: Mobile robots are intelligent machines that can move and perform tasks in different environments. They have gained massive popularity across a variety of applications, including healthcare, agriculture, hospitality, exploration, surveillance, transportation, entertainment, and even military deployments. The key factor enabling the autonomy of mobile robots lies in the reliability, safety, and robustness of their navigation systems, without the need for human intervention. Achieving such a high level of autonomy has required extensive research and development efforts, encompassing both classical approaches and the latest advancements in artificial intelligence (AI) techniques. This review paper specifically focuses on the deep reinforcement learning (DRL) techniques employed for mobile robots. It provides a comprehensive look into the most significant DRL-based navigation and control algorithms for mobile robots. Sub-components of mobile robot navigation perception, mapping, localization, and motion planning are well delineated under the lens of DRL and conventional methods.
  Keywords: Mobile robots; deep reinforcement learning; navigation; control; path planning; machine learning.
  DOI: 10.1504/IJAAC.2024.10062261
   
  
• Contamination Detection in the Cultivation of Leukocyte Based on Image Sparsity Evaluation  
  by Lianghong Wu, Zhiyang Li, Liang Chen, Cili Zou, Hongqiang Zhang 
  Abstract: The contamination in the cultivation of cell seriously affects the reliability and reproducibility of experimental results. In this paper, it proposes a sparse matrix clustering (SMC) method based on the principle of matrix sparsity to automatically detect the contamination in leukocyte. Firstly, the image segmentation and local adaptive binarization techniques are used to eliminate the noise points and shadows. Then, a scoring map of image sparsity based on the pixel distribution of segmented images is proposed to index the pollution degree of the leukocyte. By dynamically determining the threshold for evaluating image sparsity based on the maximum distributed pixels on the scoring map, the image sparsity is used as a feature for classification. Experimental results show that this method achieves an accuracy of 98.8% for detecting contamination in leukocyte culture images with fast detection speed, which can be used as an efficient cell contamination detection approach in biomedical field.
  Keywords: Keywords: image sparsity evaluation; leukocyte contamination detection; image segmentation; local adaptive binarization.
  DOI: 10.1504/IJAAC.2025.10062262
   
  
• Modifier-adaptation-based RTO Scheme for Water Distribution Networks under Demand and Parametric Uncertainties  
  by Jaivik Mankad, Nitin Padhiyar, Balasubramaniam Natarajan, Babji Srinivasan 
  Abstract: The goal of pressure management in a water distribution network (WDN) is to avoid losses due to excessive pressure while meeting the minimum target pressure at nodes. Since nodal demands can fluctuate, real-time control of nodal pressures is critical for normal network operation. Optimising the operation of WDN using a model with uncertain parameters and unaccounted nodal demands generates solutions that are not truly optimal and may even be infeasible. This work aims to achieve real-time optimal operation of a WDN in the presence of various uncertainties. A modifier-adaptation (MA)-based real-time optimisation (RTO) strategy is used to drive the WDN to its optimal point. However, the MA-based RTO scheme assumes knowledge of key variables which may not be available in practice. Therefore, a Bayesian matrix completion approach for robust state estimation is used to impute unknown model parameters with limited measurements. Simulation results demonstrate the ability of this approach.
  Keywords: real-time optimisation; modifier-adaptation; plant-model mismatch; water distribution networks; uncertain demand; pressure control.
  DOI: 10.1504/IJAAC.2024.10062336
   
  
• Research on steelmaking-continuous casting cast batch planning based on improved surrogate absolute-value Lagrangian relaxation framework  
  by Congxin Li, Liangliang Sun 
  Abstract: Cast batch planning (CBP) is the bottleneck of batch planning in the steelmaking-continuous casting-hot rolling (SM-CC-HR) section. With the rapid development of the market-oriented demand of steel enterprises to multiple species, small batches, and on-time delivery, the batch planning integrated production process has dramatically increased the flexibility of the CBP as well as the functional requirements of the time dynamic balance. Therefore, it is of great significance to research the method of CBP to improve production efficiency and reduce material and energy consumption. In this paper, based on the improved surrogate absolute-value Lagrangian relaxation (ISAVLR) framework, the heuristic method based on a multiplier iteration strategy with controllable gradient direction combined with a local search (LS) algorithm is proposed. The 'zigzagging' problem in the traditional Lagrangian relaxation (LR) is overcome and the solution efficiency is improved while the original problem is provided with tighter lower bounds.
  Keywords: steelmaking-continuous casting; ISAVLR; improved surrogate absolute-value Lagrangian relaxation; CBP; cast batch planning; heuristic.
  DOI: 10.1504/IJAAC.2025.10062754
   
  
• Model predictive control with constraints based on PSO and fuzzy logic applied to the control of coupled longitudinal-lateral dynamics of the autonomous vehicle  
  by Rachid Alika, El Mehdi Mellouli, Tissir Elhoussaine 
  Abstract: In this paper, a strategy for controlling the longitudinal and lateral dynamics of an autonomous vehicle is developed. This strategy is based on the model predictive control (MPC) with constraints combined with LPV form. The three degrees of freedom (3DOF) model of the autonomous vehicle is used. The cornering stiffness is approximated by a fuzzy logic type Takagi-Sugeno, with the aim of finally approximating the nonlinear lateral forces. In order to improve the systems performance, constraints for controller inputs and also for systems outputs are defined. The MPC weights are determined using the particle swarm optimisation (PSO). The objective of this strategy is to follow the reference trajectory of the autonomous vehicle while reducing the lateral and longitudinal displacement error. The steering angle and the longitudinal acceleration are the control inputs, the outputs of this system are the longitudinal velocity, the yaw angle, the longitudinal and lateral displacement. The system is multi-input and multi-output (MIMO) and has non-linear dynamics. Simulation results show some improvements over the literature.
  Keywords: autonomous vehicles; MPC; model predictive control; MPC constraints; LPV system; PSO; particle swarm optimisation; MIMO system; nonlinear dynamic; path planning; fuzzy logic.
  DOI: 10.1504/IJAAC.2025.10062896
   
  
• FPGA-based performance evaluation of backstepping control and computed torque control for industrial robots  
  by Arezki Fekik, Hocine Khati, Ahmad Taher Azar, Mohamed Lamine Hamida, Hakim Denoun, Nashwa Ahmad Kamal 
  Abstract: In this paper, a comparative study is conducted on two nonlinear control techniques: state feedback control through backstepping and computed torque control. The study focuses on their application to the industrial robot PUMA 560. The primary goal is to assess the trajectory tracking accuracy and speed achieved by these methods. To achieve this objective, both control techniques are employed on the Zed board Zynq FPGA platform, encompassing both simulation and hardware systems. Subsequently, the experimental results are thoroughly analyzed and compared, aiming to accentuate the unique advantages and constraints associated with each method.
  Keywords: field-programmable gate array; FPGA; backstepping control; computed torque control; CTC; Zed board Zynq; PUMA 560.
  DOI: 10.1504/IJAAC.2025.10062960
   
  
• Kharitonov-Hurwitz analysis based robust decentralized PID controller for benchmark industrial processes using nonlinear constraint optimization  
  by K.R. Achu Govind, Subhasish Mahapatra, Soumya Ranjan Mahapatro 
  Abstract: The interconnected systems featuring a combination of interrelated variables present significant challenges in the control and stability aspects of industrial chemical processes. These systems demonstrate complex interactions, and time delays, contributing to sub-optimal performance. Traditional controllers struggle with variable interactions, resulting in poor disturbance rejection and imprecise tracking. To overcome these limitations, a robust decentralised proportional-integral-derivative (PID) controller is proposed, exploiting nonlinear constraint optimisation. The key objective is to enhance the robustness and performance of the PID controller through a comprehensive Kharitonov-Hurwitz analysis. The controller is formulated to minimise overshoot, meeting predefined design specifications. Validation of the proposed approach is conducted on benchmark industrial processes. Simulation results demonstrate its superior performance across various metrics, including settling time and overshoot, surpassing existing methodologies in the field. Rigorous assessments under multiplicative input uncertainty and stability evaluations using the Kharitonov-Hurwitz theorem validate the approach.
  Keywords: FOPDT System; Decentralized Control; PID; Robust control; Model Uncertainty.
  DOI: 10.1504/IJAAC.2024.10063220
   
  
• An improved information entropy for the integrated emergency-defence system capability evaluation  
  by Wei Shi, Shuai Deng, Shuanglin Li 
  Abstract: To evaluate the capability of an integrated emergency-defence system (IEDS), a dissipative structure model based on information entropy is established, which comprehensively considers the characteristics of IEDS and the relevant theory of information entropy. In this paper, we first provide a method to construct IED loop (IEDL) based on the theory of observation-direction-determination-action (OODA) to describe the relationships among the entities of IEDS. Secondly, in order to counter the uncertainty of the information exist in the IEDLs, an improved information entropy is proposed to measure the capability of IEDLs. After the capabilities of several IEDLs belonging to the IEDS network model are aggregated, the capability of the whole IEDS can be evaluated. The proposed capability evaluation method provides ideas and methods for analysing the gap in the capability between the actual and target and optimising the system architecture.
  Keywords: integration; emergency-defence system; information entropy; evaluation.
  DOI: 10.1504/IJAAC.2024.10056819
   
  
• Identification for control approach to data-driven model predictive control  
  by Yadollah Zakeri, Farid Sheikholeslam, Mohammad Haeri 
  Abstract: Data-driven model predictive control has become an attractive research subject in recent years. There are two main approaches to design data-driven model predictive control; direct methods in which controller is identified directly, and indirect ones where controller is designed based on an identified model of the plant. In this paper a new method for direct and offline identification of predictive controller is developed. Here, data-driven MPC design problem is reduced to basic model reference data-driven control problem which is more recognised, and can be analysed and designed by existing methods for LTI systems. The required tuning methods are adapted and four algorithms using modified correlation-based and virtual reference feedback tunings are developed. In comparison with other works, the proposed method can be used for both performance-oriented and model reference criteria, is direct, offline, and identifiable. Meanwhile, stability, and feasibility of the proposed algorithms can be guaranteed and certified using established analysis and synthesis methods for data-driven control.
  Keywords: data-driven control; direct data-driven control; data-driven model predictive control; identification for control.
  DOI: 10.1504/IJAAC.2024.10061447
   
  
• Force-impedance control of a 2-DOF planar robot using model predictive control based on successive linearisation of neural network model  
  by Daniel Chifisi, Ahmed Ali Abouelsoud, Karanja Kabini, Maina Martin Ruthandi 
  Abstract: This paper presents a position-based force-impedance controller for a class of robot manipulators. A multilayer perceptron (MLP) neural network (NN) based on the structure of a nonlinear autoregressive model with exogenous input (NARX) is used to accurately model the dynamics of the robot manipulator. Using the developed neural network-based prediction model, a position-tracking adaptive linear model predictive controller (MPC) is synthesised. The neural network model is trimmed and linearised successively about the reference trajectory in order to improve the performance. Finally, a force-impedance control loop is added to the position-tracking MPC to regulate the dynamic interaction between the end effector of the manipulator and the environment. The feasibility and effectiveness of the developed control scheme is verified through extensive simulation using a two degree of freedom (2-DOF) planar robot manipulator in MATLAB.
  Keywords: force-impedance control; model identification; model predictive control; neural networks; robot manipulator.
  DOI: 10.1504/IJAAC.2024.10058136
   
  
• Oct-TCN-based wind turbine generator failure fault prediction research  
  by Cheng Xiao, Qian Liu, Yubin Song, Botian Liu 
  Abstract: This paper is based on the study of machine side bearing temperature overrun faults in wind turbines. By analysing the characteristics of the data collected by the SCADA system, conventional data completion and deletion processes for missing data, outlier data and discrete anomalous data are carried out based on a priori knowledge. In order to reduce the memory and computation cost and to store and process spatial information at a lower spatial resolution, a combination of octave convolution (OctConv) and temporal convolutional network (TCN) is proposed. The sampling method is improved for the asymmetry of information that can be caused by the asymmetry of the OctConv upsampling and downsampling methods, and the Oct-TCN deep learning network is proposed. Application of Oct-TCN deep learning network algorithms to analyse wind turbine generator SCADA data with temporal characteristics is proposed. Based on the identification of fault feature variables, the fault prediction network is trained to make predictions. The system achieved a prediction accuracy of 98.65%.
  Keywords: wind turbine; machine side bearing temperature overrun fault; fault prediction; deep learning; Oct-TCN.
  DOI: 10.1504/IJAAC.2024.10058920
   
  
• Robust cascade controller design for discrete minimum phase system using a novel data-driven virtual reference feedback tuning approach  
  by Suresh Kumar Chiluka, Uday Bhaskar Babu Gara 
  Abstract: This work proposed a novel cascade controller design approach employing data-driven virtual reference feedback tuning (VRFT) to improve the performance and robustness. Selecting the closed-loop reference model [M(z)] is crucial in the conventional VRFT approach. Unlike the conventional VRFT method, the suggested approach has the distinctive property of using maximum sensitivity (M_s) as the design criterion for choosing the M(z), resulting in robust controllers. The proposed approach leads to improved closed-loop performance and stability. The proposed technique corroborates the standard series cascade (SSC) and modified series cascade (MSC) structures. Each structure's inner and outer loop controllers are designed by considering one and two reference models. Additionally, it clarifies the robustness and fragility with a perturbed plant and controller, respectively. The simulation results demonstrate enhanced robustness and overall performance attainment with the proposed approach.
  Keywords: virtual reference feedback tuning; VRFT; robust control; series cascade; fragility; minimum phase system; maximum sensitivity.
  DOI: 10.1504/IJAAC.2024.10061470
   
  
• An integral augmented sliding mode controller: the experimental application to level control plant  
  by Ajit Rambhau Laware, Bhagsen Jaggnath Parvat, Ravindra Rambhau Navthar 
  Abstract: It is well-known that servo and regulatory problems in industrial applications requires zero steady-state error. In the absence of an integral-action, uncontrolled systems give steady-state error to some extent or degraded performance under parametric uncertainties and bounded disturbances. Hence, real-time experimentation with integral augmented sliding mode control (IASMC) is adopted to enhance the closed-loop performance of level control plant. Lyapunov candidate function ensures the stability of a system. The practicability of IASMC is guaranteed with laboratory level control model. Experimental results obtained are compared with conventional sliding mode control (SMC) strategies reported by earlier researchers, and proportional-integral-derivative (PID) controller. An evaluation of experimental results with the assumption that nominal plant dynamics are known reveals that the proposed control design method provides a better set-point tracking performance, and fast and smooth level regulation in the presence of external bounded disturbances. It shows better time-domain specifications and error-based performance indices. The study shows that IASMC is applicable to industrial control systems and an alternate control strategy to prevalent design methods.
  Keywords: integral control; PID control; real-time experimentation; sliding mode control.
  DOI: 10.1504/IJAAC.2024.10058538
   
  
• Lyapunov exponent-based PID control for noisy chaotic systems  
  by Baghdadi Hamidouche, Kamel Guesmi, Najib Essounbouli 
  Abstract: This paper addresses the stabilisation issue of noisy chaotic systems. It proposes a new hybrid control approach that combines the proportional-integral-derivative (PID) method with the delayed feedback technique. The idea is to turn the structural stabilisation problem into an optimisation one. The goal is to determine the PID gains that give the lowest value of the largest-Lyapunov exponent. The difference between the system's current state and its delayed value, by one period, is used as the PID argument. As a result, the systems chaotic orbits are structurally stabilised to the greatest extent possible, the stable zone is extended, and the stabilisation time is reduced. Numerical simulations are carried out to show the effectiveness of the proposed approach on two well-known benchmarks of chaotic systems.
  Keywords: chaotic systems; delayed feedback control; optimisation; proportional-integral-derivative; PID; largest-Lyapunov exponent.
  DOI: 10.1504/IJAAC.2024.10058961
   
  
• Optimal control design for uncertain aerial manipulator system based on an adaptive approach  
  by Samah Riache, Madjid Kidouche, Mohamed Zinelabidine Doghmane, Kong Fah Tee 
  Abstract: In this paper, an optimal controller has been proposed for an aerial manipulator (AM) consisting of a quadrotor uncertain system with a two-degrees-of-freedom robotic arm. Wherein, the dynamics of this system have been derived based on Gauss's principle. The employment of this principal has permitted the pinpoint of the inner structure of the uncertain system and its possible moves. It has kept the AM in a very precise formation to analyse its dynamics and propose the suitable control. The proposed controller is designed using an adaptive approach of the non-singular terminal sliding mode technique. The main contribution is that the proposed approach guarantees both the good tracking of the desired trajectories in finite time and the chattering effect attenuation without overestimating the switching control gains. The design does not necessitate a priori knowledge of the upper limits of disturbances; the stability of the system has been established through the utilisation of Lyapunov theory. The simulation results have proved the effectiveness and robustness of the proposed optimal nonlinear terminal sliding mode technique for such an uncertain system in comparison to the sliding mode controller.
  Keywords: adaptive algorithm; chattering; quadrotor; sliding mode control; disturbances.
  DOI: 10.1504/IJAAC.2024.10059223
   
  
• A complete ultra-large wind turbine emulator for wind harvest evaluation: design and implementation  
  by Wael Farag, Mohamed Abouelela, Magdy Helal 
  Abstract: A comprehensive 5-MW wind turbine emulator's design and implementation are designed and investigated thoroughly in this paper. A separately excited DC motor set under the control of a current-controlled drive forms the basis of the suggested emulation. The emulation algorithms that simulate the features of the 5-MW wind turbine are run on a digital signal processor (DSP). These algorithms regulate the DC motor's current, which in turn regulates the torque. The results obtained demonstrate that the system was successful in accurately simulating the transient and steady-state characteristics of the 5-MW wind turbine. The emulator system was initially tested and validated with simulation results using MATLAB/Simulink code attached to both the FAST and TurbSim models. Furthermore, step and stochastic wind profiles were used to experimentally verify and test it. Nearly all of the power that is available in the wind turbine system is successfully obtained using the maximum power point tracking technique, which is used to find the best operating point. The created wind turbine emulator can be used to precisely assess energy harvesting by examining various mechanical and electrical properties of the permanent magnet synchronous generator (PMSG) vastly used in ultra-large wind turbine nacelles.
  Keywords: DC motor; digital signal processor; DSP; emulation; FAST; permanent magnet synchronous generator; PMSG; simulation; TurbSim; wind energy; wind turbine; wind harvest.
  DOI: 10.1504/IJAAC.2024.10059154
   
  
• Fully integrated LDO based on push-pull circuitry for enhanced power management in embedded systems  
  by Hatim Ameziane, Kamal Zared, Hicham Akhmal, Hassan Qjidaa 
  Abstract: We present a fully integrated analogue LDO voltage regulator with slew rate enhancement circuitry (SREC). The SREC is employed by implementing the push-pull current booster technique to ensure fast transient responses, which increases the rapidity of the LDO providing a high-accuracy output voltage of 1.6 V for a supply voltage of 1.8-2.5 V, without any increase in power consumption. However, the typical LDO architecture suffers from the speed-power tradeoff and a large output capacitor is inevitably required, which implies an excessively large chip area. The push-pull current booster technique not only solves the rapidity-power tradeoff and suppresses the need for an output capacitor, but also enables the LDO regulator to operate stably over all load conditions as well as achieving a quick settling time. The proposed SREC-LDO design and simulation is in a standard 180 nm TSMC CMOS process, achieving a good open loop stability; with 75° phase margin under full load current and ground current consumption of 10 μA. The regulation of the line and load are 0.017 mV/V and 0.003 mV/mA respectively with a 72 fs figure of merit (FOM).
  Keywords: low-dropout; LDO; system-on-chip; SoC; power management IC; PM-IC; slew-rate enhancement circuit; SREC; settling time.
  DOI: 10.1504/IJAAC.2024.10059407