Forthcoming and Online First Articles

International Journal of Automation and Control

International Journal of Automation and Control (IJAAC)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Automation and Control (25 papers in press)

Regular Issues

  • An Integral Augmented Sliding Mode Controller: The Experimental Application to Level control plant   Order a copy of this article
    by Ajit Laware, Bhagsen J. Parvat, Ravindra R. Navthar 
    Abstract: It is well-known that servo and regulatory problems in industrial applications requires zero steady-state error. In absence of an integral-action, uncontrolled systems give steady-state error in 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 proposed control design method provides a better set-point tracking performance, fast and smooth level regulation in presence of external bounded disturbances. It shows better time-domain specifications nd 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   Order a copy of this article
    by Baghdadi HAMIDOUCHE, Guesmi Kamel, 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 (P ID) 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 P ID 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 P ID argument. As a result, the system’s 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; P ID; largest-Lyapunov exponent.
    DOI: 10.1504/IJAAC.2024.10058961
  • A Complete Ultra-Large Wind Turbine Emulator for Wind Harvest Evaluation: Design and Implementation   Order a copy of this article
    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.
    DOI: 10.1504/IJAAC.2024.10059154
  • Optimal control design for uncertain aerial manipulator system based on an adaptive approach   Order a copy of this article
    by Samah Riache, Madjid Kidouche, Mohamed 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
  • Fully Integrated LDO based on Push-pull Circuitry for Enhanced Power Management in Embedded Systems.   Order a copy of this article
    by Hatim Ameziane, Kamal Zared, Hicham Akhamal, Hassan Qjidaa 
    Abstract: We present a fully integrated analogue LDO voltage regulator with slew rate enhancement circuitry (SREC). The SREC 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 1.82.5 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
  • Decentralized Event Triggered Receding Horizon Online Charge Management of Electric Vehicles   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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
  • Identification between broken rotor bars and low-frequency load torque fluctuations in a three-phase induction motor   Order a copy of this article
    by Ranjan Sasti Charan Pal, Amiya Ranjan Mohanty 
    Abstract: Motor current signature analysis is an efficient methodology for fault diagnosis of induction motors. The appearance of broken rotor bars creates pole pass frequency (fPPF). Applied load torque creates low-frequency load torque fluctuations at frequency (fL), which tends to exist in the vicinity of fPPF. Hitherto, techniques have been proposed wherein synchronised monitoring of three-phase currents and three-phase voltages are measured by three current and three voltage sensors. This leads to a requirement for a data acquisition (DAQ) unit with at least six channels that make the overall system expensive and cumbersome in the field. However, in the present article, a new fault diagnostic approach has been proposed, which considers current data being monitored only from one single phase and thus requires only one single channel of DAQ that makes the overall system economical and portable for easy field deployment. The proposed analytical study has been verified with experimental results and finite element method.
    Keywords: broken rotor bars; BRBs; load torque fluctuations; motor current signature analysis; MCSA; three-phase induction motors.
    DOI: 10.1504/IJAAC.2024.10054887
  • Sliding mode control of a two-link flexible manipulator for reduced vibration in the presence of unmatched uncertainty and time-varying external disturbance   Order a copy of this article
    by Sanjay Thakur, Ranjit Kumar Barai 
    Abstract: Accurate positioning of the flexible links is a major challenge for a flexible link manipulator because of the presence of vibration, model uncertainty, and external disturbances. In this work a popular robust controller, i.e., sliding mode controller (SMC) has been developed for joint trajectory tracking and vibration reduction of the two-link flexible manipulator. Due to the payload's variability, which makes the issue even more challenging, the mass of the payload has been treated as uncertain. Proof of the matching condition of the uncertain parameter has also been provided. The system's dynamics have been modelled using the Assumed mode method. Closed-loop stability has been verified using the Lyapunov method. Lyapunov-based controller (LBC) has also been developed for comparison purposes. Payload has been varied to show the effectiveness of the developed controller. The simulation results have exhibited better performance of the SMC over the LBC.
    Keywords: assumed mode method; Lyapunov-based controller; LBC; matching condition; sliding mode controller; SMC; two-link flexible manipulator; TLFM; uncertainty.
    DOI: 10.1504/IJAAC.2024.10055581
  • Improving ride comfort approach by fuzzy and genetic-based PID controller in active seat suspension   Order a copy of this article
    by Hamid Gheibollahi, Masoud Masih-Tehrani, Amin Najafi 
    Abstract: This article investigates the influence of two active seat suspension controllers on the ride comfort of an articulated truck semi-trailer. This paper presents a linear truck model with 13 degrees of freedom (DOF). This model is coupled with a four-DOF biodynamic model. GA-PID and fuzzy-PID controllers are defined and applied to the seat suspension to provide more ride comfort under different road conditions. The genetic algorithm (GA) extracts the first PID controller parameters, and the second PID controller parameters are achieved by fuzzy logic control (FLC). The optimisation function was considered a linear combination of some ride comfort factors. Simulation results reveal that GA-PID and fuzzy-PID controllers have had similar results and could improve ride comfort and health by declining motion sickness dose value (37.42%), vibration dose value (37.53%), excess kurtosis (14.41%), crest factor (4.95%), whole body RMS acceleration (37.40%) and its peak (39.51%) compared to the passive suspension systems.
    Keywords: motion sickness dose value; MSDV; vibration dose value; VDV; excess kurtosis; EK; crest factor; CF; whole-body vibration; WBV; ride comfort.
    DOI: 10.1504/IJAAC.2024.10056050
  • A quadrotor controlled in real-time using hand gestures and ROS2 multi-node communication within GAZEBO 3D environment   Order a copy of this article
    by Hamza Djizi, Abdelaziz Lakehal, Zoubir Zahzouh 
    Abstract: This paper introduces a novel way of designing and controlling a quadrotor prototype using hand gestures, utilising the Robotic Operating System 2 (ROS2) and GAZEBO11 3D environment. A C++-based plug-in was created for GAZEBO, while the cross-platform pipeline framework Media-Pipe was used to manage the quadrotor's movements through hand gestures. The PID regulator was utilised to enhance the movements' accuracy and responsiveness, leading to a more efficient and precise response to user commands for a better user experience. The obtained results demonstrated that the PID regulator improved the response of the quadrotor to hand gestures with greater accuracy.
    Keywords: Robotic Operating System 2; ROS2; quadrotor; GAZEBO; control; communication; hand gestures.
    DOI: 10.1504/IJAAC.2024.10056000
  • Chaos control of RESs integrated power system model using adaptive higher order PID SMC and comparison of different adaptive SMC techniques   Order a copy of this article
    by Prakash Chandra Gupta, Piyush Pratap Singh 
    Abstract: In this paper, the analysis and control of renewable energy sources (RESs) integrated 4D power system model are reported. Wind energy systems and photovoltaic panels are integrated as RESs into the power system model. A power system is a very complex, dynamic system that exhibits nonlinear behaviours. Consequently, the power system may experience serious scenarios like voltage instability or voltage collapse. The bifurcation and chaos behaviours of the RESs integrated power system model are studied and verified using the Lyapunov exponent, Lyapunov spectrum, and bifurcation diagram. Since chaotic oscillations are unlike and highly dangerous for stable operation of a power system, an adaptive higher order PID sliding mode control (SMC) technique is designed to control the chaotic oscillation. The required asymptotic stability condition is derived using Lyapunov stability theory. A comparative study is done based on different performance indices to analyse the performance of the designed control with four existing adaptive SMC techniques.
    Keywords: power system; chaos; bifurcation; renewable energy sources; RESs; adaptive control; sliding mode control; SMC.
    DOI: 10.1504/IJAAC.2024.10056205
  • An improved information entropy for the integrated emergency-defence system capability evaluation   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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 (Ms) 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