Current Issue
Vol. 22, No. 9, September 2024
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Regular PapersSeptember 1, 2024
Real-time Stability Monitoring of Power Systems Using Instantaneous Lyapunov Exponent and Malthusian Parameter
Antamil Said and Takami Matsuo*
International Journal of Control, Automation, and Systems 2024; 22(9): 2673-2685AbstractAbstract : While the Lyapunov exponents used in previous studies require embedded dimensions and/or multiple initial conditions, our previously proposed instantaneous Lyapunov exponent (ILE) and Malthusian parameter estimator (MPE) directly estimate the rate of increase or decrease by time series data in real-time. The MPE uses adaptive control algorithms to estimate the rate of increase or decrease of the system. Our previously proposed MPE tends to have larger errors for fast-varying parameters and requires a PE condition, but the MPE in the case of a stable system does not satisfy the persistency of excitation (PE) condition. In this paper, we apply recently proposed parameter estimation algorithms effective for time-varying parameters to MPE. Moreover, the other MPE using the generalized parameter estimation-based observer (GPEBO) and the energy pumping-and-damping injection construction is proposed, that does not require the PE condition. The proposed methods allow us to monitor the transient stability in real-time. We compare the estimation performance of ILE and four MPE’s by using two power system examples.
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Regular PapersSeptember 1, 2024
Optimal Cooperative Controls for Multi-motor Driving System in Long-wall Shearer
Yongfeng Lv*, Jun Zhao, Baixue Miao, Huimin Chang, and Xuemei Ren
International Journal of Control, Automation, and Systems 2024; 22(9): 2686-2698AbstractAbstract : The traditional coal mining machine uses a single-motor system, which will terminate when encountering a hard road header surface because of power limitations. The same problem exists in large radar servo systems and other applications of heavy industrial. To address this issue, this paper develops the multi-motor driving servo system for the coal mining machine, and designs the adaptive optimal torques for the cut-off gear and the multi-motor system. Firstly, the multi-motor driving system for the coal mining machine is modeled. The optimal performance functions of the cut-off gear and the driving motors are presented, and the Nash equilibrium among the optimal torques is defined. Then, based on the given performance functions, the adaptive optimal torques are found by approximate dynamic programming (ADP) technique, which can find the saddle point and optimize the coal mining machine performance. Moreover, the neural network (NN) weight convergence in the ADP structure is investigated. The stability of the multi-motor driven system with the proposed torques is proved. Finally, taking the coal mining machine as an example, the effectiveness of the performance optimization strategies of cut-off gear and multi-driving motors is verified.
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Regular PapersSeptember 1, 2024
Optimal Control Strategies for a Supply Chain System With Delay and Reference Price Effects
Zhihui Wu*, Guo-Ping Liu, June Hu, Hui Yu, and Dongyan Chen
International Journal of Control, Automation, and Systems 2024; 22(9): 2699-2710AbstractAbstract : This paper mainly discusses the impacts from the time delay of advertising and the reference price of consumer onto the cooperative advertising decisions. In our model, both the retailer’s platform goodwill (RPG) and the manufacturer’s brand goodwill (MBG) involved with their own advertising efforts are modeled by the delay differential equations. In addition, the RPG and the MBG have positive effects on the consumer’s reference price. The equilibrium advertising strategies of two channel members are firstly derived within the centralized and decentralized scenarios by resorting to the optimal control theory. Besides, the corresponding equilibrium advertising strategies and optimal channel profits are compared, which shows that the centralization brings higher profit to whole channel only when the time delays locate within a specified geometric region and the existence of time delay caused by manufacturer’s advertising also implies smaller advertising participation rate provided by the retailer. Subsequently, a new mechanism is designed to coordinate the supply chain system in the decentralized case under the consignment mode. Finally, a numerical example is employed to illustrate the impacts from key system parameters onto the coordination results when the supply chain is coordinated.
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Regular PapersSeptember 1, 2024
Adaptive Back-stepping Control of Servo Systems With Asymmetric Dead Zone
Xue Wang and Shubo Wang*
International Journal of Control, Automation, and Systems 2024; 22(9): 2711-2722AbstractAbstract : In this paper, an adaptive back-stepping control scheme based on the command filter is proposed for the servo system with current constraints and non-symmetric dead zone. First, a novel system transformation scheme is designed to transform the servo system with current constraints into the equivalent “unconstrained”. A security boundary is incorporated into the designed strategy to restrict the activation state of the constraint mechanism. Second, the asymmetric dead zone nonlinearities can be represented into a parameterized form by using a continuous piecewise linear neural network (CPLNN). Moreover, an adaptive law with guaranteed convergence is used to online update the CPLNN weights so as to derive the dead zone characteristic parameters and then compensate for the asymmetric dead zone.Then, the command filter is introduced into the back-stepping control strategy to avoid the complexity explosion. The stability analysis of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness and feasibility of the proposed control scheme are validated through the real-time experiments on a permanent magnet synchronous motor (PMSM) platform.
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Regular PapersSeptember 1, 2024
Optimal Stealthy Attack With Side Information Under the Energy Constraint on Remote State Estimation
Sheng-Sheng Dong, Yi-Gang Li*, Li Chen, and Xiaoling Zhang
International Journal of Control, Automation, and Systems 2024; 22(9): 2723-2733AbstractAbstract : This work considers the innovation-based attacks with side information under the energy constraint in cyber-physical systems where Kullback-Leibler (K-L) divergence is used as the stealthiness metric. Moreover, the attacker requires to decide when to launch attacks over a finite time horizon since the energy limitation. To cause the largest degradation to the estimation performance, the attack strategy and schedule require to be designed synergistically under the constraints. The terminal error (TE) and average error (AE) are respectively taken as attack performance indices. Then, the optimal attack policies for the TE and AE are obtained by solving a constrained optimization problem and a 0-1 programming problem. Finally, simulation examples are employed to demonstrate the results.
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Regular PapersSeptember 1, 2024
Finite-time Stabilization of Fractional-order Impulsive Switched Systems With Saturated Control Input
Yilin Shang, Leipo Liu*, Wenbo Zhang, Zhumu Fu, Xiushan Cai, and Weidong Zhang
International Journal of Control, Automation, and Systems 2024; 22(9): 2734-2745AbstractAbstract : This paper investigates the finite-time stabilization problem of fractional-order impulsive switched systems with saturated control input and matched disturbance. Saturated control input exists in the continuous time intervals as well as at the impulsive instants. By using the average dwell time approach, the Lyapunov stability theory and the binomial theorem, sufficient conditions are proposed to guarantee finite-time stability of the closedloop system. Meanwhile, the controller gains can be got via solving linear matrix inequalities. In addition, the biggest attraction domain is obtained by solving the proposed optimization problem. Finally, numerical examples are provided to illustrate the effectiveness of the designed controller.
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Regular PapersSeptember 1, 2024
Immersion and Invariance Adaptive Control for a Class of Nonlinear Systems With Uncertain Parameters
Jian-Hui Wang, Guang-Ping He*, Gui-Bin Bian, Jun-Jie Yuan, Shi-Xiong Geng, Cheng-Jie Zhang, and Cheng-Hao Zhao
International Journal of Control, Automation, and Systems 2024; 22(9): 2746-2757AbstractAbstract : An adaptive control method based on immersion and invariance (I&I) is presented in a class of nonlinear systems with time-varying uncertain parameters. A parameter estimation law based on reference models using I&I is designed to accelerate the convergence of estimated parameters to the true value, enabling the closed-loop system to reach the predefined target system on the manifold more quickly and reducing the energy consumption of the system. The inherent integrability obstacles in I&I are overcome by using dynamic scaling techniques, reducing the complexity of controller design. Stability analysis of the closed-loop system demonstrates that the proposed control method can achieve asymptotic stability control of the target system, and verified the robustness of the closedloop system in the face of external disturbances. Finally, simulations of attitude tracking control demonstrate the effectiveness and superiority of the proposed method.
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Regular PapersSeptember 1, 2024
Tracking Control Design for a Bilinear Control System With Unstable and Uncertain Internal Dynamics Using Adaptive Backstepping
Khozin Mu’tamar, Janson Naiborhu*, Roberd Saragih, and Dewi Handayani
International Journal of Control, Automation, and Systems 2024; 22(9): 2758-2768AbstractAbstract : A non-minimum phase system has unstable zero internal dynamics. Even though the system’s output has stabilised, the state variables of the internal dynamics continue to grow indefinitely. Uncertain parameters in the internal dynamics make their behaviour even more unpredictable. In this article, we solve the tracking problem for a bilinear control system with unstable internal dynamics and uncertain parameters using adaptive backstepping. The bilinear control system is transformed using input–output feedback linearisation to normal form. The unstable internal dynamics containing uncertain parameters are first stabilised using the external dynamics as a virtual control. The external dynamics are then stabilised using other state variables in the external dynamics; the final system uses the actual control function. Numerical simulations are performed to demonstrate the proposed control’s technical implementation and performance. A robustness test is conducted analytically and numerically to understand the control function’s tolerance to uncertain parameters. The simulation results show that the control function successfully solves tracking problems in non-minimum phase systems. Using the integral absolute error criterion, we also determine the range of uncertain parameter values for which the control function works satisfactorily.
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Regular PapersSeptember 1, 2024
Distributed Bearing-based Formation Control With Edge-triggered Observers
Can Ding, Zhe Zhang*, and Jing Zhang
International Journal of Control, Automation, and Systems 2024; 22(9): 2769-2782AbstractAbstract : With the growing prevalence of technologies such as drones, mobile robots, and autonomous vehicle fleets, multi-agent collaborative control has emerged as a significant area of research. This article focuses on distributed observer-based formation control for multi-agent systems with a leader-follower structure, utilizing edgeevent triggered mechanisms. Unlike traditional formation controls that depend on complete access to the leader’s velocity, this method requires only a select few followers to have access to the time-varying velocity information of the leader. A distributed velocity observer was developed through an edge-event triggered mechanism to reduce unnecessary data transmissions and conserve energy. Additionally, a bearing-based formation controller built on input-to-state stability theory was introduced to effectively manage formation tracking and execute scaling maneuvers. Numerical simulations demonstrate the effectiveness of the proposed methods and highlight their advantages over traditional node-based event-triggered strategies.
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Regular PapersSeptember 1, 2024
Matrix-scaled Consensus of Network Systems With Uniform Time-delays
Hoang Huy Vu, Quyen Ngoc Nguyen, Minh Hoang Trinh, and Tuynh Van Pham*
International Journal of Control, Automation, and Systems 2024; 22(9): 2783-2791AbstractAbstract : Time-delay is an unavoidable factor in analyzing and designing any networked system since in most scenarios, it decreases the performance or even destabilizes the system. In this paper, we study the newly proposed matrix-scaled consensus (MSC) algorithms under the presence of communication time delays. Both networks of single- and double-integrator agents are considered, and for each scenario, a corresponding delay margin will be given. The analysis hinges on the Nyquist stability criteria and the algebraic solution of quasi-polynomials associated with the MSC models. Numerical examples are provided to demonstrate the correctness of theoretical results.
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Regular PapersSeptember 1, 2024
Distributed Leaderless and Leader-following Consensus for Second-order Heterogeneous Multi-agent Systems Under Input Saturation
Yuwan Ma, Jie Wu, Xisheng Zhan*, and Qingsheng Yang
International Journal of Control, Automation, and Systems 2024; 22(9): 2792-2801AbstractAbstract : This paper mainly investigates the consensus problem of heterogeneous multi-agent systems (HMASs) consisting of second-order linear and second-order nonlinear agents under input saturation. First, the consensus control protocols for HMASs in the leaderless case and the leader-following case are designed under undirected connected topology respectively, where there is a static leader under the leader-following network. Then, based on the knowledge of graph theory and Lyapunov stability theory, it is proved that HMASs can finally reach consensus if sufficient conditions are satisfied. Eventually, the effectiveness of the above theory is further illustrated by simulation examples.
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Regular PapersSeptember 1, 2024
Distributed Fixed-time Optimization for Multiple Mechanical Systems
Yuan Liu*, Pinxiao Liu, Bing Zhang, and Xianpu Zeng
International Journal of Control, Automation, and Systems 2024; 22(9): 2802-2811AbstractAbstract : Under the general unbalanced directed communication graphs, distributed fixed-time optimization problem is studied for multiple mechanical systems modeled by Euler-Lagrange equations. Distributed controllers have been developed to achieve the optimal position of each agent within a fixed time by integrating distributed fixedtime estimator techniques and a fixed-time control design in a cohesive manner. The effectiveness of the proposed control protocol is also illustrated by a numerical simulation.
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Regular PapersSeptember 1, 2024
Observer-based Fixed-time Consensus Control for Nonlinear Multiagent Systems
Shaoxin Sun, Xin Dai, Xingxing Hua, Jie Duan*, Yanling Li, and Dufeng Yu
International Journal of Control, Automation, and Systems 2024; 22(9): 2812-2822AbstractAbstract : This paper investigates state estimation and system consensus control for multiagent systems with nonlinear function under communication topology. A novel weighted fixed-time observer is designed to estimate the system states. The observer designed in this paper takes the output errors of its own agent into account in weight distribution, and the agent state should not be known. A Lyapunov function is designed to make the estimation error globally fast fixed-time stable. This observer-based feedback controller is explored for keeping the consensus error system globally fast fixed-time stable. At last, two examples are considered in the simulation section to illustrate the effectiveness of the weighted fixed-time observer as well as controller.
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Regular PapersSeptember 1, 2024
Output Feedback Consensus for High-order Stochastic Multi-agent Systems With Unknown Time-varying Delays
Baoyu Wen and Jiangshuai Huang*
International Journal of Control, Automation, and Systems 2024; 22(9): 2823-2832AbstractAbstract : This paper addresses the dynamic output feedback leader-following consensus control for a class of highorder stochastic multi-agent systems characterized by unknown time-varying delays. The agents are modeled as a class of stochastic strict feedback nonlinear systems with unknown time-varying delays. Additionally, the states of the agents are unknown for control design. To address these challenges, observers are designed firstly to estimate the unknown states of each agent. Subsequently, a distributed observer-based output feedback consensus protocol, relying solely on the outputs of neighboring agents, is introduced. It is shown that the followers can effectively track the leader’s output with a 1st-moment exponential rate. The effectiveness of the proposed control scheme is validated through simulation examples.
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Regular PapersSeptember 1, 2024
Design and Experimental Evaluation of a Leader-follower Robot-assisted System for Femur Fracture Surgery
Fayez H. Alruwaili, Michael P. Clancy, Marzieh S. Saeedi-Hosseiny, Jacob A. Logar, Charalampos Papachristou, Christopher Haydel, Javad Parvizi, Iulian I. Iordachita, and Mohammad H. Abedin-Nasab*
International Journal of Control, Automation, and Systems 2024; 22(9): 2833-2846AbstractAbstract : In the face of challenges encountered during femur fracture surgery, such as the high rates of malalignment and X-ray exposure to operating personnel, robot-assisted surgery has emerged as an alternative to conventional state-of-the-art surgical methods. This paper introduces the development of a leader-follower robot-assisted system for femur fracture surgery, called Robossis. Robossis comprises a 7-DOF haptic controller and a 6-DOF surgical robot. A control architecture is developed to address the kinematic mismatch and the motion transfer between the haptic controller and the Robossis surgical robot. A motion control pipeline is designed to address the motion transfer and evaluated through experimental testing. The analysis illustrates that the Robossis surgical robot can adhere to the desired trajectory from the haptic controller with an average translational error of 0.32 mm and a rotational error of 0.07°. Additionally, a haptic rendering pipeline is developed to resolve the kinematic mismatch by constraining the haptic controller’s (user’s hand) movement within the permissible joint limits of the Robossis surgical robot. Lastly, in a cadaveric lab test, the Robossis system was tested during a mock femur fracture surgery. The result shows that the Robossis system can provide an intuitive solution for surgeons to perform femur fracture surgery.
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Regular PapersSeptember 1, 2024
A Function-integrated Neurosurgical Robot for Distributed Implantation of Microelectrodes
Hanwei Chen, Bo Han, Chao Liu, Yangmin Li, and Xinjun Sheng*
International Journal of Control, Automation, and Systems 2024; 22(9): 2847-2859AbstractAbstract : Stereotaxic surgeries for distributed implantation of microelectrodes into rat brains are vital for establishing brain-computer interfaces in neuroscience research. Minimally invasive craniotomy and microelectrode implantation are two related major surgical tasks requiring high accuracy and safety. In the literature, existing robotic systems are generally developed for a separate surgical task. However, the accuracy of drilling craniotomy performed first can directly affect the implantation outcomes later. Thus, we develop a function-integrated neurosurgical robot capable of completing multiple cranial drillings and distributed implantation of microelectrodes. A drilling module with bio-impedance feedback and an implantation module with adaptive grippers are integrated with a fiveaxis motion platform. Surgical planning methods based on Bezier curves and potential informed Bi-RRT, as well as kinematic relationships of the robotic system, are developed to guide the robot with obstacle avoidance in the surgical scene. The surgical path simulation is conducted to validate the effectiveness of the planning method. The experiments involving two surgical tasks and a repeated test at different implantation depths jointly demonstrate that this prototypical robot can perform the surgery with high accuracy and safety, indicating great potential in reducing the workload of surgeons and minimizing surgical failure rates.
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Regular PapersSeptember 1, 2024
Human Motion Retargeting to a Full-scale Humanoid Robot Using a Monocular Camera and Human Pose Estimation
Sujin Baek, Ahyeon Kim, Jin-Young Choi, Eunju Ha, and Jong-Wook Kim*
International Journal of Control, Automation, and Systems 2024; 22(9): 2860-2870AbstractAbstract : The retargeting human motions to those of a humanoid robot is a difficult task that involves using complex humanoid models and intensive geometric calculations, while also requiring high joint recognition accuracy. Herein, we propose a new motion retargeting framework for whole-body motions using a monocular camera composed of three modules per frame: 1) the extraction of 3D human joint coordinates from a package from pose AI, 2) the calculation of human joint angles by fitting the humanoid model to the skeleton model attained from the pose AI using a global optimization method, and 3) the transmission of the estimated joint angles as a pose command to a full-scale humanoid robot. The results suggest that the proposed framework can reproduce human-like motion sequences while reflecting certain limitations in the robot’s joint angles due to intentionally set hardware limitations and constraints. Using the proposed method, the robot can directly mimic human motion at the joint angle level based solely on images taken by an RGB camera or video files. These findings suggest that it would be useful to construct big data consisting of joint angle vectors for various human poses and joint angle trajectories for human motions, so that—as one example application in the near future—a robot butler could refer to these big data when performing various motions at a person’s home or in the office.
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Regular PapersSeptember 1, 2024
Predictor-based Tracking Control of a Class of Series Elastic Actuators With Input Delay
Hongwu Ye, Tingting Gao*, Yong Zhou, and Jiangshuai Huang
International Journal of Control, Automation, and Systems 2024; 22(9): 2871-2881AbstractAbstract : In this paper, tracking control of a class of series elastic actuators subject to unknown time-varying input delay and additive disturbances is investigated. To address the input delay, a novel predictor-like method is proposed in the control input which uses a predictor to compensate for the delay. Lyapunov-Krasovskii functions are applied within Lyapunov-based stability analysis to show semi-globally uniformly ultimately bounded tracking errors. The control scheme is extended to the case that the input delay is unknown and time-varying. A constant estimate of the delay is determined to establish uniformly ultimately bounded convergence of the tracking error. Numerical simulation results illustrate the performance of the developed robust controller.
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Regular PapersSeptember 1, 2024
A Gripper Capable of Screw Fastening and Gripping With a Single Driving Source
Ji-Hun Meng, Inhwan Yoon, Sung-Jae Park, and Jae-Bok Song*
International Journal of Control, Automation, and Systems 2024; 22(9): 2882-2890AbstractAbstract : As the range of applications of robots expanded, they began to be used for complex assemblies such as screw fastening and pin assembly. Most specialized screw fastening tools are sensitive to external influences and require additional instruments to prevent screw dislodgement when working in unstructured environments. To address this challenge, we propose a screw fastening gripper (SFG) capable of screw fastening and small pin gripping with a single power source. The proposed SFG is divided into a fastening part for screw fastening and a gripper for grasping, with power distributed via a magnetic gear. It is designed to temporarily separate the gripper and fastener using the magnetic gear’s features, so it can be used to fasten screws of various lengths if necessary. Through gripping force measurements and screw fastening experiments, the proposed SFG showed sufficient performance in grasping and screw fastening.
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Regular PapersSeptember 1, 2024
Adaptive ANN-BFO Hybrid Method for Solving the Forward Kinematics Problem of a Hexa Parallel Robot
Ba-Phuc Huynh
International Journal of Control, Automation, and Systems 2024; 22(9): 2891-2898AbstractAbstract : This paper introduces an adaptive hybrid approach to address the forward kinematics problem of a Hexa parallel robot (HPR), known for its challenge in obtaining a unique closed-form analytic solution. In the initial stage, we construct an artificial neural network (ANN) model to rapidly generate a preliminary result, effectively narrowing the search space. Subsequently, bacterial foraging optimization (BFO) is adapted to refine the result by focusing on exploration within the reduced search space. Adaptive functions adjust BFO parameters based on the error level in the preliminary result, enhancing algorithm performance. Software is developed to demonstrate the practical application of this method. Experimental results within the robot workspace indicate a significant reduction in calculation errors compared to using only the ANN model.
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Regular PapersSeptember 1, 2024
CSI-Net: CNN Swin Transformer Integrated Network for Infrared Small Target Detection
Lammi Choi, Won Young Chung, and Chan Gook Park*
International Journal of Control, Automation, and Systems 2024; 22(9): 2899-2908AbstractAbstract : In the realm of infrared (IR) small target detection, pinpointing blurry and low-contrast targets accurately is immensely challenging due to the intricate features of IR images. To tackle this, we introduce CSI-Net, a novel network architecture merging CNN and swin transformer. CSI-Net features a hybrid encoder design, blending encoder-decoder layout of UNet with swin transformer’s parallel execution alongside CNN. This amalgamation enables the network to capture local features and long-distance dependencies, enhancing its ability to accurately identify small targets. Leveraging hierarchical features of swin transformer, CSI-Net adeptly grasps contextual information crucial for small target detection. Moreover, CSI-Net employs full-scale skip connections over encoder-decoder and decoder-decoder, integrating multiscale CNN and swin transformer features to improve gradient propagation. Experimental results validate superiority of proposed method over traditional CNN and Transformer methods. At NUAA-SIRST, metrics like mIoU (0.7483), detection probability (0.9734), and false alarm rates (0.101 × 10−5) demonstrate significant improvement. Similarly, at NUDT-SIRST, values like mIoU (0.8887), detection probability (0.9894), and false alarm rates (0.431×10−5) show notable enhancement. The performance of network scales with dataset size, and its robustness is affirmed by the area under the ROC curve (AUC). Additionally, an ablation study validates the efficacy of hybrid encoder. Varying the presence of the parallel swin transformer module (PSM) reveals that its application enhances small target detection performance. The comprehensive evaluation shows that the swin transformer-enhanced UNet architecture effectively tackles the challenges of IR small target detection.
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Regular PapersSeptember 1, 2024
Control of a Wind Turbine Working in the Intermediate Velocity Zone: A Model Free Discrete Time Approach
Maria Letizia Corradini, Gianluca Ippoliti, and Giuseppe Orlando*
International Journal of Control, Automation, and Systems 2024; 22(9): 2909-2919AbstractAbstract : In this paper, a novel data-driven control algorithm based on model-free adaptive control is presented, addressing general discrete-time single-input single-output nonlinear systems, approximated by an equivalent dynamic linearization model using pseudo-partial derivatives. The closed loop stability is proved, showing that the tracking error asymptotically vanishes. Moreover, the proposed approach has been applied to a 5 MW wind turbine, considering as control target the efficiency optimization issue when the turbine operates under medium wind speed conditions. Validation of the technique has been performed, testing the overall control system by simulation using the tool FAST developed by the National Renewable Energy Laboratory (NREL).
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Regular PapersSeptember 1, 2024
Modified Higher Order Sliding Control Based Active Harmonic Current Compensator in Induction Furnace Using Emotional Tuned Intelligent Controller
T. D. Raheni*, K. Premalatha, and P. Thirumoorthi
International Journal of Control, Automation, and Systems 2024; 22(9): 2920-2933AbstractAbstract : This paper presents the design of active harmonic current compensator (AHCC) to mitigate the current harmonics generated by supply side for an induction furnace application. Induction furnaces have nonlinear and time-varying properties, resulting in harmonics and voltage/current imbalances. AHCC are high-speed compensators that enhance the performance of induction furnaces and solve power quality issues. The proposed system is designed with modified higher order sliding control (MHOSC) algorithm and extended form of reactive power theory to generate a three-phase reference compensating current. The control method examines the sliding surface parameter uncertainties in order to obtain a controlled direct current (DC) link current when using nonlinear converters. The proposed work compares the performance of proportional integral (PI) tuned sliding mode controllers with emotional tuned intelligent controllers (ETIC). The compensated current reference signal is used to provide switching pulses for AHCC. A major advantage of MHOSC is its ability to endure external disruptions and unpredicted parameter changes, which improves reference current tracking without introducing undesirable oscillations (chattering). Implementation of the proposed control algorithm is validated in MATLAB / Simulink demonstrating that the designed AHCC compensates the harmonic current to an acceptable level (total harmonic distortion of source current is 1.54%) satisfying IEEE 519-2014 standard.
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Regular PapersSeptember 1, 2024
Evaluating MR-GPR and MR-NN: An Exploration of Data-driven Control Methods for Nonlinear Systems
Hyuntae Kim, Hamin Chang, and Hyungbo Shim*
International Journal of Control, Automation, and Systems 2024; 22(9): 2934-2941AbstractAbstract : This paper addresses the challenge of data-driven control of nonlinear systems, focusing on the limitations and capabilities of model reference Gaussian process regression (MR-GPR) and its evolved counterpart, model reference neural networks (MR-NN). MR-GPR, based on Gaussian processes renowned for their adaptability to diverse data structures, encounters scalability issues especially when handling large datasets. To address these limitations, this paper introduces MR-NN, an extension of MR-GPR, leveraging neural networks (NN) to manage large datasets and capture complex nonlinear dynamics effectively. We present a comprehensive evaluation of both methods through a classical control problem of the inverted pendulum, a system well-recognized for its nonlinear behavior. Numerical experiments are conducted to compare the methods in terms of control performance, computational efficiency, and reliability.
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Regular PapersSeptember 1, 2024
Novel Adaptive Pinning Synchronization Criteria for Delayed Caputotype Fuzzy Neural Networks With Uncertain Parameters
Renyu Ye, Xinbin Chen, Hai Zhang*, and Jinde Cao
International Journal of Control, Automation, and Systems 2024; 22(9): 2942-2953AbstractAbstract : In this article, some synchronization issues for delayed fractional-order fuzzy neural networks (FOFNNs) including uncertain parameters are discussed. To begin with, the complete synchronization (CS) criterion is derived through the adaptive controller. This control strategy can effectively reduce control costs. Next, applying the pinning controller, the CS condition is inferred by controlling partial nodes. Meanwhile, considering the advantages of adaptive and pinning control, an adaptive pinning controller is established to reach CS. Finally, we present some numerical examples to demonstrate the derived criteria.
Vol. 22, No. 9, pp. 2673~2953
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Editorial: The 22nd International Conference on Control, Automation, and Systems (ICCAS 2022)
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International Journal of Control, Automation, and Systems 2023; 21(8): 2429-2429 -
Improved Four-channel PBTDPA Control Strategy Using Force Feedback Bilateral Teleoperation System
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International Journal of Control, Automation and Systems 2022; 20(3): 1002-1017
