International Journal of Modelling, Identification and Control (18 papers in press)

Regular Issues

• Outlier detection algorithm based on deviation characteristic  
  by Yong Wang, Hongbin Wang, Pengcheng Sun, Xinliang Yin 
  Abstract: Outlier mining focuses on researching rare events through detection and analysis to dig out the valuable knowledge from them. In the static data set environment, the traditional LOF algorithm calculates the local outlier factor through the whole data set and requires a lot of computing time. To solve this problem, the algorithm divides the data space into grids, and calculates the local outlier factor based on the centroids of the grids. Since the grid number is less than data point number, the time complexity is obviously reduced under acceptable error. When the new data points are added, it can rapidly detect outliers. The contrast experiment results show that the new algorithm can reduce the computation time and improve the efficiency, while achieving comparable accuracy.
  Keywords: outlier detection; local outlier factor; deviation characteristic; fast LOF detection algorithm.
  
  
• Tube-MPC method via estimation for flexible hypersonic vehicle with input delay  
  by Taoyi Chen, Huixiang Peng, Xiaoyu Chang, Xiaonan Zhang, Xinyue Liu 
  Abstract: In this paper, a novel tube model predictive control (Tube-MPC) method is proposed for flexible hypersonic vehicle with input delay. Firstly, input delay is approached and identified by all-pole approximation and gradient estimation methods respectively. Secondly, the polytopic linear parameter-varying (LPV) model is established. On the basis, the Tube-MPC controller is designed to handle input delay and parameter uncertainty using the predictive state over the delay period. For the bounded predictive error resulted from the delay estimation error, the nominal controller of Tube-MPC is updated by redesigning the invariant set based on the baseline controller. Then, the stability of the closed-loop system is guaranteed. Finally, the simulation results verify the proposed method’s effectiveness for flexible hypersonic vehicle with input delay.
  Keywords: flexible hypersonic vehicle; input delay; tube model predictive control; Tube-MPC; prediction.
  DOI: 10.1504/IJMIC.2024.10066641
   
  
• Reliability optimisation method for intelligent manufacturing systems based on particle swarm optimisation algorithm  
  by Li Ren, Juchen Li 
  Abstract: This paper proposes a reliability optimization method for intelligent manufacturing systems based on particle swarm optimization algorithm in order to improve the reliability of intelligent manufacturing systems and enhance the efficiency of resource allocation. Firstly, reliability assignment criteria for intelligent manufacturing systems are designed, subjective factors are evaluated through experts, and the fuzzy logic method is used to calculate the weight of the influencing factors; Then, the reliability problem of intelligent manufacturing system is described, and the reliability decision model of intelligent manufacturing system is constructed; Finally, the particle swarm optimization algorithm is used to obtain the optimal resource allocation for the intelligent manufacturing system, maximizing its reliability. The experimental results show that the resource allocation reliability of our method can reach 99.5%, and the resource allocation accuracy can reach 99.8%. Our method can improve the resource allocation efficiency of intelligent manufacturing systems.
  Keywords: particle swarm optimisation; decision model; allocation criteria; fuzzy logic; intelligent manufacturing system.
  DOI: 10.1504/IJMIC.2024.10066805
   
  
• Urban traffic vehicle trajectory tracking control method based on binocular vision  
  by Zhiting Liu 
  Abstract: To improve the effectiveness of vehicle trajectory tracking control and reduce tracking false alarms, this paper proposes a binocular vision based urban traffic vehicle trajectory tracking control method. Firstly, using binocular stereo vision technology to obtain image information from different perspectives and obtain depth information of traffic vehicle trajectory images; Secondly, calculate the similarity of vehicle trajectory tracking targets based on motion characteristics and obtain the similarity distance of target matching; Then, the relaxation factor term is introduced to construct the control objective function, and the control increment is obtained based on the constraint conditions; Finally, solve the incremental sequence of control variables to complete the tracking control of the desired trajectory. The results show that the tracking false detection rate under the proposed method does not exceed 0.22%, and the control time is within 12 seconds, demonstrating good universality and applicability.
  Keywords: forward distribution addition; dynamic grid generation algorithm; XGBoost; data mining.
  DOI: 10.1504/IJMIC.2024.10066806
   
  
• A precise control method for gripping force of underactuated grasping robotic arm  
  by Hui Cao  
  Abstract: This study aims to improve the success rate, accuracy, and stability of robotic arm grasping, and proposes a precise control method for the gripping force of underactuated grasping robotic arm based on improved PID. Firstly, the Denavit Hartenberg parameter method is used to determine the kinematic relationship between the end effector pose and joint angle of the robotic arm, and a dynamic model is established to analyze the motion behavior and force situation of the robotic arm. Secondly, adjust the parameters of the PID controller to meet the control requirements under different working conditions. Finally, the PID control method is improved by adjusting the force distribution between each circuit through a multivariable PID method, achieving precise control of the gripping force of the underactuated grasping robotic arm. The experimental results show that the proposed method can improve the success rate, accuracy, and stability of grasping.
  Keywords: underdrive; mechanical arm; clamping force; dynamic model; Denavit Hartenberg parameter method; multivariable PID control.
  DOI: 10.1504/IJMIC.2024.10066807
   
  
• An adaptive collaborative control method for multiple mobile robots based on improved genetic algorithm  
  by Yuanquan Zhong, Shaowei Zhang 
  Abstract: In order to reduce the position control error of robots and improve the collision avoidance success rate between robots, an improved genetic algorithm based adaptive collaborative control method for multiple mobile robots is proposed. Firstly, under the constraint of rotation angle, a robot adaptive collaborative control objective function is constructed with the goal of collision avoidance by combining the moving step size. Secondly, in order to improve the convergence of genetic algorithm, virtual tasks are added to improve the algorithm. Finally, calculate the fitness function of the improved genetic algorithm, solve the objective function based on the fitness function, obtain the optimal solution, and complete the adaptive collaborative control of multiple mobile robots. The experimental results show that the position control error of the proposed method is significantly reduced, with a minimum of only 0.13m, and the collision avoidance success rate is significantly improved, consistently maintaining above 95%.
  Keywords: improved genetic algorithm; multiple mobile robots; adaptive collaborative control; rotation angle.
  DOI: 10.1504/IJMIC.2024.10066808
   
  
• Novel heuristics for identifying failures on railroad switches: a case study on Vales railway  
  by João Pedro Augusto Costa, Omar Andres Carmona Cortes, Adriano Rodrigues, Andre Machado Sousa, Tiago Ferreira Souza, Valerio Nunes 
  Abstract: Railroad switches are essential mobile mechanisms to control trains, guiding them from one track to another. However, they are subject to failures over time because of wheel attrition, component wear, and obstacles during the train movement. In modern railways, switch operations are controlled by point machines, which allows the switches to be operated remotely, enabling a more robust operational schema. Electric point machines generally receive commands from PLCs, which keep historical information from both commands sent and indications received from the railroad equipment. This paper proposes two heuristics developed and used to identify the four most common types of occurrences that can lead to future failures on railroad switches and point machines, avoiding emergency maintenance that stops the railway operation and avoiding possible accidents. This system enables us to analyze the data coming from Vale’s railway dataset and identify possible operational issues. The obtained results using these heuristics show that it is possible to decrease the number of failures by almost 50% when we use the information as the starting point to apply predictive maintenance.
  Keywords: heuristics; failure; detection; railway.
  DOI: 10.1504/IJMIC.2024.10066885
   
  
• Observer-based distributed cooperative control strategies for AC microgrids under false data injection attacks  
  by Yiwei Feng, Yuhong Meng 
  Abstract: In this paper, we focus on the false data injection (FDI) attack that violates the cooperative nature of AC (ac) microgrid distributed generators (DGs), resulting in an unstable dynamics of the system. In order to solve the above problems, we propose observer-based detection and resilient control strategy. Firstly, a commonly used AC microgrid model needs to be established, and an FDI attack independent of the data encrypted by the system needs to be designed based on the control structure of the microgrid, to illustrate the sufficient necessity of studying this attack. Then, based on the above system and attack model, an observer-based detection is designed in one part to observe the data at the attacked location and accurately differentiate between attacks and disturbances. An adaptive distributed resilience controller is designed in the other part to ensure that the frequency of the system can be kept in synchrony and recovered to the reference frequency under attack to curb system out-of-synchrony operation. Finally, the speed of convergence from the system frequency and the ability to recover to the reference frequency of the controller designed in this paper is verified by simulation comparison on a system with 4 DGs, which verifies that the control of the controller designed in this paper is better under different attacks.
  Keywords: AC microgrids; AC MGs; false data injection; FDI; attack; an adaptive distributed resilience controller.
  DOI: 10.1504/IJMIC.2024.10065056
   
  
• Delayed model-free adaptive control with prescribed performance and external disturbance based on DESO  
  by Yujuan Wang, Jiahui Huang, Chao Shen, Hua Chen 
  Abstract: A new data-driven model-free adaptive control is proposed for the discrete-time nonlinear system with input time delay and bounded external disturbance, and the tracking error constraint is considered to improve the tracking accuracy. Firstly, the original nonlinear time delay system is transformed into a data model by applying the partial-form dynamic linearisation (PFDL) method. Secondly, the discrete-time extended state observer (DESO) is applied to estimate the unknown residual nonlinear time-varying term. In addition, a novel transformed error algorithm and a new sliding mode control framework are studied to ensure the tracking error converges to the preset region. A DESO-based PFDL prescribed performance control (PPC) is proposed to ensure that the tracking error always converges to a prescribed zone, which is important and considerable in practical engineering applications. Finally, some numerical simulations prove the effectiveness of the proposed control methods.
  Keywords: model-free adaptive control; prescribed performance control; PPC; disturbance; time delay; discrete-time extended state observer.
  DOI: 10.1504/IJMIC.2024.10066943
   
  
• Automatic control method of AC asynchronous motor variable frequency speed control based on CEEMDAN-wavelet threshold  
  by Dandan Zhao, Xiaodong Zhang 
  Abstract: In order to overcome the problems of low response speed, poor control accuracy, and low baud rate in motor variable frequency speed control, an automatic control method for motor variable frequency speed control based on CEEMDAN wavelet threshold was designed. Firstly, collect motor signals and decompose them through CEEMDAN; then, use wavelet threshold to remove high-frequency component signal noise; finally, calculate the frequency of variable frequency speed control and use a current and speed dual closed-loop PI controller to control the motor speed and load torque, achieving automatic control of variable frequency speed control. The results show that after applying the method proposed in this paper, the minimum speed deviation is only 29 RPM, the minimum response speed is only 628 ms, and the control baud rate varies between 147 and 180 bps/h. This verifies the effectiveness of the motor variable frequency speed control method proposed in this paper.
  Keywords: AC asynchronous motor; variable frequency speed control; CEEMDAN decomposition; wavelet threshold; control frequency.
  DOI: 10.1504/IJMIC.2024.10064159
   
  
• Design of DTS training simulation system networking based on LoRaWAN protocol  
  by Weichen Long, Ruiqian Su, Haiyong Wu, Wei Wang, Lizhong Peng 
  Abstract: To improve the networking effect of DTS training simulation system, research is conducted on the networking design of DTS training simulation system based on LoRaWAN protocol. First, the networking architecture is designed according to the LoRaWAN protocol. Then, the DTS training simulation system is connected to the LoRaWAN protocol, and the optimal gateway of the DTS training simulation system networking is selected to achieve network API LoRa gateway load balance control. Finally, experiments are used to prove the progressiveness of the proposed method. The experimental results show that after applying the proposed method, the training simulation system has a throughput of 183 bits/s, a data transmission delay of only 13 ms, and a resource utilisation rate of 96.5%, proving its good application effect.
  Keywords: LoRaWAN protocol; optimal gateway selection; system networking design; load balance.
  DOI: 10.1504/IJMIC.2024.10064170
   
  
• Remote user experience data collection method for social networks under cloud visualisation layout  
  by Yingchun Zhang 
  Abstract: A remote user experience data collection method for social networks based on cloud visualisation layout is proposed to address issues such as low efficiency in data collection. Firstly, determine the type of experience for remote users and calculate the weight to determine the key elements of the user experience; secondly, a directed graph structured social network is introduced to obtain experiential features, and interference is reduced through normalisation. HITS algorithm is used to analyse experiential features; then, the experience data features are visualised and transformed, using TF-IDF algorithm to filter remote user experience features, and designing cloud visualisation layout. At the same time, consistency of difference values is processed, and all experience data is annotated; finally, the annotation objective function and constraint conditions are introduced to achieve the design of the collection method. The research results indicate that the proposed method can efficiently collect experience data and has certain feasibility.
  Keywords: cloud visualisation layout; social networks; remote users; experience data; collection; HITS algorithm.
  DOI: 10.1504/IJMIC.2024.10066496
   
  
• An obstacle avoidance trajectory control method for robot biomimetic manipulators based on machine vision  
  by Yongtang Wu 
  Abstract: In order to improve the control effect of obstacle avoidance trajectory, a robot biomimetic robotic arm obstacle avoidance trajectory control method is studied using computer vision technology. By equipping the robot with visual sensors, it can obtain image information from the environment. Based on this information, a region growth algorithm is combined for robotic arm image segmentation, while visual tracking algorithms are used for robotic arm obstacle detection. On the basis of obstacle detection, the convolutional neural network (CNN) in machine vision algorithms is combined to achieve obstacle avoidance trajectory control for robot biomimetic robotic arms. Based on the perceived environmental obstacle information, the obstacle avoidance trajectory is generated. By analysing the experimental results, it can be concluded that the method proposed in this paper can efficiently avoid obstacles of various shapes and sizes, with a high success rate and smoothness, providing strong support for safe and efficient robot operations.
  Keywords: machine vision; biomimetic robotic arm; adaptive estimation; region growth algorithm; convolutional neural network; CNN.
  DOI: 10.1504/IJMIC.2024.10066494
   
  
• Motion control of eight bar stamping mechanism based on fuzzy self-tuning PID  
  by Dongsheng Ma, Juchen Li 
  Abstract: In order to improve the motion speed and operational efficiency of the eight bar stamping mechanism, a motion control method based on fuzzy self-tuning PID for the eight bar stamping mechanism is proposed. Firstly, based on the structural principle of the eight bar stamping mechanism, a dynamic model of the eight bar stamping mechanism is constructed by combining collision contact force and friction force, and its motion characteristics are analysed. Secondly, a fuzzy self-tuning PID controller structure is designed and the basic and fuzzy domains of the controller output and output variables are set. Finally, by setting fuzzy rules, self-tuning parameters are calculated. The parameters are input into the controller to complete the motion control of the eight bar stamping mechanism. The experimental results show that the method proposed in this paper can improve the operational efficiency of the eight bar stamping mechanism while increasing its motion speed.
  Keywords: fuzzy self-tuning PID; eight bar stamping mechanism; motion control; fuzzy rules.
  DOI: 10.1504/IJMIC.2024.10066492
   
  
• Obstacle avoidance trajectory control method for quadruped biomimetic robots based on embedded sensors  
  by Yuanquan Zhong, Guanglin Wang 
  Abstract: To improve the obstacle avoidance effect of robots, a four legged bionic robot obstacle avoidance trajectory control method based on embedded sensors is proposed. Firstly, an embedded sensor module is designed using CMOS sensors, ARM processors, and PCs to obtain accurate perception results of the robot's mobile environment. Secondly, the motion characteristics and dynamic behaviour of robots in actual mobile tasks are analysed. Then, the bilinear interpolation method is used to find a safe moving target point, and the obstacle avoidance safety distance is calculated using the dynamic window method. Finally, constrained by the safe distance, the obstacle avoidance path is planned based on the grid method, and the robot's angular velocity and linear velocity are adjusted to adjust the direction of travel. The experiment shows that the obstacle avoidance effect of this method is good, and the control response time is between 3.10 s and 3.90 s.
  Keywords: quadruped biomimetic robot; embedded sensors; dynamic analysis; obstacle avoidance trajectory control.
  DOI: 10.1504/IJMIC.2024.10066493
   
  
• Detection method of abnormal state of power transformer based on SOM neural network  
  by Wei Tong, Qi-Ping Huang 
  Abstract: In order to reduce the detection error of abnormal states of power transformers, a power transformer abnormal state detection method based on SOM neural network is proposed. Firstly, collect data such as current, voltage, temperature, and vibration of power transformers, and extract the characteristics of abnormal states of power transformers through empirical wavelet transform. Secondly, by constructing a decision function, the pre-processing results of abnormal state detection feature quantities for power transformers are obtained. Finally, based on the pre-processed abnormal state features and the detection results of power transformer abnormal states, a power transformer abnormal state detection model is constructed using SOM convolutional neural network. The experimental results show that the proposed method is relatively superior in terms of anomaly detection error, with a detection error of only 4.78 cm under a 5% delay error.
  Keywords: SOM neural network; power transformer; abnormal state detection; empirical wavelet transform; EMD.
  DOI: 10.1504/IJMIC.2024.10066491
   
  
• Hybrid multi control for better drone stability  
  by Wassim Arfa, Chiraz Ben Jabeur, Yassine Faleh, Hassene Seddik 
  Abstract: This study posits that the PID controller, designed to uphold drone stability, encounters a timing issue that warrants further tuning and enhancement. The study conducts a performance evaluation of PID controller gains for drone angle control, with the objective of optimising them to bolster the drone's speed, accuracy, and stability. To achieve this objective, a PID flight controller is proposed to manage the altitude dynamics of a UAV. The study's methodology primarily involves a comparative analysis across three levels: initially utilising a single PID controller for all three angles, then employing two PID controllers for all three angles where one manages pitch and roll angles while the other handles yaw angle, and finally implementing three PID sub-controllers for each angle (pitch, roll, and yaw). The comparative analysis aims to pinpoint the most effective PID controller configuration that enhances stability, responsiveness, and accuracy during flight. In comparison to prior research, the suggested adaptive PID flight controller showcases innovation and efficacy in the field.
  Keywords: PID controller; drone; angle control; optimisation; simulation; stability.
  DOI: 10.1504/IJMIC.2024.10064246
   
  
• Vibration control method of eight-bar stamping mechanism based on coupled backstepping method  
  by Jiangliu Deng 
  Abstract: To address the issue of coupling vibration in the eight-bar stamping mechanism, a vibration control approach utilising the coupled backstepping method is introduced. We establish a three-degree-of-freedom vibration model for the eight-bar stamping mechanism and devise a coupled vibration control strategy, leveraging the coupled backstepping method, specifically tailored for the various mass blocks experiencing forces within the vibration model. An output feedback controller is designed, and the coupled backstepping method is employed to vertically control and synchronise the upper crossbeam components, slider components, and base components of the eight-bar stamping mechanism. Experimental findings reveal that, as the operating time of the eight-bar stamping mechanism increases, the vibration speed stabilises at approximately 0 mm/s within 0.5 seconds, thereby demonstrating the effectiveness of the proposed method in achieving coupled vibration control.
  Keywords: coupled backstepping; eight-bar stamping mechanism; vibration control; kinematic model; controller.
  DOI: 10.1504/IJMIC.2024.10064888