International Journal of Modelling, Identification and Control (12 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
   
  
• Adaptive PID control based on exponential forgetting recursive least squares for 2DOF robotic manipulator  
  by Meena Girgis, Nasr Elkhateeb 
  Abstract: This paper presents a new adaptive proportional-integral-derivative (PID) controller for improving the stability and performance of a 2DOF robotic manipulator. Robotic arm manipulators have complex nonlinear dynamics that can cause stability and tracking issues. Moreover, the control process can be rigid due to the high coupling between the position and acceleration of the robotic arm and joint torques. Therefore, the paper proposes the exponential forgetting recursive least squares (EFRLS) algorithm for tuning the PID gains. The EFRLS algorithm is developed using Lyapunov stability analysis to ensure stability while adapting the PID gains. The adaptive PID based on the EFRLS algorithm offers a stable and robust tracking performance of the 2DOF robotic manipulator in the presence of disturbance effects.
  Keywords: adaptive; PID control; recursive least squares; 2DOF robotic manipulator.
  DOI: 10.1504/IJMIC.2024.10067217
   
  
• Mechanical characteristics analysis of cantilever hydraulic steel pipe structure in construction machinery under low-speed impact  
  by Jibin Guo, Haiyang Yuan, Peng Li 
  Abstract: The purpose of this study is to analysis the mechanical properties of cantilever hydraulic steel pipe structure of construction machinery under low-speed impact. The impact test and mechanical characteristics analysis were carried out by using a drop hammer test machine with a maximum impact energy of 300J. After analyzing the load of the hydraulic steel pipe, it can be judged that the maximum load and maximum stress will appear at the A end of the steel pipe. Therefore, the composite stress at points 1 to 4 in Figure 4 can be calculated to analyze the mechanical properties of the steel pipe structure. The experimental results show that, compared with the existing methods, the stress analysis accuracy of the proposed method is significantly improved, which is always maintained at more than 90%, and the response time of the proposed method is also significantly reduced.
  Keywords: low-speed impact; construction machinery cantilever; hydraulic steel pipe; mechanical properties.
  DOI: 10.1504/IJMIC.2024.10067277
   
  
• Prediction method of ultimate bearing capacity of derrick steel structures based on firefly algorithm  
  by Xiaodong Li 
  Abstract: To overcome the problems of high relative error rate of load detection, low prediction accuracy and long time consumption in traditional prediction methods, a prediction method of ultimate bearing capacity of derrick steel structures based on firefly algorithm is proposed. The vibration system equation of derrick steel structure is constructed and simplified, so as to identify the dynamic response parameters. The load parameters of derrick steel structure are detected by combining the results of vibration differential equation. According to the load parameter detection results, the ultimate bearing capacity prediction model based on RBF neural network optimized by firefly algorithm is established, and the ultimate bearing capacity prediction results are obtained. The experimental results show that the relative error rate of load detection of this method varies in the range of 2.5%~4.8%, the prediction accuracy is always above 92.6%, the time consumption varies from 0.47 s to 0.84 s.
  Keywords: firefly algorithm; derrick steel structure; ultimate bearing capacity; prediction; dynamic response parameters; load parameters; RBF neural network.
  DOI: 10.1504/IJMIC.2024.10067640
   
  
• Stress distribution of rotating machinery bearing bolts based on finite element analysis  
  by Rongchang Zhou, Yangbin Xie, Shudong He 
  Abstract: The research on stress distribution of rotating machinery bearing bolts is of great significance for improving the safety, reliability and economy of rotating machinery.In order to overcome the problems of high relative error rate of stress measurement, low analysis accuracy and long time consumption in traditional methods, a research method of stress distribution of rotating machinery bearing bolts based on finite element analysis is proposed. The data of rotating machinery bearing bolts are collected, and the missing data are filled by MIC-LSTM.The finite element model of rotating machinery bearing bolt is established by finite element software, and the stress distribution of bolt is analyzed through the steps of material property definition, mesh division,boundary conditions and load application. The experimental results show that the maximum relative error rate of stress measurement is 3.7%, the maximum analysis accuracy is 97.1%, and the average analysis time is 0.45 s.
  Keywords: finite element analysis; rotating machinery bearing; bolts; stress distribution; MIC-LSTM; stress measurement.
  DOI: 10.1504/IJMIC.2024.10067641
   
  
• Strong structural controllability of structured networks with MIMO node systems  
  by Yanting Ni, Jiajia Jia, Xuyang Lou 
  Abstract: This paper addresses the problem of strong structural controllability of structured networks with multi-input multi-output (MIMO) node systems. The authors first present necessary and sufficient condition for strong structural controllability. The condition is somewhat restrictive and computationally expensive, especially for large-scale networks with high-dimensional state spaces. To overcome this computational complexity, several necessary algebraic conditions are established from the perspectives of both the node dynamics and the structured interconnection laws, respectively. Furthermore, by utilizing the so-called weakly color change rule, a graph-theoretic method is provided to assess the condition from the perspective of the structured interconnection laws. Overall, this paper contributes to the study of strong structural controllability in structured networks with MIMO node systems, providing both theoretical and practical insights for their analysis and design.
  Keywords: structural controllability; structured network; multi-input-multi-output system.
  DOI: 10.1504/IJMIC.2024.10067821