International Journal of Modelling, Identification and Control (6 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
   
  
• 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
   
  
• Anti-windup attitude control for UAVs based on exponential coordinates  
  by Chao Liu 
  Abstract: This paper investigates the manoeuvring capabilities of UAVs while considering the singularities of kinematic representation and actuator saturation. Initially, the attitude kinematics of UAVs are represented on a configuration manifold, and exponential coordinates are utilized to describe their evolution on the tangent space of the said manifold. Subsequently, the UAV's attitude model with exponential coordinates is taken as the control model, and an inverse model is developed. A state feedback controller using PCH (pseudo control hedging) is constructed based on the inverse model. The simulation results demonstrate that the designed controller is effective in ensuring that the UAVs track the desired angles sharply and accurately while also avoiding poor performance due to actuator saturation.
  Keywords: UAV; exponential coordinates; anti-windup; pseudo control hedging; PCH; exponential stability.
  DOI: 10.1504/IJMIC.2024.10068411
   
  
• Multi-scale transmission line defect identification for new power system based on convolutional neural network  
  by Jinbin Luo, Jian Zhang, Ruchao LIAO, Duanjiao LI, Jinchao Guo 
  Abstract: In the face of multiple multi-scale transmission line defects, existing methods have problems with low identification accuracy and long identification time. Therefore, this paper proposes a multi-scale transmission line defect identification for new power system based on convolutional neural network. Firstly, use unmanned aerial vehicles to collect multi-scale images of transmission line defects and correct the collected images. Secondly, this article establishes a unified data centre for storing, managing, and analysing this data. Then, convolutional neural networks are used to extract defect features from multi-scale transmission line images. Finally, the extracted defect features are input into the support vector to complete the identification of multi-scale transmission line defects. The experimental results show that the proposed method can accurately identify various types of transmission line defects and shorten the identification time.
  Keywords: data centre; new power system; multi scale; transmission lines; defect identification.
  DOI: 10.1504/IJMIC.2024.10068673
   
  
• Graphical Voronoi study for enhancing pursuer-evader robot games strategies: improved spatial awareness and decision-making  
  by Imen Ben Omrane, Khaled Khnissi, Hassene Seddik, Ahmed Hably 
  Abstract: This research examines a differential multi-agent pursuit-evasion capture game based on an improved graphical Voronoi partition method. The objective is to capture all evaders within a specified time limit. By applying the modified Voronoi graph technique, every pursuer can detect nearby evaders and move to catch them. The pursuer performs capturing by surrounding the evader within its Voronoi cell. As the pursuit intensifies, the area of the evaders cell shrinks since the agents work in a constrained environment. The general applicability of this graphical method for resolving multi-agent pursuit-evasion games is shown using Voronoi partitioning and control policies. The Voronoi diagram provides a discrete abstraction of the continuous space which enables decentralised collision-free motion planning. To assess the computational difficulty of the multi-agent, capture method, the joint capture conditions are established. The pursuers coordinate based on local information to converge on the evaders. This research provides a novel graph-based technique for cooperative multi-agent capture scenarios and may have broader applications in robotics and distributed control. Overall, this work establishes the theoretical foundations and demonstrates the universality of an improved Voronoi-based approach for multi-pursuer multi-evader capture.
  Keywords: differential game; pursuit-evasion game; mobile robots; AI; Voronoi; decision-making; autonomous navigation.
  DOI: 10.1504/IJMIC.2025.10069694