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Computationally Efficient Optimal control Problem Formulation Illustrated by Automotive Applications 11

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Computationally Efficient Optimal Control Problem Formulatio...

11th Vienna International Conference on Mathematical Modelling, MATHMOD 2025

作者： Wegscheider, F. Galkina, A. Maier, J. Schlacher, K. Reichhartinger, M. Institute of Automation and Control Graz University of Technology Institute of Automation and Control Graz8010 Austria Magna Powertrain GmbH & Co KG Industriestraße 35 Lannach8502 Austria Engineering Center Steyr GmbH & Co KG Steyrer Straße 32 St. Valentin4300 Austria Lehrstuhl für Systemtheorie und Regelungstechnik Universität des Saarlandes Professur für Modellierung und Simulation Technischer Systeme Campus A5 1 Saarbrücken66123 Germany Institute of Automatic Control and Control Systems Technology Johannes Kepler Universität Linz Altenberger Straße 69 Linz4040 Austria

The paper focuses on reducing computational time when solving optimal control problems by expressing them within a flat coordinate system. To demonstrate and discuss this approach, two case studies are presented: Time-optimal velocity trajectory planning and torque control of permanent magnet synchronous motors. The reformulated optimal control problems show significant reductions in computational time without affecting the resulting trajectories. Additionally, analyses were performed to investigate the impact of prediction horizons and solver starting values on the observed computational advantages. The results clearly show the potential of the presented method for developing computationally efficient optimization-based control strategies. Copyright © 2025 The Authors.

关键词： Optimal control systems

TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

Automated Linear Parameter-Varying Modeling of Nonlinear systems: A Global Embedding Approach

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arXiv 2025年

作者： Olucha, E. Javier Koelewijn, Patrick J.W. Das, Amritam Tóth, Roland Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, an automated linear parameter-varying (LPV) model conversion approach is proposed for nonlinear dynamical systems. The proposed method achieves global embedding of the original nonlinear behavior of the system by leveraging the second fundamental theorem of calculus to factorize matrix function expressions without any approximation. The implementation of the proposed method in the LPVcore toolbox for Matlab is discussed, and its performance is showcased on a comprehensive example of automated LPV model conversion of an unbalanced disk system, which is then used to design an LPV controller that is deployed on the original nonlinear system. In addition, the conversion capabilities are further demonstrated by obtaining an LPV embedding of a three-degree-of-freedom control moment gyroscope. All software implementations are available at ***. © 2025, CC BY.

关键词： MATLAB

A Unifying Complexity-Certification Framework for Branch-and-Bound Algorithms for Mixed-Integer Linear and Quadratic Programming

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arXiv 2025年

作者： Shoja, Shamisa Arnström, Daniel Axehill, Daniel Division of Automatic Control Department of Electrical Engineering Linköping University Sweden Division of Systems and Control Department of Information Technology Uppsala University Sweden

In model predictive control (MPC) for hybrid systems, solving optimization problems efficiently and with guarantees on worst-case computational complexity is critical, particularly in real-time applications. These optimization problems often take the form of mixed-integer linear programs (MILPs) or mixed-integer quadratic programs (MIQPs) that depend on system parameters. A common approach for solving such problems is the branch-and-bound (B&B) method. This paper extends existing complexity certification methods by presenting a unified complexity-certification framework for B&B-based MILP and MIQP solvers, specifically for the family of multi-parametric MILP and MIQP problems that arise in, e.g., hybrid MPC applications. The framework provides guarantees on worst-case computational metrics, including the maximum number of iterations or relaxations B&B algorithms require to reach optimality. It systematically accounts for different branching and node selection strategies, as well as heuristics integrated into B&B, ensuring a comprehensive certification framework. By offering theoretical guarantees and practical insights for solver customization, the proposed framework enhances the reliability of B&B for real-time application. The usefulness of the proposed framework is demonstrated through numerical experiments on both random MILPs and MIQPs, as well as on MIQPs arising from a hybrid MPC problem. © 2025, CC BY.

关键词： Mixed-integer linear programming

Data-driven finite-time adaptive attitude tracking control for spacecraft

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Advances in Space Research 2025年第12期75卷 8780-8791页

作者： Wang, Jianhui He, Guangping Bian, Guibin Geng, Shixiong College of Mechanical & Energy Engineering Beijing University Of Technology Beijing100124 China Department of Mechanical and Electrical Engineering North China University of Technology Beijing100144 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the disturbance unit matrix is introduced, and the parameter estimation law in the form of algebraic equations is presented, which realizes the arbitrarily small convergence of parameter estimation error. The convergence of parameter estimation errors is verified through stability analysis. Globally non-singular fast terminal sliding mode control is designed to achieve finite-time arrival of the sliding surface and convergence of the system state error. The stability analysis of the closed-loop system demonstrates the effectiveness of the proposed method. Furthermore, the effectiveness and superiority of the proposed method are verified through numerical simulations of spacecraft attitude tracking control. © 2025 COSPAR

关键词： Attitude control

Parallel Domain-Decomposition Algorithms for Complexity Certification of Branch-and-Bound Algorithms for Mixed-Integer Linear and Quadratic Programming

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arXiv 2025年

When implementing model predictive control (MPC) for hybrid systems with a linear or a quadratic performance measure, a mixed-integer linear program (MILP) or a mixed-integer quadratic program (MIQP) needs to be solved, respectively, at each sampling instant. Recent work has introduced the possibility to certify the computational complexity of branch-and-bound (B&B) algorithms when solving MILP and MIQP problems formulated as multi-parametric MILPs (mp-MILPs) and mp-MIQPs. Such a framework allows for computing the worst-case computational complexity of standard B&B-based MILP and MIQP solvers, quantified by metrics such as the total number of LP/QP iterations and B&B nodes. These results are highly relevant for real-time hybrid MPC applications. In this paper, we extend this framework by developing parallel, domain-decomposition versions of the previously proposed algorithm, allowing it to scale to larger problem sizes and enable the use of high-performance computing (HPC) resources. Furthermore, to reduce peak memory consumption, we introduce two modifications to the existing (serial) complexity certification framework, integrating them into the proposed parallel algorithms. Numerical experiments show that the parallel algorithms significantly reduce computation time while maintaining the correctness of the original framework. © 2025, CC BY.

关键词： Mixed-integer linear programming

Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics

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arXiv 2025年

作者： He, Zhiyu Bolognani, Saverio Dörfler, Florian Muehlebach, Michael Max Planck Institute for Intelligent Systems Germany Automatic Control Laboratory ETH Zürich Switzerland

Distribution shifts have long been regarded as troublesome external forces that a decision-maker should either counteract or conform to. An intriguing feedback phenomenon termed decision dependence arises when the deployed decision affects the environment and alters the data-generating distribution. In the realm of performative prediction, this is encoded by distribution maps parameterized by decisions due to strategic behaviors. In contrast, we formalize an endogenous distribution shift as a feedback process featuring nonlinear dynamics that couple the evolving distribution with the decision. Stochastic optimization in this dynamic regime provides a fertile ground to examine the various roles played by dynamics in the composite problem structure. To this end, we develop an online algorithm that achieves optimal decision-making by both adapting to and shaping the dynamic distribution. Throughout the paper, we adopt a distributional perspective and demonstrate how this view facilitates characterizations of distribution dynamics and the optimality and generalization performance of the proposed algorithm. We showcase the theoretical results in an opinion dynamics context, where an opportunistic party maximizes the affinity of a dynamic polarized population, and in a recommender system scenario, featuring performance optimization with discrete distributions in the probability simplex. © 2025, CC BY.

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Impact Time Constrained Guidance with Bounded Field-of-View and Input

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Impact Time Constrained Guidance with Bounded Field-of-View ...

AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Singh, Swati Kumar, Shashi Ranjan Mukherjee, Dwaipayan Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai400 076 India Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai400 076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article proposes a guidance scheme for stationary targets to achieve time-constrained interception at a desired time, considering the bounded field-of-view capability of seekerequipped interceptors and the physical limits of the actuator. Actuator saturation is a crucial problem in physical systems, often resulting in performance degradation. However, the actuator limitations are usually known to the designer, therefore, augmenting these constraints into the guidance design may enhance performance. The time-to-go error-based approach is used to satisfy the field-of-view constraint;further, the engagement kinematics are augmented with an input saturation model to incorporate the lateral acceleration constraints. Subsequently, the guidance strategy that constrains the lateral acceleration and the time-to-go values within their respective bounds is derived using Lyapunov stability concepts and the backstepping technique. Furthermore, a multi-stage approach is suggested to expand the achievable range of impact time. Numerical simulations are performed to validate the efficacy of the proposed scheme for different initial engagement geometries. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Backstepping

Multi-agent Collision Avoidance Based on Buffered Voronoi Cells and B-Splines 16th

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Multi-agent Collision Avoidance Based on Buffered Voronoi C...

16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： Dinh, Cong Khanh Prodan, Ionela Stoican, Florin LCIS Valence26000 France Department of Automatic Control and Systems Engineering National University of Science and Technology "Politehnica" Bucharest 313 Splaiul Independenţei Bucharest060042 Romania

ISBN: (纸本)9783031817236

This paper tackles the challenging issue of collision avoidance among multiple dynamical agents, a problem known for its non-convex nature and computational complexity. Our proposed solution involves decomposing the space into time-varying Voronoi cells with buffer zones, exploiting the versatility of B-splines to reconfigure trajectories when collisions are predicted. This approach is integrated into a Model Predictive control (MPC) framework, implemented in a distributed manner where agents communicate predicted control point sequences defining the B-spline curves. Through simulation testing across various scenarios, our approach demonstrates significant promise, paving the way for experimental validation and real-world applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive control systems