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UKACC International Conference on control (control)

作者： J. A. Rossiter Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

There has a been a growing interest in virtual laboratories as a supplement to hardware laboratories in supporting student learning and experience. This paper focuses specifically on virtual laboratories built using the MATLAB environment and highlights some recent developments. Specifically, these virtual laboratories aim to give users an overview of the core content of an entire 1st course in control in a single virtual laboratory interface. This paper highlights two such laboratories and shows how they can be used to supplement other learning resources and activities.

关键词： Laboratories Hardware Matlab

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

arXiv

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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

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A non-iterative approach to Linear Quadratic Static Output Feedback

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IFAC-PapersOnLine 2023年第2期56卷 9540-9545页

作者： Hadriano Morales Escamilla Paul Trodden Visakan Kadirkamanathan Department of Automatic Control and Systems Engineering ACSE The University of Sheffield Sheffield UK

This paper considers the problem of static output feedback (SOF) synthesis for linear time-invariant (LTI) systems. Static output feedback, and more generally structured controller synthesis, is of special interest to any industrial application where a reduced-order controller is desired, e.g., high-order systems, or a specific structure is to be imposed, i.e., distributed/decentralised control. A simple two-step process is proposed, solving one Riccati equation and one optimisation problem with linear matrix inequality (LMI) constraints, enabled via a dilation using the distance to the full-state feedback optimum gain. Numerical analysis shows considerable computational savings, with negligible differences in the performance, when compared to current iterative methods.

关键词： Output feedback control controller constraints and structure Linear multivariable systems Linear matrix inequalities Optimal control Static controller synthesis S-procedure

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Solidity Effects on Small Hybrid Savonius-Darrieus Wind Turbine Performance: Experimental Analysis with NREL S809 Airfoil 10

Solidity Effects on Small Hybrid Savonius-Darrieus Wind Turb...

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10th International Conference on Applied System Innovation, ICASI 2024

作者： Irawan, Elysa Nensy Shibuya, Kai Yamashita, Ken-Ichiro Fujita, Goro Shibaura Institute of Technology Functional Control Systems Tokyo Japan Universitas Pendidikan Indonesia Department of Mechatronics and Artificial Intelligence Bandung Indonesia Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan Salesian Polytechnic Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350394924

This experimental study uses the NREL S809 airfoil to evaluate how solidity affects the performance of a hybrid Savonius-Darrieus wind turbine. To assess its effects on power coefficient, starting torque, and other performance metrics, solidity is varied with values of 0.5, 0.75, and 1. The model is made using 3D printing with PLA material and has internal and external rotor radii of 5cm and 10cm, respectively. The experiments are conducted in a wind tunnel with a testing chamber cross-sectional area measuring $30\mathrm{x}30$ cm between 3-12 m/s of wind speed variation. Overall, the model with a solidity of 0.75 demonstrates the best performance, showcasing both favorable initial torque and the highest maximum power coefficient of 0.33 at TSR 2.1. © 2024 IEEE.

关键词： Wind turbines

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Disturbance Observer-Based Data Driven Model Predictive Tracking control of Linear systems

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IEEE Access 2023年 11卷 88597-88608页

作者： Farbood, Mohsen Echreshavi, Zeinab Shasadeghi, Mokhtar Mobayen, Saleh Skruch, Pawel Shiraz University of Technology Department of Electrical and Electronics Engineering Shiraz71557-13876 Iran University of Zanjan Department of Electrical Engineering Zanjan45371-38791 Iran National Yunlin University of Science and Technology Douliou Graduate School of Intelligent Data Science Yunlin640301 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper introduces a new data-driven MPC structure based on two offline and online parts to achieve the robust and constrained performance in an optimal scheme. In the first step, according to the model matching condition, an offline data-driven controller is designed to reach the tracking performance. In addition, to reduce the effects of the external disturbance, a data-driven-based disturbance observer is presented to estimate the external disturbance. Therefore, the robustness against the external disturbances is achieved in an offline procedure. Then, a data-driven model predictive control (MPC) is structured based on a data-driven-based model of a stabilized system. In other words, the overall controller is configured such that the limitations of the system states and control input are considered in the control design process. Moreover, by employing the move blocking strategy, the online computational burden of the suggested controller is greatly reduced. To further improve of the feasibility problem, an ellipsoidal terminal (ET) constraint is considered. The rows number of the blocking matrix influences on the ET set which leads to feasibility enhancement. So, the main contributions of the presented data-driven controller are feasibility improvement and reducing online computational burden in an optimal and constrained scheme which are illustrated in the simulation section. © 2013 IEEE.

关键词： Linear systems

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

arXiv

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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

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Optimized Spatial Filter Selection for Transfer Learning in Brain-Computer Interface

Optimized Spatial Filter Selection for Transfer Learning in ...

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Metrology for Extended Reality, Artificial Intelligence and Neural engineering (MetroXRAINE), IEEE International Conference on

作者： Mohamed A A Mohamed Joshua Giles Mahnaz Arvaneh Automatic control and Systems Engineering Department University of Sheffield Sheffield UK

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

The Common Spatial Patterns (CSP) algorithm has shown great efficacy in extracting features for Brain-Computer Interfaces (BCIs), particularly in motor imagery BCIs. However, CSP performs poorly when dealing with limited labeled data, which leads to long calibration time at the beginning of each session. To overcome this challenge, we leverage source data, i.e., labeled data from other subjects, to transfer knowledge across subjects. This work proposes a novel approach termed Scaled and Warped CSP-based Transfer Learning (SW-CSP-TL). This method aligns source data with the temporal and amplitude structure of target data before computing CSP filters, ensuring optimization for capturing discriminative features relevant to the target domain. We evaluate the proposed SW-CSP-TL algorithm using the publicly available dataset 2a from BCI Competition IV and compare its performance with that of the classical CSP algorithm and the transfer learning CSP algorithm (CSP-TL) without amplitude scaling and temporal warping. Our algorithm exhibits superior performance particularly when the training data size is relatively small. Results demonstrate that for 5 and 15 training trials per class from the target session, SW-CSP-TL outperformed the classical CSP by an average of 10%, and 8%, respectively.

关键词： Training Transfer learning Training data Neural engineering Feature extraction Spatial filters Motors Brain-computer interfaces Standards Optimization

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Fault detection and diagnosis using the dynamic network framework ⁎

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IFAC-PapersOnLine 2024年第15期58卷 384-389页

作者： Yibo Shi Stefanie J.M. Fonken Paul M.J. Van den Hof Control Systems Group Department of Electrical Engineering Eindhoven University of Technology The Netherlands

A local model-based method for fault detection and diagnosis (FDD) in large-scale interconnected network systems is introduced, using models in a dynamic network framework. To this end, model validation methods are developed for validating single modules in a dynamic network, which are generalized from the classical auto- and cross-correlation tests for open- and closed-loop systems. Invalidation of the model can indicate the detection of a fault in the system. A fault diagnosis algorithm is developed that includes fault isolation and optimal placement of external excitation signals. Numerical illustrations demonstrate the method’s capability to detect a fault in a local module and isolate it within the entire network system.

关键词： Fault interconnected system dynamic network model validation correlation test

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

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

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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

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A Deep Learning Approach for Faults Recognition of Dissolved Oxygen Sensor in Wastewater Treatment Plants 28

A Deep Learning Approach for Faults Recognition of Dissolved...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Ghinea, Liliana Maria Miron, Mihaela Ratnaweera, Harsha Electrical Engineering and Electronics Faculty of Automation Computers Department of Automatic Control and Electrical Engineering Department Galaţi Romania Computers Electrical Engineering and Electronics Faculty of Automation Department of Computer Science and Information Technology Galaţi Romania Norwegian University of Life Sciences Faculty of Science and Technology Oslo Norway

ISBN: (纸本)9798350339918

Fault diagnosis in wastewater treatment plants (WWTPs) is important to protect communities and ecosystems from toxic elements discharged into water. In this sense, fault identification of sensors plays an important role as they are the key components of the water plants control, especially because environmental legislation is very strict when referring to failures or anomalies in WWTPs. This paper analyzes the performances of two Deep Learning models, a Feedforward Neural Network (FFNN) and a 1D Convolution Neural Network (1DCNN) for identifying five operating states of the dissolved oxygen (DO) sensor: normal and faulty (bias, stuck, spike and precision degradation faults). The experiments were conducted on the Benchmark Simulator Model No 2 (BSM2) developed by the IWA Task Group. The performance of the Deep Learning (DL) classifiers was evaluated via accuracy, precision, recall, and F1-score metrics. The best overall classification accuracy was obtained by FFNN, 98.32% for training and 98.30% for testing. © 2023 IEEE.

关键词： Wastewater treatment

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