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Entropy for incremental stability of nonlinear systems under disturbances

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arXiv 2022年

作者： Chong, Michelle S. The Control Systems Technology section The Department of Mechanical Engineering Eindhoven University of Technology Netherlands

Entropy notions for Ε-incremental practical stability and incremental stability of deterministic nonlinear systems under disturbances are introduced. The entropy notions are constructed via a set of points in state space which induces the desired stability properties, called an approximating set. We provide conditions on the system which ensures that the approximating set is finite. Lower and upper bounds for the two estimation entropies are computed. The construction of the finite approximating sets induces a robust state estimation algorithm for systems under disturbances using quantized and time-samples measurements. © 2022, CC BY-SA.

关键词： Entropy

controller confidentiality for nonlinear systems under sensor attacks

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arXiv 2022年

作者： Chong, Michelle S. The Control Systems Technology section The Department of Mechanical Engineering Eindhoven University of Technology Netherlands

controller confidentiality under sensor attacks refers to whether the internal states of the controller can be estimated when the adversary knows the model of the plant and controller, while only having access to sensors, but not the actuators. We show that the controller's state can be estimated accurately when the nonlinear closed-loop system is detectable. In the absence of detectability, controller confidentiality can still be breached with a periodic probing scheme via the sensors under a robust observability assumption, which allows for the controller's state to be estimated with arbitrary accuracy during the probing period, and with bounded error during the non-probing period. Further, stealth can be maintained by choosing an appropriate probing duration. This study shows that the controller confidentiality for nonlinear systems can be breached by balancing the estimation precision and the stealthiness of the adversary. © 2022, CC BY-SA.

关键词： controllers

Fixed-time adaptive parameter estimation for magnetostrictive actuated positioning system

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Fixed-time adaptive parameter estimation for magnetostrictiv...

第43届中国控制会议

作者： Shengbin Wu Jing Na Yingbo Huang Faxiang Zhang Xinkai Chen Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Department of Electronic and Information Systems Shibaura Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

An adaptive parameter estimation method that ensures fixed-time convergence is proposed for micro-nano positioning system driven by magnetostrictive actuator(i.e., magnetostrictive actuated positioning system). Firstly, the hysteresis nonlinearity of the magnetostrictive actuated positioning system is characterized using the generalized Prandtl–Ishlinskii(GPI) ***, the low-pass filter is introduced to design the adaptive estimation law driven by the estimation error, by which the unmeasured intermediate hysteresis variable can be avoided, and the estimation error converges to zero within a fixed time. Specifically,a modified error variable is designed to deal with the influence of the regression vector, thereby improving convergence performance and simplifying parameter adjustment. Finally, the effectiveness of the presented method is verified by simulation and experimental outcomes.

关键词： Adaptive parameter estimation Fixed-time convergence Magnetostrictive actuator Micro/nano positioning system

Bias Considerations When Identifying systems from Noisy Input-Output Data — Extensions to General Model Structures

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Bias Considerations When Identifying Systems from Noisy Inpu...

European control Conference (ECC)

作者： Torsten Söderström Umberto Soverini Department of Information Technology Division of Systems and Control Uppsala University Uppsala Sweden Dept of Electrical Electronic and Information Engineering University of Bologna Bologna Italy

Standard identification methods give biased parameter estimates when recorded signals are corrupted by noise on both input and output sides. In previous papers it has been shown that the bias is significant in case th... 详细信息

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

关键词： Noise Transfer functions Europe control systems Data models Noise shaping Error correction codes

Parameter-Varying Feedforward control: A Kernel-Based Learning Approach

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arXiv 2025年

作者： van Haren, Max Blanken, Lennart Oomen, Tom Department of Mechanical Engineering Control Systems Technology Section Eindhoven University of Technology Groene Loper 5 Eindhoven5612 AE Netherlands Sioux Technologies Esp 130 Eindhoven5633 AA Netherlands Delft Center for Systems and Control Delft University of Technology Mekelweg 2 Delft2628 CN Netherlands

The increasing demands for high accuracy in mechatronic systems necessitate the incorporation of parameter variations in feedforward control. The aim of this paperis to develop a data-driven approach for direct learning of parameter-varying feedforward control to increase tracking performance. The developed approach is based on kernel-regularized function estimation in conjunction with iterative learning to directly learn parameter-varying feedforward control from data. This approach enables high tracking performance for feedforward control of linear parameter-varying dynamics, providing flexibility to varying reference tasks. The developed framework is validated on a benchmark industrial experimental setup featuring a belt-driven carriage. © 2025, CC BY-NC-ND.

关键词： Mechatronics

Performance Analysis of Multirate systems: A Direct Frequency-Domain Identification Approach

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arXiv 2025年

Frequency-domain performance analysis of intersample behavior in sampled-data and multirate systems is challenging due to the lack of a frequency-separation principle, and systematic identification techniques are lacking. The aim of this paper is to develop an efficient technique for identifying the full intersample performance in the frequency-domain for closed-loop multirate systems, in particular the Performance Frequency Gain (PFG). Through local modeling techniques, aliased frequency components are effectively disentangled when identifying the PFG, which is directly facilitated by frequency-lifting the multirate system to a multivariable time-invariant representation. The developed method accurately and directly identifies the PFG in a single identification experiment. Finally, the developed method is experimentally validated on a prototype motion system, showing accurate identification of frequency-domain representations for the multirate system, including the PFG. © 2025, CC BY-NC-ND.

关键词： Frequency domain analysis

Sensor Fusion for Glucose Monitoring systems

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IFAC-PapersOnLine 2023年第2期56卷 11527-11532页

作者： Mohamad Al Ahdab Karim Davari Benam Hasti Khoshamadi Anders Lyngvi Fougner Sebastien Gros Section of Automation and Control Department of Electronic Systems Aalborg University Aalborg Øst Denmark Department of Engineering Cybernetics Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology (NTNU) O. S. Bragstads Plass 2D 7034 Trondheim Norway

A fully automated artificial pancreas (AP) requires accurate blood glucose (BG) readings. However, many factors can affect the accuracy of commercially available sensors. These factors include sensor artifacts due to the pressure on surrounding tissues, connection loss, and poor calibration. The AP may administer an incorrect insulin bolus due to inaccurate sensor data when the patient is not supervising the system. The situation can be even worse in animal experiments because animals are eager to play with the sensor and apply pressure. In this study, we propose and derive a Multi-Model Kalman Filter with Forgetting Factor (MMKFF) for the problem of fusing information from redundant subcutaneous glucose sensors. The performance of the developed MMKFF was assessed by comparing it against other Kalman Filter (KF) strategies on experimental data obtained in two different animals. The developed MMKFF was shown to provide a reliable fused glucose reading. Additionally, compared to the other KF approaches, the MMKFF was shown to be better able to adjust to changes in the accuracy of the glucose sensors.

关键词： Developments in measurement signal processing Diabetes

Lifted Frequency-Domain Identification of Closed-Loop Multirate systems: Applied to Dual-Stage Actuator Hard Disk Drives

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arXiv 2025年

作者： van Haren, Max Mae, Masahiro Blanken, Lennart Oomen, Tom Department of Mechanical Engineering Control Systems Technology Section Eindhoven University of Technology Groene Loper 5 Eindhoven5612 AE Netherlands Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo113-8656 Japan Sioux Technologies Esp 130 Eindhoven5633 AA Netherlands Delft Center for Systems and Control Delft University of Technology Mekelweg 2 Delft2628 CN Netherlands

Frequency-domain representations are crucial for the design and performance evaluation of controllers in multirate systems, specifically to address intersample performance. The aim of this paperis to develop an effective frequency-domain system identification technique for closed-loop multirate systems using solely slow-rate output measurements. By indirect identification of multivariable time-invariant representations through lifting, in combination with local modeling techniques, the multirate system is effectively identified. The developed method is capable of accurate identification of closed-loop multirate systems within a single identification experiment, using fast-rate excitation and inputs, and slow-rate outputs. Finally, the developed framework is validated using a benchmark problem consisting of a multivariable dual-stage actuator from a hard disk drive, demonstrating its applicability and accuracy. © 2025, CC BY-NC-ND.

关键词： Frequency estimation

Accelerating soft-constrained MPC for linear systems through online constraint removal

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arXiv 2024年

作者： Nouwens, S.A.N. Paulides, M.M. Heemels, W.P.M.H. Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Department of Radiotherapy Erasmus University Medical Center Cancer Institute Rotterdam Netherlands

Optimization-based controllers, such as Model Predictive control (MPC), have attracted significant research interest due to their intuitive concept, constraint handling capabilities, and natural application to multi-input multi-output systems. However, the computational complexity of solving a receding horizon problem at each time step remains a challenge for the deployment of MPC. This is particularly the case for systems constrained by many inequalities. Recently, we introduced the concept of constraint-adaptive MPC (ca-MPC) to address this challenge for linear systems with hard constraints. In ca-MPC, at each time step, a subset of the constraints is removed from the optimization problem, thereby accelerating the optimization procedure, while resulting in identical closed-loop behavior. The present paper extends this framework to soft-constrained MPC by detecting and removing constraints based on sub-optimal predicted input sequences, which is rather easy for soft-constrained MPC due to the receding horizon principle and the inclusion of slack variables. We will translate these new ideas explicitly to an offset-free output tracking problem. The effectiveness of these ideas is demonstrated on a two-dimensional thermal transport model, showing a three order of magnitude improvement in online computational time of the MPC scheme. © 2024, CC BY-NC-ND.

关键词： Predictive control systems