A Non-Iterative Approach to Direct Data-Driven Control Design of MIMO LTI Systems
IEEE Access, 2023 This paper proposes a non-iterative direct data-driven technique that deals with linear time-invariant (LTI) controller design by directly identifying the controller from input-output data without using plant identification.
Mohammad Abuabiah +3 more
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Direct data-driven control approach of reference shaping for two degree of freedom control
SICE Journal of Control, Measurement, and System Integration, 2022 In this study, we propose a novel data-driven approach for control of two degrees of freedom systems. The proposed method uses one-shot experimental data to derive the reference governor for improving control performance.
Motoya Suzuki, Osamu Kaneko
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Data-Driven Gradient Descent Direct Adaptive Control for Discrete-Time Nonlinear SISO Systems [PDF]
Electronics, 2014 A novel data-driven gradient descent (GD) adaptive controller, for discrete-time single-input and single output (SISO) systems, is presented. The controller operates as the least mean squares (LMS) algorithm, applied to a nonlinear system with feedback ...
Igor R. Krcmar +2 more
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A Deep Q-Learning Direct Torque Controller for Permanent Magnet Synchronous Motors
IEEE Open Journal of the Industrial Electronics Society, 2021 Torque control of electric drives is a challenging task, as high dynamics need to be achieved despite different input and state constraints while also pursuing secondary objectives, e.g., maximizing power efficiency. Whereas most state-of-the-art methods
Maximilian Schenke, Oliver Wallscheid
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Machine Learning for Monitoring and Control of Ngl Recovery Plants
Chemical Engineering Transactions, 2021 In this contribution, the monitoring and control problem of the natural gas liquids (NGL) extraction process is addressed by exploiting a data-driven approach.
Marta Mandis +4 more
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On the Role of Regularization in Direct Data-Driven LQR Control
2022 IEEE 61st Conference on Decision and Control (CDC), 2022 The linear quadratic regulator (LQR) problem is a cornerstone of control theory and a widely studied benchmark problem. When a system model is not available, the conventional approach to LQR design is indirect, i.e., based on a model identified from data.
Dorfler, F, Tesi, P, De Persis, C
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Formation Control of Non-Holonomic Mobile Robots: Predictive Data-Driven Fuzzy Compensator
Mathematics, 2023 A key research topic in the field of robotics is the formation control of a group of robots in trajectory tracking problems. Using organized robots has many advantages over using them individually, such as efficient use of resources, increased ...
Jinfeng Wang +5 more
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Direct Data-Driven Control of Linear Time-Varying Systems
IEEE Transactions on Automatic Control, 2023 Considering discrete-time linear time-varying systems with unknown dynamics, controllers guaranteeing bounded closed-loop trajectories, optimal performance and robustness to process and measurement noise are designed via convex feasibility and optimisation problems involving purely data-dependent linear matrix inequalities.
Benita Nortmann, Thulasi Mylvaganam
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An Online Adaptation Strategy for Direct Data-driven Control
IFAC-PapersOnLine, 2023 This work has been accepted for presentation at IFAC World Congress ...
Johannes Teutsch +4 more
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Noniterative Data-Driven Gain-Scheduled Controller Design Based on Fictitious Reference Signal
IEEE Access, 2023 This paper proposes a noniterative direct data-driven gain-scheduled control. Gain-scheduled proportional–integral–derivative (PID) control is one of the most popular approaches for nonlinear systems.
Shuichi Yahagi, Itsuro Kajiwara
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