Results 11 to 20 of about 2,570,203 (288)
On Direct vs Indirect Data-Driven Predictive Control [PDF]
2021 60th IEEE Conference on Decision and Control (CDC), 2021 In this work, we compare the direct and indirect approaches to data-driven predictive control of stochastic linear time-invariant systems. The distinction between the two approaches lies in the fact that the indirect approach involves identifying a lower dimensional model from data which is then used in a certainty-equivalent control design, while the ...
Krishnan, Vishaal, Pasqualetti, Fabio
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When is FDI a Capital Flow? [PDF]
, 2006 In this paper we analyze the conditions under which a foreign direct investment (FDI) involves a net capital flow across countries. Frequently, foreign direct investment is financed in the host country without an international capital movement.
Marin, Dalia, Schnitzer, Monika
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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 model-reference control with Lyapunov stability guarantees [PDF]
2021 60th IEEE Conference on Decision and Control (CDC), 2021 In this work, we introduce a novel data-driven model-reference control design approach for unknown linear systems with fully measurable state. The proposed control action is composed by a static feedback term and a reference tracking block, which are shaped from data to reproduce the desired behavior in closed-loop.
Breschi V. +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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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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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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