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Model-Free Predictive Control and Its Relation to Parameter-Estimation-Based Predictive Control
2019 SICE International Symposium on Control Systems (SICE ISCS), 2019Model-free predictive control is a method of predictive control that utilizes the measured input/output data of a controlled system instead of using mathematical models. In general, the simplest way to obtain a mathematical model is to estimate its parameters by fixing its structure, referred to as parameter-estimation-based predictive control in this ...
Nicha Chaovalit, Shigeru Yamamoto
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Design of a model‐free controller based on predictive functional control
Electronics and Communications in JapanAbstractIntelligent‐PID (i‐PID) control proposed by Fliess is a simple control algorithm. The controller is designed based on ultra‐local model, and consisted of PID type controller and derivatives of reference signal and controlled variables. Authors have considered discrete i‐PID controller and its properties, and one of the result was that PD ...
Yoichiro Ashida, Masaru Katayama
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Modulated Model-free Predictive Control of PMSM Drive System
2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019Modulated model predictive control (MMPC) is an effective strategy to improve the steady-state control performance for a permanent magnet synchronous motor (PMSM) drive system. However, the theoretical basis for the duty cycles calculation of basic voltage vectors in this method is insufficient.
Wang Yuchen +5 more
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Distributed Model-Free Adaptive Predictive Control for Urban Traffic Networks
IEEE Transactions on Control Systems Technology, 2022Data-driven control without using mathematical models is a promising research direction for urban traffic control due to the massive amounts of traffic data generated every day. This article proposes a novel distributed model-free adaptive predictive control (D-MFAPC) approach for multiregion urban traffic networks.
Dai Li, Bart De Schutter
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Model-Free Finite Set Predictive Voltage Control of Induction Motor
2021 12th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC), 2021The emerging theory of model-free control (MFC) has presented an ultra-local modeling approach for systems, which is independent of the system parameters. This paper proposes a model-free based predictive voltage control for the induction motor (IM) drive. In this method, replacing the classic mathematical model of IM with an ultra-local model provides
Mahdi S. Mousavi +4 more
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A model-free predictive controller with Laguerre polynomials
This paper presents a combined subspace system identification and model predictive-control algorithm with Laguerre orthonormal functions. The term commonly used for such an approach is called model-free predictive control. The main contribution of this paper is to investigate the effect of non-stationary disturbance on the stability and performance of ...Barry, T., Wang, Liuping
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Model-free predictive control for power decoupling integrated PFC converters
2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019An innovative integration of the second-order ultra-local model and deadbeat predictive control tactic is proposed to reinforce the performance of the power decoupling circuit. Consequently, bulky electrolytic capacitors can be eliminated, and the reliability of PFC converter can be improved.
Xikang Dong +5 more
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Model-free predictive current control of a voltage source inverter
2015 IEEE 2nd International Future Energy Electronics Conference (IFEEC), 2015This work presents a model-free predictive current control (MFPCC) that is suitable for a voltage source inverter with a decoupled three-phase load. With this method, the load currents and the load current differences are available to predict the future load currents associated with eight possible switching states, generated by the inverter.
null Cheng-Kai Lin +4 more
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Polynomial regression based model-free predictive control for nonlinear systems
2016 55th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), 2016In this paper, we introduce model-free predictive control based on a polynomial regression expression for nonlinear systems. In contrast to conventional methods, model-free predictive control does not explicitly require a mathematical model of the controlled systems. In stead of the model, it utilizes massive stored and observed input/output dataset to
Hongran Li, Shigeru Yamamoto
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An improved model-free predictive current control of PWM rectifiers
2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017Model predictive current control (MPCC) is a powerful control strategy for the control of three-phase power converters. Conventional MPCC achieves good steady state performance and quick dynamic response by selecting the optimal voltage vector. However, this method is highly dependent on the accuracy of the model and parameters, which means that the ...
Yongchang Zhang, Jie Liu
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