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Relevant bibliographies by topics / Rmpc

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Journal articles

Academic literature on the topic 'Rmpc'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Rmpc"

1

Li, Zexin, Feng Xu, Dongsheng Guo, Pingjiang Wang, and Bo Yuan. "New P-type RMPC Scheme for Redundant Robot Manipulators in Noisy Environment." Robotica 38, no. 5 (2019): 775–86. http://dx.doi.org/10.1017/s0263574719001036.

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SUMMARYRepetitive motion planning and control (RMPC) is a significant issue in the research of redundant robot manipulators. Moreover, noise from rounding error, truncation error, and robot uncertainty is an important factor that greatly affects RMPC schemes. In this study, the RMPC of redundant robot manipulators in a noisy environment is investigated. By incorporating the proportional and integral information of the desired path, a new RMPC scheme with pseudoinverse-type (P-type) formulation is proposed. Such a P-type RMPC scheme possesses the suppression of constant and bounded time-varying

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2

Eedara, Aswani K., Chandra S. Koritala, and Srinivasa R. Rayapudi. "Refined Model Predictive Control of Back-to-back 3L-NPC Converter Interfacing a PMSG Based WECS with Grid for Blocking High Jumps in Voltages." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 1 (2020): 43–51. http://dx.doi.org/10.2174/2213111607666190124093856.

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Background: For controlling a back-to-back three-level (3L) Neutral-Point-Clamped (NPC) converter of a Permanent-Magnet Synchronous Generator (PMSG) based Wind Energy Conversion System (WECS), a Refined Model Predictive Control (RMPC) strategy is presented in this paper. Methods: The RMPC strategies of PMSG-side and network-side converters aim at prevention of the high jumps in line and pole voltages of both the converters. A suitable subset of Switching States (SSs), which can prevent these high jumps, is predetermined for each SS. In each control cycle, the RMPC algorithm determines an optim

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3

Wang, Di, Xiao Wu, and Jiong Shen. "An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant." Energies 13, no. 15 (2020): 3775. http://dx.doi.org/10.3390/en13153775.

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Regulating performance of the main steam temperature (MST) system concerns the economy and safety of the coal-fired power plant (CFPP). This paper develops an offset-free offline robust model predictive control (RMPC) strategy for the MST system of CFPP. Zonotope-type uncertain model is utilized as the prediction model in the proposed RMPC design owing to its features of higher accuracy, compactness of representation and less complexity. An offline RMPC aiming at the system robustness and computational efficiency is then developed to maintain the desired steam temperature in case of wide opera

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4

Moradi, Shahab M., Ahmad Akbari, and Mehdi Mirzaei. "An offline LMI-based robust model predictive control of vehicle active suspension system with parameter uncertainty." Transactions of the Institute of Measurement and Control 41, no. 6 (2018): 1699–711. http://dx.doi.org/10.1177/0142331218787599.

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In vehicle active suspension design, it is desirable to improve performance criteria, such as ride comfort and road holding, subject to constraints on some states and control input. To tackle this constrained optimization problem, an offline robust model predictive control (RMPC) using linear matrix inequalities (LMIs) is proposed. In conventional model predictive control (MPC), an optimization problem is solved at each sampling interval, which might lead to task overrun and hence could prevent its real-time implementation. The proposed offline RMPC approach overcomes the problem by offline op

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5

Minh, Vu Trieu, and Fakhruldin Bin Mohd Hashim. "Robust Model Predictive Control Schemes for Tracking Setpoints." Journal of Control Science and Engineering 2010 (2010): 1–9. http://dx.doi.org/10.1155/2010/649461.

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This paper briefly reviews the development of nontracking robust model predictive control (RMPC) schemes for uncertain systems using linear matrix inequalities (LMIs) subject to input saturated and softened state constraints. Then we develop two new tracking setpoint RMPC schemes with common Lyapunov function and with zero terminal equality subject to input saturated and softened state constraints. The novel tracking setpoint RMPC schemes are able to stabilize uncertain systems once the output setpoints lead to the violation of the state constraints. The state violation can be regulated by cha

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6

Al-Azzawi, Waleed Khalid. "Artificial pancreas techniques based on robust model predictive controller." IAES International Journal of Robotics and Automation (IJRA) 8, no. 3 (2019): 189. http://dx.doi.org/10.11591/ijra.v8i3.pp189-193.

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Diabetes is known as the major cause of death in the world leading to kidney, retinopathy and cardiovascular diseases as well. In this paper, a Robust Model Predictive Controller (RMPC) is introduced to design artificial pancreas that solved the model uncertainty and keep the blood glucose level in the normal range by regulating the size of insulin infusion from pump based on RMPC. The simulation results will present a good performance of the proposed controller to avoid disturbance and robustness against uncertainties.

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7

Jarmolowitz, Fabian, Christopher Groß-Weege, Thomas Lammersen, and Dirk Abel. "Robust Output Model Predictive Control of an Unstable Rijke Tube." Journal of Combustion 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/927345.

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This work investigates the active control of an unstable Rijke tube using robust output model predictive control (RMPC). As internal model a polytopic linear system with constraints is assumed to account for uncertainties. For guaranteed stability, a linear state feedback controller is designed using linear matrix inequalities and used within a feedback formulation of the model predictive controller. For state estimation a robust gain-scheduled observer is developed. It is shown that the proposed RMPC ensures robust stability under constraints over the considered operating range.

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8

Wu, Xuan, Hui Wang, Xiaofang Yuan, Shoudao Huang, and Derong Luo. "Design and Implementation of Recursive Model Predictive Control for Permanent Magnet Synchronous Motor Drives." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/431734.

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In order to control the permanent-magnet synchronous motor system (PMSM) with different disturbances and nonlinearity, an improved current control algorithm for the PMSM systems using recursive model predictive control (RMPC) is developed in this paper. As the conventional MPC has to be computed online, its iterative computational procedure needs long computing time. To enhance computational speed, a recursive method based on recursive Levenberg-Marquardt algorithm (RLMA) and iterative learning control (ILC) is introduced to solve the learning issue in MPC. RMPC is able to significantly decrea

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9

Cavalca, Mariana Santos Matos, Roberto Kawakami Harrop Galvão, and Takashi Yoneyama. "Robust Model Predictive Control Using Linear Matrix Inequalities for the Treatment of Asymmetric Output Constraints." Journal of Control Science and Engineering 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/485784.

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One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC) strategies based on linear matrix inequalities (LMIs). However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output

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10

Daoud, R. M., S. I. Kolesnikov, A. A. Kuzina, K. Sh Kaseev, and Yu V. Akimenko. "Development of Regional Maximum Permissible Concentrations of Oil in the Soils of Arid Ecosystems in the South of Russia." Ecology and Industry of Russia 23, no. 9 (2019): 66–71. http://dx.doi.org/10.18412/1816-0395-2019-9-66-71.

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Objective difficulties and incorrect use of a single maximum permissible concentration of oil for all soils of Russia are considered. It is more expedient to use regional maximum permissible concentrations (RMPC) of oil in different soils of Russia, taking into account their regional ecological-genetic and ecological-geographical features. RMPC of oil in arid soils of the South of Russia was developed on the basis of violation of their ecosystem functions. Regional MPC of oil in dark chestnut soils (haplic kastanozems) is 0.40 % of oil in soil, chestnut (haplic kastanozems) and light chestnut

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