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Model Predictive Control (MPC) Based BLDC Drive for Indian Drive Cycle
2023 IEEE 8th International Conference for Convergence in Technology (I2CT), 2023Brushless DC motor is used in variety of applications. It is one of the popular motors in the industry and automotive. This motor is often used in an electric vehicle due to its high efficiency and high torque to weight ratio.
Phatak Ketaki, M. Sindhu
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IEEE Transactions on Vehicular Technology, 2023
This paper studies the distributed dynamic event-triggered model predictive control (MPC) of vehicle platoon systems subject to denial-of-service (DoS) attacks and external disturbances.
Jicheng Chen, Hui Zhang, Guo-dong Yin
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This paper studies the distributed dynamic event-triggered model predictive control (MPC) of vehicle platoon systems subject to denial-of-service (DoS) attacks and external disturbances.
Jicheng Chen, Hui Zhang, Guo-dong Yin
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LSTM-MPC: A Deep Learning Based Predictive Control Method for Multimode Process Control
IEEE transactions on industrial electronics (1982. Print), 2023Modern industrial processes often operate under different modes, which brings challenges to model predictive control (MPC). Recently, most MPC related methods would establish prediction models independently for different modes, which results in their ...
Keke Huang +4 more
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TinyMPC: Model-Predictive Control on Resource-Constrained Microcontrollers
IEEE International Conference on Robotics and Automation, 2023Model-predictive control (MPC) is a powerful tool for controlling highly dynamic robotic systems subject to complex constraints. However, MPC is computationally demanding, and is often impractical to implement on small, resource-constrained robotic ...
Anoushka Alavilli +4 more
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IEEE Transactions on Intelligent Vehicles, 2023
Model predictive control (MPC) has been widely researched for automotive control. However, the real-world application of MPC for autonomous vehicles (AV) is still limited due to the high computational requirement of solving the real-time optimization ...
Zhao-Ying Zhou +2 more
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Model predictive control (MPC) has been widely researched for automotive control. However, the real-world application of MPC for autonomous vehicles (AV) is still limited due to the high computational requirement of solving the real-time optimization ...
Zhao-Ying Zhou +2 more
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Reinforcement Learning-Based Model Predictive Control for Discrete-Time Systems
IEEE Transactions on Neural Networks and Learning Systems, 2023This article proposes a novel reinforcement learning-based model predictive control (RLMPC) scheme for discrete-time systems. The scheme integrates model predictive control (MPC) and reinforcement learning (RL) through policy iteration (PI), where MPC is
Min Lin +3 more
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Model Predictive Control for Connected Vehicle Platoon Under Switching Communication Topology
IEEE transactions on intelligent transportation systems (Print), 2022Vehicular platoon control can effectively achieve group consensus, improve vehicular running safety and increase road capacity. However, some constraints exist in practical situations due to the limitations of traffic environment in time-varying metrics (
Pangwei Wang +5 more
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IEEE/CAA Journal of Automatica Sinica, 2022
Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the ...
Teng Li +5 more
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Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the ...
Teng Li +5 more
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MPC model based predictive control
UKACC Control 2006 Mini Symposia, 2006The presentation covers the practical implementation of a DeltaV MBPC on furnace control. It describes the importance of step tests and pseudo random binary sequence tests to obtain the process model and how the various tuning parameters affect the performance and robustness of the controller.
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Bioprocess Modelling for Learning Model Predictive Control (L-MPC)
2009Batch and Fed-Batch cultivation processes are used extensively in many industries where a major issue today is to reduce the production losses due to sensitivity to disturbances occurring between batches and within batches. In order to ensure consistent product quality by eliminating the influence of process disturbances it is very important to ...
María Antonieta Alvarez +2 more
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