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MPCMinor Planet Center (IAU)
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References in periodicals archive ?
Among these, the enhanced Model Predictive Control (eMPC) algorithm proved to be efficient and safe in several multicenter clinical studies.
This research proposes an economic nonlinear model predictive control strategy and EKF engine state estimation for SI engine IMEP control.
Therefore, receding horizon optimal control, also called Model Predictive Control (MPC), is used here to design the controller since MPC integrates model-based prediction of vehicle states into optimal control strategy [14].
Installed in the MEGADRIVE-LCI, the MPTC uses a control algorithm based on Model Predictive Control that ensures the operation of the drive during power and grid disturbances in order to provide the compressor with partial torque, preventing the compressor from going into surge.
Along these same lines, Model Predictive Control (MPC) strategies have been utilized to control the energy fows between generator, load, and a hybrid ES [6].
These requirements are met by using Model Predictive Control (MPC), which is naturally suited for control problems requiring constraint management [1] [2].
On the other hand, the application of Model Predictive Control (MPC) for cruise in heavy duty applications has been studied in many works, see for example [2, 3 and 4] and references therein with indication of fuel economy benefit of this technology.
Authors Li and Zheng present readers with a comprehensive examination of distributed model predictive control (DMPC), itAEs basic concepts, technologies, and implementation in plant-wide systems.
Model predictive control (MPC) is based on the prediction of future behaviour of the drive and then choosing the best action to fulfil given requests.
Application of Stochastic Model Predictive Control to Modeling Driver Steering Skills," SAE Int.
Nonlinear systems and their control can be found in many areas, for example using nonlinear model predictive control in automotive industry [6], receding horizon control of vehicle formation [16], stochastic nonlinear model predictive control in film deposition [2], nonlinear PI control of wind turbine [14], neural network for model predictive control of continuous reactor [23], nonlinear model predictive control of robot manipulator [18], steam valve control of multi- machine power systems [1], or controlling galloping vibrations [4], nonlinear control of boost converter [19], adaptive control of nonlinear finance system [5], to name some.
In the above section, a sufficient condition to ensure the asymptotic stability of the robust model predictive control with additive gain perturbations is discussed.
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