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Showing 1 to 5 of 5 for “"Stochastic Model Predictive Control"”.
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Stochastic Model Predictive Control via Fixed Structure Policies
<p>In this work, the model predictive control problem is extended to include not only open-loop control sequences but also state-feedback control laws by directly optimizing parameters of a control policy. Additionally, continuous cost functions are developed to allow training of the control policy …
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Fast stochastic model predictive control under parametric uncertainties
Model predictive control (MPC) is widely applied in industry due to its ability to handle constraints explicitly Many processes in chemical engineering have a high number of states, but a relatively low number of inputs and outputs Input-output formulations of MPC employ process models, predicting …
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Optimal reservoir operation using stochastic model predictive control
… random external forcings that complicate theie control. In order to achieve optimal performance, these systems need to continually adapt to external disturbances in real time. This capability is provided by feedback based control strategies that derive an optimal control from the current state …
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Stochastic Optimization approaches for trading on financial and energy markets
… for a rather broad class of financial options a stochastic model predictive control (SMPC) approach is proposed for dynamically hedging a portfolio of underlying assets.After formulating the dynamic hedging problem as a stochastic control problem with a least-squares criterion, for plain vanilla …
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Threat Assessment and Proactive Decision-Making for Crash Avoidance in Autonomous Vehicles
… kinds of threats. Various driver behavior predictive models have been proposed in the literature for motion prediction. However, these models cannot be trusted entirely due to the human drivers' highly uncertain nature. This thesis proposes a novel trust-based driver behavior prediction and …