model predictive control
In this project, an LSTM-based Model Predictive Controller (LSTM-MPC), with 200 neurons of each layer, is designed to have a highly efficient control on the temperature. The resulted dataset is attached, for further considerations.
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The problem of cooling in rescue robots is similar to that of the entire domain of product development involving electronic systems. When considering mission-oriented rescue robots, this issue becomes more severe, as the tolerance to failure is remarkably low. While cooling is considered indispensable, the hazardous environmental condition of the scene of deployment, comprising of water, dust, toxic gases, or fire, constrains the choices of the method.
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This dataset is in support of my following Research papers
Preprint (Make sure you have read Caution) :
- Novel ß Transtibial Prosthetic 9-DoF Artificial Leg Adaptive Controller - Part I*
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When batteries supply behind-the-meter services such as arbitrage or peak load management, an optimal controller can be designed to minimize the total electric bill. The limitations of the batteries, such as on voltage or state-of-charge, are represented in the model used to forecast the system's state dynamics. Control model inaccuracy can lead to an optimistic shortfall, where the achievable schedule will be costlier than the schedule derived using the model.
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548 Views