首页|Researchers from National University of Singapore Report New Studies and Finding s in the Area of Machine Learning (Explicit Machine Learning-based Model Predict ive Control of Nonlinear Processes Via Multi-parametric Programming)
Researchers from National University of Singapore Report New Studies and Finding s in the Area of Machine Learning (Explicit Machine Learning-based Model Predict ive Control of Nonlinear Processes Via Multi-parametric Programming)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting out of Singapore, Singapore, by New sRx editors, research stated, "Machine learning-based model predictive control ( ML-MPC) has been developed to control nonlinear processes with unknown first-pri nciples models. While ML models can capture nonlinear dynamics of complex system s, the complexity of ML models leads to increased computation time for real-time implementation of ML-MPC." Financial supporters for this research include NRF-CRP Grant, MOE AcRF Tier 1 FR C Grant. Our news journalists obtained a quote from the research from the National Univer sity of Singapore, "To address this issue, in this work, we propose an explicit ML-MPC framework for nonlinear processes using multi-parametric programming. Spe cifically, a self-adaptive approximation algorithm is first developed to obtain a piecewise linear affine function that approximates the behaviors of ML models. Then, multiparametric quadratic programming (mpQP) problems are formulated to generate the solution map for states in discretized state-space. Furthermore, t o accelerate the implementation of explicit ML-MPC, a neighbor- first search alg orithm is developed."
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