Model Predictive Control (MPC) has emerged as a versatile and robust strategy in modern control engineering, enabling controllers to predict future system behaviour and optimise performance over a ...
Dynamic optimisation and model predictive control (MPC) are at the forefront of modern process systems engineering, offering robust methodologies to address the challenges posed by time-varying ...
Distillation columns are extensively deployed in the chemical process industries when there is a need for separation of components that have different boiling points. Typically, a mixture of ...
Distributed model predictive control (DMPC) offers a computationally efficient alternative to centralized model predictive control (CMPC) for enabling the optimal control of industrial process systems ...
Model Predictive Control (MPC) is a modern feedback law that generates the control signal by solving an optimal control problem at each sampling time. This approach is capable of maximizing a certain ...
Within this talk the advantages of using intensified Design of experiments (iDoE) in combination with hybrid modeling will be demonstrated. In detailed upstream and downstream showcases the applied ...
The application of modeling tools to better understand and control bioprocess development and manufacturing has become a hot topic within the last few years. However, what do we actually need to ...
The air conditioner compressor motor driver as shown in Fig.1 utilizes advanced model-free predictive control technology, ensuring efficient and stable operation under varying load conditions.
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