Nonlinear Model Predictive Control of the Hydraulic Fracturing Process

Model-Based Closed-Loop Control of the Hydraulic Fracturing Process

Improved Optimization Process for Nonlinear Model Predictive Control of PMSM

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

Predictive Control of Nonlinear Process

Concept of model based predictive control (MBPC) has been heralded as one of the most significant control developments in recent ten years. Wide range of choice of model structures, prediction horizon, and optimization criteria allows the designer to easily tailor MBPC to its application in industry. The main idea of Model Predictive Control (MPC) is the prediction of the output signal at each ...

Linear and Nonlinear Model Predictive Control of Quadruple Tank Process

In a multi input and output (MIMO) process mathematical modeling of the physical systems has gained importance due to the complexity of interactions within the system. All the parameters used in a model cannot be determined accurately. The major problem in a multivariable process is that loop interaction can arise and cause difficulty in feedback control design. This problem can be solved using...

Gaussian Process Model Predictive Control of Unknown Nonlinear Systems

MPC of an unknown system that is modelled by GP techniques is studied in this paper. Using GP, the variances computed during the modelling and inference processes allow us to take model uncertainty into account. The main issue in using MPC to control systems modelled by GP is the propagation of such uncertainties within the control horizon. In this paper, two approaches to solve this problem, c...