model predictive controller is widely used in industrial plants. uncertainty is one of the critical issues in real systems. in this paper, the direct adaptive simplified model predictive control (smpc) is proposed for unknown or time varying plants with uncertainties. by estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

In dealing with model predictive controllers (MPC), controller tuning is a key design step. Various tuning methods are proposed in the literature which can be categorized as heuristic, numerical and analytical methods. Among the available tuning methods, analytical approaches are more interesting and useful. This paper is based on a proposed analytical MPC tuning approach for plants can be appr...

Objective clinical analyses are required to evaluate balance control performance. To this outcome, it is relevant study experimental protocols and develop devices that can provide reliable information about the ability of a subject maintain balance. Whereas most applications available in literature on market involve shifting tilting base support, system presented paper based direct application ...

The present sought to draw a comparison between Model Predictive Control performance and two other controllers named Simple PI and Selective PI in controlling large-scale natural gas transport networks. A nonlinear dynamic model of representative gas pipeline was derived from pipeline governing rules and simulated in SIMULINK® environment of MATLAB®. Control schemes were designed to provide a s...