Nonlinear Model Predictive Control for Cold Start Selective Catalytic Reduction

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...

Nonlinear Model Predictive Control

Robust Model Predictive Control for a Class of Discrete Nonlinear systems

This paper presents a robust model predictive control scheme for a class of discrete-time nonlinear systems subject to state and input constraints. Each subsystem is composed of a nominal LTI part and an additive uncertain non-linear time-varying function which satisfies a quadratic constraint. Using the dual-mode MPC stability theory, a sufficient condition is constructed for synthesizing the ...

Model-based Cold-start Speed Control Design for SI Engines

This paper presents a feedback deign approach to the cold-start speed control for spark ignition engines. First, in order to ensure successful combustion in the transient mode, a fuel injection controller is given based on the air charge estimation with inverse dynamics of fuel path, which is a dual sampling rate system, i.e. the estimation for the air charge is performed TDC-based, and the fue...

Nonparametric Nonlinear Model Predictive Control

−Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction ...