Nonlinear model predictive control for improving range-based relative localization by maximizing observability

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...

Tube - Based Robust Nonlinear Model Predictive Control

A successful method for model predictive control of constrained linear systems uses a local linear control law that, in the presence of disturbances, maintains the disturbed trajectory of the controlled system in a tube whose centre is the nominal trajectory (generated ignoring the disturbance) and whose ‘cross-section’ is a robust, positively invariant set; robust exponential stability of an i...

Passivity-based Nonlinear Model Predictive Control

In this thesis a nonlinear model predictive control (NMPC) scheme is presented that is based on the concept of passivity. The proposed NMPC scheme takes advantage of the relationship between optimal control and passivity and the relationship between optimal control and model predictive control. This novel NMPC scheme, guaranteeing closedloop stability through the incorporation of a passivity-ba...

Nonlinear Model Predictive Control

Controlling Nonlinear Processes, using Laguerre Functions Based Adaptive Model Predictive Control (AMPC) Algorithm

Laguerre function has many advantages such as good approximation capability for different systems, low computational complexity and the facility of on-line parameter identification. Therefore, it is widely adopted for complex industrial process control. In this work, Laguerre function based adaptive model predictive control algorithm (AMPC) was implemented to control continuous stirred tank rea...