In this paper two predictive controllers for non-linear systems are presented. Both methods—
ELPC and MELPC—are based on a local linearisation of the process at each sampling …

This paper describes two nonlinear Model Predictive Control (MPC) algorithms with neural
approximation. The first algorithm mimics the MPC algorithm in which a linear approximation …

Classical model predictive control (MPC) algorithms need very long horizons when the
controlled process has complex dynamics. In particular, the control horizon, which …

Model predictive control, MPC, is a model-based control philosophy that select control
actions by online optimization of objective functions. Design methods based on MPC have …

This paper describes the implementation of an efficient model predictive control (MPC)
approach on a standard programmable logic controller (PLC). PLCs are commonly used in …

Predictive Functional Control - Application to Fast and Accurate Robots Page 1 Copvright ©
IL\C IlIth Tril'lllli,d \I'mld COllgre", \Iulli,h, FR(;. lHi PREDICTIVE FUNCTIONAL CONTROL …

In this paper a practical approach to Nonlinear Model Predictive Control (NMPC) of a robotic
manipulator subject to nonlinear state constraints is presented, which leads to a successful …

This paper describes a nonlinear Model Predictive Control (MPC) algorithm based on neural
models. Two neural models are used on-line: from a dynamic model the free trajectory (the …

Robot manipulators present restrictions on their performance, such as the maximum torque
the motors can apply, limitations in their position, speed, acceleration, etc. This paper …

A new model predictive control (MPC) algorithm for nonlinear systems is presented. The
plant under control, the state and control constraints, and the performance index to be …