Abstract Autonomous Vehicles (AVs) have shown indelible and revolutionary effects on
accident reduction and more efficient use of travel time, with outstanding socio‐economic …

Model predictive control (MPC) theory has gained attention with the recent increase in the
processing power of computers that are now able to perform the needed calculations for this …

The control problem was formulated in the previous chapters considering all signals to
possess an unlimited range. This is not very realistic because in practice all processes are …

The formulation and final control law of two of the more popular MPC algorithms, dynamic
matrix control (DMC) and generalised predictive controller (GPC), are specially analysed in …

This paper presents a new path tracking scheme for a car-like mobile robot based on neural
predictive control. A multi-layer back-propagation neural network is employed to model non …

This paper presents a simple and effective solution for the path tracking problem of a mobile
robot using a PID controller. The proposed method uses a simple linearized model of the …

Trajectory tracking for autonomous vehicles is usually solved by designing control laws that
make the vehicles track predetermined feasible trajectories based on the trajectory error …

Recently, model predictive control (MPC) is increasingly applied to path tracking of mobile
devices, such as mobile robots. The characteristics of these MPC-based controllers are not …

This paper presents a neural network predictive control scheme for studying the coagulation
process of wastewater treatment in a paper mill. A multi-layer back-propagation neural …

This paper presents a way of implementing a model-based predictive controller (MBPC) for
mobile robot navigation when unexpected static obstacles are present in the robot …