Mobile robots tracking a reference trajectory are constrained by the motion limits of their
actuators, which impose the requirement for high autonomy driving capabilities in robots …

" Advanced Control of Industrial Processes" presents the concepts and algorithms of
advanced industrial process control and on-line optimisation within the framework of a …

In this paper, we present a neurodynamic approach to model predictive control (MPC) of
unknown nonlinear dynamical systems based on two recurrent neural networks (RNNs). The …

In this paper, we have developed a novel visual servo-based model predictive control
method to steer a wheeled mobile robot (WMR) moving in a polar coordinate toward a …

In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …

In this paper, a model predictive control (MPC) scheme is presented for tracking of
underactuated vessels with only two available controls: namely, surge force and yaw …

In this paper, a class of nonholonomic chained systems is first converted into two
subsystems, and then an explicit exponential decaying term is introduced into the input of …

This paper presents a neural network approach to robust model predictive control (MPC) for
constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded …

This paper presents new results on a neural network approach to nonlinear model predictive
control. At first, a nonlinear system with unmodeled dynamics is decomposed by means of …

This book systematically synthesizes research achievements in the field of fuzzy neural
networks in recent years. It also provides a comprehensive presentation of the …