This paper proposes a real-time human inverse kinematics approach based on the
Gaussian Process (GP) to address the open problem of finding appropriate inverse …

Modeling error and external disturbances can severely degrade the performance of Model
Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this …

The computational burden could be an issue of traditional model predictive control (MPC) in
real-time applications. There are different procedures to cope with this problem such as …

This paper introduces a novel approach to the conventional model predictive control design
within a tube model predictive control framework for a DC motor servo system that is an …

In this article, a new intelligent hybrid controller is proposed. The controller is based on the
combination of the orthogonal endocrine neural network (OENN) and orthogonal endocrine …

This paper deals with Predictive Sliding Mode Control (PSMC) that uses Laguerre functions
in the design of a control input signal. Two types of PSMC algorithms are considered: one …

This work aims to enhance the robustness and reduce the control effort in the presence of
input and state constraints while performing rehabilitation exercises with uncertainty in the …

This paper deals with Tube Model Predictive Control (MPC) based on Laguerre functions
with a Sliding Mode Controller (SMC) as an auxiliary controller. Two types of SMC are …

This paper presents a control system for elimination of chaotic behaviors in spur gear
system. To this end, at first different aspects of chaos are investigated by means of numerical …

Dans cette thèse de doctorat, plusieurs avancées sont présentées pour améliorer les
capacités d'un robot exosquelette à sept degrés de liberté (7 DDL) conçu pour la …