Inverse optimal control (IOC) is an advanced methodological framework that seeks to deduce the underlying cost or reward functions based solely on the observation of optimal behaviour. Traditionally, ...

The Takagi--Sugeno (T--S) fuzzy descriptor system offers a promising avenue for controlling non-linear systems but lacks optimal control strategies. Moreover, while robust control methods have been ...

Deep reinforcement learning (DRL) is applied to control a nonlinear, chaotic system governed by the one-dimensional Kuramoto–Sivashinsky (KS) equation. DRL uses reinforcement learning principles for ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

Research in dynamics includes theoretical, computational and experimental research in the general area of dynamical systems, dynamics and vibrations, dynamics of flexible bodies, high-dimensional ...

This graduate level survey course will cover the physiological elements within the vertebrate motor system and the computational problems intrinsic to the production of movement. We will cover the ...

Yokogawa Electric Corporation announces that Yokogawa and Shell have jointly developed Platform for Advanced Control and Estimation, a software suite that speeds up and simplifies the process of ...

A research team has reviewed how machine learning (ML) is revolutionizing fermentation design and process optimization by ...

Exploring the Future of Metabolic Optimization As we advance into 2026, the pursuit of optimal health and performance continues to evolve with the development of innovative metabolic optimization ...