A brief overview on the model-based control and data-driven control methods is presented.
The data-driven equivalent dynamic linearization, as a foundational analysis tool of data …

This paper proposes the Virtual Reference Feedback Tuning (VRFT) of a combination of two
control algorithms, Active Disturbance Rejection Control (ADRC) as a representative data …

This book categorizes the wide area of data-driven model-free controllers, reveals the exact
benefits of such controllers, gives the in-depth theory and mathematical proofs behind them …

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each
other when performing intelligent optimization. They are both regarded as promising …

This paper aims to discuss and analyze the potentialities of Recurrent Neural Networks
(RNN) in control design applications. The main families of RNN are considered, namely …

This article considers the neural adaptive control issues of a category of non-integer-order
non-square plants with actuator Nonlinearities and Asymmetric Time-Varying pseudo-State …

This paper investigates a novel robust path following control scheme for unmanned surface
vehicle (USV) with unknown dynamics, currents and actuator saturation. In the guidance …

This paper proposes the design and implementation of a model-free tire slip control for a fast
and highly nonlinear Anti-lock Braking System (ABS). A reinforcement Q-learning optimal …

Based on ACP (artificial systems, computational experiments, and parallel execution)
methodology, parallel control and management has become a popularly systematic and …

This study addresses the issue of the adaptive output tracking control for a category of
uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the …