Reinforcement learning-based control using Q-learning and gravitational search algorithm with experimental validation on a nonlinear servo system
This paper presents a novel Reinforcement Learning (RL)-based control approach that uses
a combination of a Deep Q-Learning (DQL) algorithm and a metaheuristic Gravitational …
a combination of a Deep Q-Learning (DQL) algorithm and a metaheuristic Gravitational …
Hybrid data-driven fuzzy active disturbance rejection control for tower crane systems
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 …
control algorithms, Active Disturbance Rejection Control (ADRC) as a representative data …
A unified form of fuzzy C-means and K-means algorithms and its partitional implementation
This paper proposes as an element of novelty the Unified Form (UF) clustering algorithm,
which treats Fuzzy C-Means (FCM) and K-Means (KM) algorithms as a single configurable …
which treats Fuzzy C-Means (FCM) and K-Means (KM) algorithms as a single configurable …
Evolving fuzzy models for prosthetic hand myoelectric-based control
This article applies an incremental online identification algorithm to develop a set of evolving
fuzzy models (FMs) that characterize the nonlinear finger dynamics of the human hand for …
fuzzy models (FMs) that characterize the nonlinear finger dynamics of the human hand for …
A survey on fuzzy control for mechatronics applications
Fuzzy control has become one of the most effective tools for dealing with complex
engineering processes. Over the years, research on fuzzy control systems has continuously …
engineering processes. Over the years, research on fuzzy control systems has continuously …
Iterative feedback tuning algorithm for tower crane systems
This paper proposes validates an Iterative Feedback Tuning (IFT) algorithm, which is a
classical and also popular data-driven algorithm, on tower crane systems. The IFT algorithm …
classical and also popular data-driven algorithm, on tower crane systems. The IFT algorithm …
[PDF][PDF] Evolving fuzzy models of shape memory alloy wire actuators
RCR Hedrea, EM Petriu - Science and Technology, 2021 - romjist.ro
This paper suggests Takagi-Sugeno-Kang (TSK) fuzzy models that characterize the position
of Shape Memory Alloy (SMA) wire actuators. The systems dynamics are important because …
of Shape Memory Alloy (SMA) wire actuators. The systems dynamics are important because …
A practical implementation of robust evolving cloud-based controller with normalized data space for heat-exchanger plant
The RECCo control algorithm, presented in this article, is based on the fuzzy rule-based
(FRB) system named ANYA which has non-parametric antecedent part. It starts with zero …
(FRB) system named ANYA which has non-parametric antecedent part. It starts with zero …
Evolving fuzzy and neuro-fuzzy systems: Fundamentals, stability, explainability, useability, and applications
E Lughofer - Handbook on Computer Learning and Intelligence …, 2022 - World Scientific
This chapter provides an all-round picture of the development and advances in the fields of
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …
Evolving fuzzy systems—fundamentals, reliability, interpretability, useability, applications
E Lughofer - Handbook on computational intelligence: volume 1 …, 2016 - World Scientific
This chapter provides a round picture of the development and advances in the field of
evolving fuzzy systems (EFS) made during the last decade since their first appearance in …
evolving fuzzy systems (EFS) made during the last decade since their first appearance in …