Gradient-based methods have been widely used for system design and optimization in
diverse application domains. Recently, there has been a renewed interest in studying …

Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …

This paper introduces a novel reference tracking control approach implemented using a
combination of the Actor-Critic Reinforcement Learning (RL) framework and the Grey Wolf …

摘要给出了数据驱动控制理论和方法相关问题的定义, 从控制理论, 实际应用和历史发展趋势三
个角度阐述了数据驱动控制的存在背景, 说明了数据驱动控制理论和方法的适用条件 …

This paper is a brief survey on the existing problems and challenges inherent in model-
based control (MBC) theory, and some important issues in the analysis and design of data …

During the past half century, modern control theory has developed greatly and many
branches and subfields have emerged, for example, linear system theory, optimal control …

In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed
based on a new dynamic linearization technique (DLT) with a novel concept called pseudo …

In this work, a novel data-driven control approach, model-free adaptive control, is presented
based on a new dynamic linearization technique for a class of discrete-time single-input and …

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 …

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 …