The paper discusses the proportional-integral-derivative (PID) controller from the viewpoint
of (a) the analytical tuning of the PID controller for the double integrator plus dead time …

A novel direct synthesis (DS) method for simultaneous and non-iterative design of multi-loop
PID controllers for stable multivariable processes is presented in this article. We deal with …

The feasibility of a neural network method was discussed in terms of a self-tuning
proportional–integral–derivative (PID) controller. The proposed method was configured with …

The industrial sector is nowadays experiencing a digital transformation motivated by the
Industry 4.0 paradigm. Concepts such as data-driven models, Artificial Neural Networks …

This paper describes the controller design aspects of DFIG‐based wind turbine system
(WTS) using gravitational search algorithm (GSA). The appropriate control schemes are …

PID control is the longest history and the most vital basic control mode that has been widely
applied in the production process. The oscillatory dynamics of the process have various …

A new technique is proposed for the design of PID controllers for minimum and non-
minimum phase (NMP) stable first-order and second-order processes. The idea is to make …

This paper studies states estimation and resilient control schemes based on model
predictive control (MPC) algorithm for a class of Takagi–Sugeno (T–S) fuzzy stochastic …

In this paper, we address the design of data-based Artificial Neural Networks (ANN)
controllers. More specifically, we consider a scalable design based on a Transfer Learning …

The industrial process control systems are high-order sophisticated and complicated
systems with characteristics such as inertia, uncertainty, and even oscillatory. The controller …