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 …

The spread of active braking controllers on vehicles with significant mechanical differences
and on low-cost products asks for control design approaches which offer easy and fast …

A data-driven approach for on-line tuning of minimum variance (MV) PID controller is
proposed in this paper for a linear system subject to stochastic disturbances, in which none …

Modeling a launch vehicle dynamics accurately is time-consuming since its dynamics is very
complex with high nonlinearity, when considering the influence of load variation and other …

Without the explicit process identification, the authors propose a model‐free adaptive control
framework for unknown plant by using the concept of equivalent dynamic linearisation …

This paper presents a hierarchical data-driven/model-based control architecture to robot
implicit force control aiming at enhancing closed-loop performance. An inner data-driven …

Fictitious reference iterative tuning (FRIT) is a method for designing the feedback controller
of an unknown plant model. FRIT searches control parameters so that the plant output …

This paper presents a novel method for proportional-integral-derivative (PID) controller
tuning directly using the step response data of the process without resorting to a process …

A systematic data-based design method for tuning proportional–integral–derivative (PID)
controllers for disturbance attenuation is proposed. In this method, a set of closed-loop plant …

Typically chemical processes have significant nonlinear dynamics, but despite this, industry
is conventionally still using PID-based regulatory control systems. Moreover, process units …