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Practical PID Control

TLDR
Basics of PID Control, Derivative Filter Design, Anti-windup Strategies, Setpoint Weighting, Use of a Feedforward Action, Plug&Control, Identification and Model Reduction Techniques, Performance Assessment, Control Structures as discussed by the authors.
Abstract
Basics of PID Control.- Derivative Filter Design.- Anti-windup Strategies.- Set-point Weighting.- Use of a Feedforward Action.- Plug&Control.- Identification and Model Reduction Techniques.- Performance Assessment.- Control Structures.

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Citations
More filters
Journal ArticleDOI

Tuning rules for optimal PID and fractional-order PID controllers

TL;DR: In this paper, a set of tuning rules for standard (integer-order) PID and fractional-order PID controllers is presented, based on a first-order plus-dead-time model of the process, in order to minimize the integrated absolute error with a constraint on the maximum sensitivity.
Journal ArticleDOI

PI and Sliding Mode Control of a Cuk Converter

TL;DR: In this article, a closed-loop Cuk converter with the aid of the equivalent control method is obtained with the assistance of the Routh-Hurwitz stability criterion and root locus, and a stable and robust system suitable for large signal variations is achieved.
Proceedings ArticleDOI

Intelligent PID controllers

TL;DR: The main tool is an online numerical differentiator, which is based on easily implementable fast estimation and identification techniques, which demonstrates the efficiency of the method when compared to more classic PID regulators.
Journal ArticleDOI

Closed-Loop Analysis and Cascade Control of a Nonminimum Phase Boost Converter

TL;DR: In this paper, a cascade controller is designed and analyzed for a boost converter, and the simulation results show that the reference output voltage is well tracked under parametric changes, system uncertainties, or external disturbances with fast dynamic transients.
Journal ArticleDOI

Design of a Control System for an Autonomous Vehicle Based on Adaptive-PID

TL;DR: This paper presents the control system architecture for the autonomous vehicle integrating multi-sensor navigation and positioning, intelligent decision making and control technology, and describes how the system will be implemented in the real-time.