𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Moving average and self-tuning control

✍ Scribed by K. J. Åström

Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
119 KB
Volume
13
Category
Article
ISSN
0890-6327

No coin nor oath required. For personal study only.

✦ Synopsis

This paper revisits several problems in self-tuning control. The starting point is regulation of industrial processes. The desire to solve these problem was a driver for much of the research. Control design is discussed from the point of view of moving average control, system identiÿcation and self-tuning control. These are all areas where Peterka has given major contributions. The paper is of expository character but it also provides background and perspective.

📜 SIMILAR VOLUMES

Practical aspects of self-tuning control
Practical aspects of self-tuning controllers
✍ Vladimír Bobál; Josef Böhm; Roman Prokop 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 194 KB 👁 2 views

The contribution presents a class of Single Input Single Output (SISO) discrete self-tuning controllers suitable for industrial applications. The proposed adaptive controllers can be divided into three groups. The "rst group covers PID adaptive algorithms with using of traditional methods. The secon

Self-tuning control and industrial appli
Self-tuning control and industrial applications: the limited authority control concept
✍ M. J. Grimble; M. A. Johnson; C. L. Brasca; V. Arcidiacono 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 267 KB 👁 1 views

Since Peterka "rst introduced the concept of self-tuning control the industrial application of self-tuning or adaptive control, has not been as widespread as might have been expected. Self-tuning concepts are relatively simple but procedures and techniques for routine plant application have not emer

Self-tuning PID controller using δ-model
Self-tuning PID controller using δ-model identification
✍ Vladimír Bobál; Martin Sysel; Petr Dostál 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 312 KB 👁 1 views

## Abstract This contribution presents an application of a self‐tuning digital PID controller for process control modelled by __δ__‐models. The process is identified by the regression (ARX) model using the recursive least‐squares method (RLSM) with LD decomposition and applied directional forgettin