scholarly journals Control solutions in mechatronics systems

2005 ◽  
Vol 18 (3) ◽  
pp. 379-394
Author(s):  
Radu-Emil Precup ◽  
Stefan Preitl
Keyword(s):  
Fuzzy Control ◽  
Control Systems ◽  
Third Order ◽  
Fuzzy Controllers ◽  
Real World Application ◽  
Conventional Solution ◽  
Extended Symmetrical Optimum Method ◽  
Theoretical Results ◽  
Iterative Feedback ◽  
Fuzzy Solutions

This paper presents control solutions dedicated to a class of controlled plants widely used in mechatronics systems, characterized by simplified mathematical models of second-order and third-order plus integral type. The conventional control solution is focused on the Extended Symmetrical Optimum method proposed by the authors in 1996. There are proposed six fuzzy control solutions employing PI-fuzzy controllers. These solutions are based on the approximate equivalence in certain conditions between fuzzy control systems and linear ones, on the application of the modal equivalence principle, and on the transfer of results from the continuous-time conventional solution to the fuzzy solutions via a discrete-time expression of the controller where Prof. Milic R. Stojic's book [1] is used. There is performed the sensitivity analysis of the fuzzy control systems with respect to the parametric variations of the controlled plant, which enables the development of the fuzzy controllers. In addition, the paper presents aspects concerning Iterative Feedback Tuning and Iterative Learning Control in the framework of fuzzy control systems. The theoretical results are validated by considering a real-world application.

Iterative Feedback Tuning in Linear and Fuzzy Control Systems

2009 ◽  
pp. 179-192
Author(s):  
Radu-Emil Precup ◽  
Mircea-Bogdan Rădac ◽  
Stefan Preitl ◽  
Emil M. Petriu ◽  
Claudia-Adina Dragoş
Keyword(s):  
Fuzzy Control ◽  
Control Systems ◽  
Iterative Feedback

Stable Fuzzy Control Systems with Iterative Feedback Tuning

2008 ◽  
Author(s):  
R.-E. Precup ◽  
S. Preitl ◽  
P. A. Clep ◽  
I. B. Ursache ◽  
J. K. Tar ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Control Systems ◽  
Iterative Feedback

Fuzzy-control for improved nitrogen removal and energy saving in WWT-plants with pre-denitrification

2003 ◽  
Vol 47 (11) ◽  
pp. 69-76 ◽  
Author(s):  
U. Meyer ◽  
H. J. Pöpel
Keyword(s):  
Fuzzy Logic ◽  
Wastewater Treatment ◽  
Fuzzy Control ◽  
Control Systems ◽  
Large Scale ◽  
Wastewater Treatment Plants ◽  
Control Strategies ◽  
Air Flow ◽  
Control Variable ◽  
Fuzzy Controllers

In the last few years, numerous studies were carried out, dealing with the application of fuzzy-logic to improve the control of the activated sludge process. In this paper, fuzzy-logic based control strategies for wastewater treatment plants with pre-denitrification are presented that should lead to better effluent quality and, in parallel, to a reduction of energy consumption. Extensive experimental investigations on a large scale pilot plant as well as simulation studies (ASM1 with SIMBA®) were carried out in order to design, evaluate and compare different fuzzy-controllers with each other and with comparable conventional control systems. The fuzzy-controllers were designed as high-level controllers that determine the DO-setpoints in the aerated zones and the ratio between aerated and non-aerated zones. Conventional PI-controllers were used to maintain the DO-concentration at the set-point levels. The ammonia and nitrate concentration in the effluent and the ammonia load in the influent were considered as input variables for the different fuzzy-controllers. Compared to the operation with fixed nitrification/denitrification zones and constant DO concentrations, the required air-flow could be reduced up to 24% by using fuzzy-logic based control strategies. In comparison with a more advanced conventional control strategy (relay controller with two thresholds and the NH4-N concentration in the effluent as single control variable) a reduction of air-flow-rate up to 14% could be achieved. At the same time, NH4-N peaks in the effluent that are normally caused by peak flow conditions could be reduced significantly. The large scale experiments show that the fuzzy-controllers can be easily implemented in modern control and supervision systems and that the control characteristics can be followed and modified during operation. It therefore can be expected that the developed fuzzy-control systems will be accepted by the operating personnel in wastewater treatment plants.

Fuzzy Control for Inverted Pendulum Using Fuzzy Neural Networks

1995 ◽  
Vol 7 (1) ◽  
pp. 36-44 ◽  
Author(s):  
Shin-ichi Horikawa ◽  
◽  
Masahiro Yamaguchi ◽  
Takeshi Furuhashi ◽  
Yoshiki Uchikawa ◽  
...  
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Inverted Pendulum ◽  
Fuzzy Neural Networks ◽  
Fuzzy Controllers ◽  
Type Iv ◽  
Control Rules ◽  
Fuzzy Neural

Fuzzy control has a distinctive feature in that it can incorporate experts' control rules using linguistic expressions. The authors have presented various types of fuzzy neural networks (FNNs) called Type I-V. The FNNs can automatically identify the fuzzy rules and tune the membership functions of fuzzy controllers by utilizing the learning capability of neural networks. In particular, the Type IV FNN has a simple structure and can express the identified fuzzy rules linguistically. The authors have also proposed a method to describe the behavior of fuzzy control systems based on the fuzzy models. The method can comprehensively express the dynamic behavior of fuzzy control systems and makes easy to know how to modify the fuzzy controllers. This paper studies an acquisition of fuzzy controller for an inverted pendulum using the Type IV FNNs and presents a new method for describing of the behavior of the fuzzy control system. The new method expresses the dynamic ehavior of the fuzzy control system more clearly by incorporating the change of the output of the controlled object. This new rule-to-rule mapping method enables easy modification of the fuzzy control rules. The experimental results illustrate that the method is effective in designing the fuzzy controllers having good performance.

Synthesis and optimization of fuzzy controllers in the control systems of pyrolysis reactors

2017 ◽  
Vol 0 (4) ◽  
Author(s):  
Oleksiy V. Kozlov ◽  
Galyna V. Kondratenko ◽  
Yuriy P. Kondratenko
Keyword(s):  
Control Systems ◽  
Fuzzy Controllers
Sign in / Sign up

Export Citation Format

Share Document