Analytical Structures of Takagi-Sugeno Fuzzy Two-Input Two-Output Proportional-Integral/Proportional-Derivative Controllers With Multiple Fuzzy Sets

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Ritu Raj ◽  
B. M. Mohan
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Rule Base ◽  
Complete Control ◽  
Proportional Integral ◽  
Control Rules ◽  
Gain Variation ◽  
Multiple Input ◽  
Takagi Sugeno

In this paper, an attempt is made to generalize the analytical structures of Takagi-Sugeno (TS) fuzzy two-input two-output (TITO) proportional-integral (PI)/proportional-derivative (PD) controllers using multiple input fuzzy sets. Two models of fuzzy TITO PI/PD controllers are proposed based on two distinct control strategies. The inputs are fuzzified by multiple fuzzy sets with trapezoidal/triangular membership functions. The generalized rule base consists of nine control rules imbibing the complete control strategy and is closer in spirit to the original TS rule base. Algebraic product (AP) triangular norm, bounded sum (BS) triangular conorm, and center of gravity (CoG) defuzzifier are applied to derive the models. The models of the fuzzy TITO PI/PD controllers with multiple input fuzzy sets are (nonlinear) variable gain/structure controllers. Also, each output of the fuzzy controller is the sum of two nonlinear PI/PD controllers with variable gains. The gain variation and properties of the proposed controllers are studied. Two examples of nonlinear dynamic processes are considered to demonstrate the applicability of the proposed controllers.

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

2021 ◽  
Author(s):  
Shahrooz Alimoradpour ◽  
Mahnaz Rafie ◽  
Bahareh Ahmadzadeh
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy System ◽  
Inverted Pendulum ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Base System ◽  
Control Rules ◽  
Dynamics And Control

Abstract One of the classic systems in dynamics and control is the inverted pendulum, which is known as one of the topics in control engineering due to its properties such as nonlinearity and inherent instability. Different approaches are available to facilitate and automate the design of fuzzy control rules and their associated membership functions. Recently, different approaches have been developed to find the optimal fuzzy rule base system using genetic algorithm. The purpose of the proposed method is to set fuzzy rules and their membership function and the length of the learning process based on the use of a genetic algorithm. The results of the proposed method show that applying the integration of a genetic algorithm along with Mamdani fuzzy system can provide a suitable fuzzy controller to solve the problem of inverse pendulum control. The proposed method shows higher equilibrium speed and equilibrium quality compared to static fuzzy controllers without optimization. Using a fuzzy system in a dynamic inverted pendulum environment has better results compared to definite systems, and in addition, the optimization of the control parameters increases the quality of this model even beyond the simple case.

Fuzzy control of aeration in an activated sludge wastewater treatment plant: design, simulation and evaluation

1999 ◽  
Vol 39 (4) ◽  
pp. 71-78 ◽  
Author(s):  
T. J. J. Kalker ◽  
C. P. van Goor ◽  
P. J. Roeleveld ◽  
M. F. Ruland ◽  
R. Babuška
Keyword(s):  
Fuzzy Logic ◽  
Wastewater Treatment ◽  
Activated Sludge ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Treatment Plant ◽  
Rule Base ◽  
Plant Design ◽  
High Level ◽  
Simulation And Evaluation

Fuzzy logic can in several ways be applied to improve the control of the activated sludge system. In the present study, two types of fuzzy logic controllers were developed for intermittent aeration control: a low-level fuzzy controller for DO control and a high-level controller for nitrogen removal. A Simulink-SIMBAR model was used to subsequently design and optimise the controller and furthermore to compare various control strategies. The results indicate that the direct fuzzy controller allows for some improvements in comparison with a PI controller. Nevertheless, it is suggested that high-level controllers have more potentials for improving and integrating the control of wastewater treatment. The developed high-level fuzzy controller performs better than two conventional controllers in terms of energy consumption and, at the same time, results in a slightly better effluent quality. Design and tuning were quite straightforward. Since the rule base applied is comprehensive it is expected that in practice the controller will meet with the demands of the operator.

Fuzzy Based Modeling, Control, and Fault Diagnosis of Permanent Magnet Synchronous Generator

2013 ◽  
pp. 487-520 ◽  
Author(s):  
N. Selvaganesan
Keyword(s):  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Rule Base ◽  
Permanent Magnet Synchronous Generator ◽  
Takagi Sugeno

This chapter presents the design methodology of fuzzy based modeling, control, and fault diagnosis of Permanent Magnet Synchronous Generator (PMSG) system. The fuzzy based modeling scheme for PMSG is developed using the general Takagi-Sugeno fuzzy model. Subsequently, fuzzy controller is designed and simulated to maintain three phase output voltage as constant by controlling the speed of generator. The feasibility of the fuzzy model and control scheme is demonstrated using various operating conditions by MATLAB simulation. Also, fuzzy based fault detection scheme for PMSG is developed and presented. The positive and negative sequence currents are used as fault indicators and given as inputs to fuzzy fault detector. The fuzzy inference system is created, and rule base is evaluated, relating the sequence current component to the type of faults. The feasibility of this scheme is demonstrated for different types of fault under various operating conditions using MATLAB/Simulink.

Fuzzy Control of Target Approaching and Object-Grabbing for a Four-Wheeled Vision-Based Mobile Robot

2013 ◽  
Vol 17 (2) ◽  
pp. 343-350
Author(s):  
Chih-Hung Wu ◽  
◽  
I-Sheng Lin ◽  
Ming-Liang Wei
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Fuzzy Sets ◽  
Fuzzy Controller ◽  
Ccd Camera ◽  
Control Rules ◽  
Practical Experiences ◽  
And Control

This paper presents practical experiences in deploying a fuzzy controller on a vision-based fourwheeled mobile robot for target-approaching and object-grabbing. The robot senses the environment using a simple CCD camera in its patrol. One of the robot’s missions is to actuate a mechanical grabber for picking up specific objects detected in its patrol routine. To overcome the control errors caused by physical friction and inertia, a fuzzy controller is designed and implemented for wheel-driving and objectgrabbing. Definitions are presented for fuzzy sets and control rules that consider hardware specifications. The feasibility of the method has been verified under various ground friction. Experiments in the performance of the proposed method are presented and analyzed.

scholarly journals A Heating Controller Designing Based on Living Space Heating Dynamic’s Model Approach in a Smart Building

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 998
Author(s):  
Roozbeh Sadeghian Broujeny ◽  
Kurosh Madani ◽  
Abdennasser Chebira ◽  
Veronique Amarger ◽  
Laurent Hurtard
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Time Series Prediction ◽  
Adaptive Controller ◽  
Inference System ◽  
Diverse Range ◽  
Smart Building ◽  
Living Space ◽  
Soft Computing Techniques

Most already advanced developed heating control systems remain either in a prototype state (because of their relatively complex implementation requirements) or require very specific technologies not implementable in most existing buildings. On the other hand, the above-mentioned analysis has also pointed out that most smart building energy management systems deploy quite very basic heating control strategies limited to quite simplistic predesigned use-case scenarios. In the present paper, we propose a heating control strategy taking advantage of the overall identification of the living space by taking advantage of the consideration of the living space users’ presence as additional thermal sources. To handle this, an adaptive controller for the operation of heating transmitters on the basis of soft computing techniques by taking into account the diverse range of occupants in the heating chain is introduced. The strategy of the controller is constructed on a basis of the modeling heating dynamics of living spaces by considering occupants as an additional heating source. The proposed approach for modeling the heating dynamics of living spaces is on the basis of time series prediction by a multilayer perceptron neural network, and the controlling strategy regarding the heating controller takes advantage of a Fuzzy Inference System with the Takagi-Sugeno model. The proposed approach has been implemented for facing the dynamic heating conduct of a real five-floor building’s living spaces located at Senart Campus of University Paris-Est Créteil, taking into account the occupants of spaces in the control chain. The obtained results assessing the efficiency and adaptive functionality of the investigated fuzzy controller designed model-based approach are reported and discussed.

scholarly journals Effects of different methods to control the parasitic weed Phelipanche ramosa (L.) Pomel in processing tomato crops

2016 ◽  
Vol 10 (1s) ◽  
pp. 39 ◽  
Author(s):  
Grazia Disciglio ◽  
Francesco Lops ◽  
Antonia Carlucci ◽  
Giuseppe Gatta ◽  
Annalisa Tarantino ◽  
...  
Keyword(s):  
Control Strategies ◽  
Block Design ◽  
Soluble Solids ◽  
Marketable Yield ◽  
Department Of Agriculture ◽  
Parasitic Weed ◽  
Complete Control ◽  
Tomato Plants ◽  
Processing Tomato ◽  
Phelipanche Ramosa

The root-parasitic weed <em>Phelipanche ramosa</em> (L.) Pomel represents a major problem for processing tomato crops. The control of this holoparasitic plant is difficult, and better understanding of treatment methods is needed to develop new and specific control strategies. This study investigated 12 agronomic, chemical, biological and biotechnological strategies for the control of this parasitic weed, in comparison with the untreated situation. The trial was carried out in 2014 at the Department of Agriculture, Food and the Environment of the University of Foggia (southern Italy), using processing tomato plants grown in pots filled with soil from a field that was heavily infested with <em>P. ramosa</em>. After transplantation, top dressing was performed with 70 kg ha<sup>–1</sup> nitrogen. A randomised block design with 3 replicates (pots) was adopted. During the growing cycle of the tomato, at 70, 75, 81 and 88 days after transplantation, the number of parasitic shoots (branched plants) that had emerged in each pot was determined, and the leaf chlorophyll of the plants was measured using a soil-plantanalysis- development meter. At harvesting on 8 August 2014, the major quanti-qualitative yield parameters were determined, including marketable yield, mean weight, dry matter, soluble solids, and fruit colour. The results show lower chlorophyll levels in the parasitised tomato plants, compared to healthy plants. None of the treatments provided complete control against P. ramosa. However, among the methods tested, Radicon® biostimulant (Radicon, Inc., Elk Grove Village, IL, USA), compost activated with <em>Fusarium oxysporum</em>, nitrogen and sulphur mineral fertilisers, Enzone<sup>TM</sup> soil fumigant (Elliott Chemicals Ltd., Auckland, New Zealand), and a resistant tomato genotype mitigated the virulence of the attacks of this parasite. These effects should be improved by combining some of these treatments, especially for gradual and continued reduction in the <em>seed bank</em> of the parasite in the soil. For the tomato yields across the different treatments, there were no significant differences seen; however, the yields showed an improving trend for treatments with lower presence of the <em>P. ramosa</em> weed.

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