Decentralized robust evolving cloud-based controller for two input two output systems

2021 ◽  
pp. 014233122110492
Author(s):  
J Vijay Anand ◽  
PS Manoharan
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Rule ◽  
Single Input Single Output ◽  
Point Tracking ◽  
Single Output ◽  
Tito Systems

The fuzzy logic controller (FLC) makes it possible to control a system using IF-THEN rules through human intellect. It tackles parameter uncertainty using imprecise reasoning. The fuzzy logic controller is usually tuned using offline methods. An online evolving adaptation of fuzzy controller design is a recent trend in fuzzy rule-based systems. The robust evolving cloud-based controller (RECCo) is one such controller implemented for single-input-single-output (SISO) systems. The membership functions and consequent rules are automatically updated in real time based on the input data. In this paper, a decentralized robust evolving cloud-based controller (DRECCo) is proposed for two-input-two-output (TITO) systems. It consists of two independent loops with RECCos having a nonparametric premise facet and an adaptive proportional-integral-derivative (PID) model consequent facet. The effectiveness of the proposed method is validated for the benchmark interacting two-tank process (ITTP) and quadruple-tank process (QTP) by simulation and in real time. The results indicate that with the information of loop pairing and the forward-acting/reverse-acting nature of the process, the proposed controller can adapt itself to ensure set-point tracking and disturbance rejection.

scholarly journals Design and Implementation of Adaptive PID and Adaptive Fuzzy Controllers for a Level Process Station

2021 ◽  
Author(s):  
Aparna Venkataraman
Keyword(s):  
Real Time ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Equilibrium Points ◽  
Process Variable ◽  
Open Loop ◽  
Single Input Single Output ◽  
Adaptive Fuzzy ◽  
Single Output ◽  
Adaptive Fuzzy Logic

This proposed work proposes the design and real-time implementation of an adaptive fuzzy logic controller (FLC) and a proportional-integral-derivative (PID) controller for adaptive gain scheduling that can be configured for any complex industrial nonlinear application. Initially, the open-loop test of the single-input single-output (SISO) system, with nonlinearities and disturbances, is conducted to represent the mathematical model of the process around a set of equilibrium points. The adaptive controllers are then developed and deployed by using the national instruments reconfigurable input/output data acquisition device (NI RIO), NI myRIO-1900, and the control parameters are adapted in real-time corresponding to the changes in the process variable. The resulting servo and regulatory performance of the controllers are compared in MATLAB® software. The adaptive fuzzy controller is deduced to be the better controller as it can generate the desired output with quicker settling times, fewer oscillations, and negligible overshoot.

scholarly journals An Optimized Multi-Output Fuzzy Logic Controller for Real-Time Control

2008 ◽  
Vol 12 (4) ◽  
pp. 370-376
Author(s):  
Noel S. Gunay ◽  
◽  
Elmer P. Dadios
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Time Lag ◽  
Real Time Control ◽  
Single Output ◽  
Time Control ◽  
Object Oriented Approach ◽  
Control Application

Any real-time control application run by a digital computer (or any sequential machine) demands a very fast processor in order to make the time-lag from data sensing to issuance of a control action closest to zero. In some instances, the algorithm used requires a relatively large primary memory which is crucial especially when implemented in a microcontroller. This paper presents a novel implementation of a multi-output fuzzy controller (which is known in this paper as MultiOFuz), which utilizes lesser memory and executes faster than a type of an existing multiple single-output fuzzy logic controllers. The design and implementation of the developed controller employed the object-oriented approach with program level code optimizations. MultiOFuz is a reusable software component and the simplicity of how to interface this to control applications is presented. Comparative analyses of algorithms, memory usage and simulations are presented to support our claim of increased efficiency in both execution time and storage use. Future directions of MultiOFuz are also discussed.

On-Line Fuzzy Logic Temperature Control of a Concentric-Tubes Heat Exchanger Facility

2006 ◽  
Author(s):  
Claudia Ruiz-Mercado ◽  
Arturo Pacheco-Vega ◽  
Kevin Peters
Keyword(s):  
Heat Exchanger ◽  
Temperature Control ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Outlet Temperature ◽  
Single Input Single Output ◽  
Single Output ◽  
On Line ◽  
The Difference ◽  
Two Stages

We develop a fuzzy rule based controller to perform on-line temperature control of a concentric-tubes heat exchanger facility. The rules were derived from dynamical values of the mass flow rates and fluid temperatures in the heat exchanger. The controller was embedded in a closed-loop single-input single-output system to control the outlet temperature of the cold fluid. The controller was constructed in two stages, the difference between them being the amount of information provided to the controller. To validate the fuzzy controller two sets of tests were carried out for maintaining a constant value of the outlet temperature under different perturbations. Results from this analysis demonstrate that the fuzzy-based controller is able to achieve control of the system, and that the information about the system provided to it is important in terms of accuracy and efficiency.

scholarly journals Controller Design for Temperature Control of MISO Water Tank System

2021 ◽  
Vol 15 (4) ◽  
pp. 1-13
Author(s):  
Vishal Vishnoi ◽  
Sheela Tiwari ◽  
Rajesh Kumar Singla
Keyword(s):  
Fuzzy Logic ◽  
Temperature Control ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Water Tank ◽  
Single Output ◽  
Multiple Input ◽  
Tank System ◽  
Process Disturbances ◽  
The Impact

This article introduces the design of split range control and fuzzy logic control for temperature control of the MISO (multiple input single output) water tank scheme. A multiple input single output (MISO) system is considered for the proposed work as most of the practical systems comprise of numerous MISO system. Investigations are conducted on the impact of control parameters, system dynamics and process disturbances. From the simulation outcomes, it is clearly inferred that the fuzzy logic controller outperformed split range control over all parameters.

scholarly journals Multi loop Controller Design for Multivariable Processes Employing SISO PI Tuning Rules

2019 ◽  
Vol 8 (6S4) ◽  
pp. 347-351
Keyword(s):  
Controller Design ◽  
Industrial Applications ◽  
Single Input Single Output ◽  
Distillation Columns ◽  
Proportional Integral ◽  
Point Tracking ◽  
Single Output ◽  
Internal Model Controller ◽  
And Performance ◽  
Tuning Rules

Ability of the proportional integral (PI) and proportional integral derivative (PID) controllers in set point tracking and disturbance rejection has led to their wide usage in industrial applications. The desired controller performance can be achieved by application of suitable tuning rules. The presence of interacting loops in a process makes it a challenging task of PI controllers design in multivariable processes. This problem highly mitigated by employing simple single input single output internal model controller (IMC). This IMC PI controller values are applied for different distillation process involving distillation columns like Wardle and Wood (WW) , Wood and Berry (WB) and Vinate-Luyben (V-L). The obtained simulation with proposed method gives better results and performance indices values compared to other control tuning strategies.

scholarly journals High Efficiency Photovoltaic System with Fuzzy Logic Controller

2018 ◽  
Vol 21 (2) ◽  
pp. 60
Author(s):  
Branko Blanuša ◽  
Željko Ivanović ◽  
Branko Dokić
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
High Efficiency ◽  
Fuzzy Controller ◽  
Current Mode ◽  
Photovoltaic System ◽  
Maximum Efficiency ◽  
Switching Frequency ◽  
Pv System ◽  
Point Tracking

In this paper is presented high efficiency photovoltaic system (PV) with fuzzy logic controller. This system consists of PV panel, boost DC/DC converter and 24V DC load. Control module is realized with fuzzy controller. This controller has double function and it gives references for duty factor and switching frequency of the converter control signal. In this way the PV system works with applied maximum power point tracking (MPPT) method and switching frequency is changed on the way so the converter works with maximum efficiency in continuous current mode. Functionality of proposed model is tested through computer simulations in Matlab and on laboratory prototype.

Fuzzy Controller Approach for DC Motor Control on Fishing Rod

2015 ◽  
Vol 2 (1) ◽  
pp. 20-28
Author(s):  
Emmanuel Ade Crisna Putra ◽  
Houtman P. Siregar
Keyword(s):  
Fuzzy Logic ◽  
Transfer Function ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Dc Motor ◽  
Step Response ◽  
Rule Base ◽  
Dc Motor Control ◽  
Automation Control

In this paper described the usable and effectiveness of automation control by using fuzzy logic controller forcontrolling the speed of DC motor that will be used on string roller of fishing rod. The transfer function of DCmotor has been obtained. For transfer function, the load of DC motor will be acted as input, and the output is thevelocity of DC motor. The fuzzy rule base then created by trial and error. The step response between fuzzy logiccontroller and without using fuzzy logic controller then obtained and compared. As a result, the fuzzy logic hassuccessfully reduced the overshoot of step response.

Indirect Adaptive Fuzzy H∞ Tracking Control with Self-Structuring Algorithm for a Class of Uncertain Nonlinear SISO Systems

2013 ◽  
Vol 756-759 ◽  
pp. 622-626
Author(s):  
Sen Xu ◽  
Zhang Quan Wang ◽  
You Rong Chen ◽  
Ban Teng Liu ◽  
Lu Yao Xu
Keyword(s):  
Fuzzy Controller ◽  
Controller Design ◽  
Pendulum System ◽  
Single Input Single Output ◽  
Adaptive Fuzzy ◽  
Single Output ◽  
Inverted Pendulum System ◽  
Single Input ◽  
Indirect Adaptive Fuzzy Controller ◽  
Siso Systems

Indirect adaptive fuzzy controller with a self-structuring algorithm is proposed in this paper to achieve tracking performance for a class of uncertain nonlinear single-input single-output (SISO) systems with external disturbances. Selecting membership functions and the fuzzy rules are difficult in fuzzy controller design. As a result, self-structuring algorithm is used in this paper, which simplifies the design of fuzzy controller. Lyapunov analysis is used to prove asymptotic stability of the proposed approach. Application of the proposed control scheme to a second-order inverted pendulum system demonstrates the effectiveness of the proposed approach.

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