Design a Novel SISO Off-line Tuning of Modified PID Fuzzy Sliding Mode Controller

Shahcheraghi, Ali; Piltan, Farzin; Mokhtar, Masoud; Avatefipour, Omid; Khalilian, Alireza

doi:10.5815/ijitcs.2014.02.10

Cited by 15 publications

(23 citation statements)

References 35 publications

(62 reference statements)

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“…The remaining terms in the dynamic equations resulting from gravitational potential energies and spring energies are collected in the matrix . The coefficient matrices of the dynamic equations are given below, [58][59][60][61][62][63][64][65][66][67][68][69]. However the application area for fuzzy control is really wide, the basic form for all command types of controllers consists of;…”

Section: Dynamic Formulation Of Continuum Robotmentioning

confidence: 99%

“…The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input. This in turn would further inspire multi-uncertainties testing for continuum robot [58][59][60][61][62][63][64][65][66][67][68][69]. In project we can used fuzzy logic theory when a plant can be considered as a black box with outputs available for measurement and a possibility of changing inputs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design Intelligent Model base Online Tuning Methodology for Nonlinear System

Roshanzamir¹,

Piltan²,

Mozafari³

et al. 2014

IJMECS

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Abstract-In various dynamic parameters systems that need to be training on-line adaptive control methodology is used. In this paper fuzzy model-base adaptive methodology is used to tune the linear Proportional Integral Derivative (PID) controller. The main objectives in any systems are; stability, robust and reliability. However PID controller is used in many applications but it has many challenges to control of continuum robot. To solve these problems nonlinear adaptive methodology based on model base fuzzy logic is used. This research is used to reduce or eliminate the PID controller problems based on model reference fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.Index Terms-PID Controller, Fuzzy logic methodology, Adaptive Techniques, Model reference fuzzy tuning.

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Section: Dynamic Formulation Of Continuum Robotmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design Intelligent Model base Online Tuning Methodology for Nonlinear System

Roshanzamir¹,

Piltan²,

Mozafari³

et al. 2014

IJMECS

Self Cite

View full text Add to dashboard Cite

show abstract

“…This paper proposed a self-adaptive modified harmony search (MHS) algorithm to address the deficiencies of the previous methods for handling the conflicting targets of the problem. Mathematically, the concerned multi-objective optimization problem is formulated in (15) incorporate to the constraints [30]. …”

Section: Multi-objective Optimization Algorithmmentioning

confidence: 99%

“…In [10], fuzzy logic theory idea is used to investigate the optimal capacitor allocation problem. Recently, fuzzy set theory has caught the attraction of researcher for designing intelligent systems in broad range of applications such as electrical load forecasting [11], designing fuzzy controller for industrial robots [12,13], powerful tool for system uncertainty compensator and optimization method with high rate of accuracy and performance [14,15], adaptive model for non-linear controllers [16,17], etc. Here the system is modeled by using fuzzy membership function which most challenging issue would be the proper choose of membership functions and identify corresponding rule properly and precisely.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Reactive Power Compensation Using Capacitor Allocation Based on Modified Harmony Search Algorithm

Wáng¹,

Cheong²,

Chén³

2017

IJCATR

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This paper presents a heuristics based approach for capacitor allocation problem incorporating Point Estimate Method (PEM) based analysis to attain optimal capacitor reallocation in radial distribution systems. The proposed probabilistic method is used to achieve optimal capacitor allocation associated with the active/reactive loads forecasted error as well as energy loss reduction by taking into account the cost function coefficients. This problem is formulated as a mix integer non-linear, discrete multi-objective problem which be in need of a robust optimization tool to avoid trapping in local optima. The proposed solution based on modified harmony search (MHS) algorithm employ to search for a set of Pareto optimal value of objective functions which save in memory that called repository. Moreover, a fuzzy clustering method is utilized to control the size memory (repository) for the concerned problem.The proposed approach has been tested on IEEE 9 buses to check feasibility and robustness of the proposed approach.

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“…To name some of the powerful expert and data-driven methods: Artificial Neural Network, fuzzy systems, decision tree, Support Vector Machine (SVM), Bayesian Network, etc. [6][7] [8]. It goes without saying that data evaluation which have been attained from patients can be considered as an important factor to develop an efficient and accurate diagnostic method.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of Breast Cancer using Decision Tree and Artificial Neural Network Algorithms

Higa¹

2018

IJCATR

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Breast Cancer Diagnosis and Prognosis are two medical applications which have posed a challenge to the researchers. The use of machine learning and data mining techniques has revolutionized the whole process of breast cancer Diagnosis and Prognosis. Breast Cancer Diagnosis distinguishes benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast Cancer is likely to recur in patients that have had their cancers existed. Thus, these two problems are mainly in the scope of the classification problems. Most data mining methods which are commonly used in this domain are considered as classification category and applied prediction techniques assign patients to either a" benign" group that is non-cancerous or a" malignant" group that is cancerous. Hence, the breast cancer diagnostic problems are basically in the scope of the widely discussed classification problems. In this study, two powerful classification algorithms namely decision tree and Artificial Neural Network have been applied for breast cancer prediction. Experimental results show that the aforementioned algorithms has a promising results for this purpose with the overall prediction accuracy of 94% and 95.4%, respectively.

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Design a Novel SISO Off-line Tuning of Modified PID Fuzzy Sliding Mode Controller

Cited by 15 publications

References 35 publications

Design Intelligent Model base Online Tuning Methodology for Nonlinear System

Design Intelligent Model base Online Tuning Methodology for Nonlinear System

Stochastic Reactive Power Compensation Using Capacitor Allocation Based on Modified Harmony Search Algorithm

Diagnosis of Breast Cancer using Decision Tree and Artificial Neural Network Algorithms

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