18 results with keyword: 'adaptive type fuzzy logic control non linear processes'
In the proposed optimization method, the inputs and the outputs of a type-1 fuzzy controller with a 49 rule base constitute the training data for the adaptive network-based
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In addition, Fuzzy logic controller based control strategy shows better result because fuzzy logic overcomes the mathematical difficulties of modeling of highly
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Control techniques such as linear control, optimal control, adaptive control, sliding-mode control, neural networks, or fuzzy logic deal with the control of
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Results show that the optimal interval type-2 fuzzy logic controller can reduce the noise effect in system performance much better than linear conventional and type-1 fuzzy
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The purpose of this study is to review the records of patients who underwent spinal, epidural, or general anesthesia for urgent cesarean delivery for non- reassuring fetal heart
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In Section 2 type-2 fuzzy sets and type-2 fuzzy logic systems (FLSs) are briefly described; Section 3 describes the process, its nonlinear state space model and the control problems
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[19] Hari Om Gupta, Lal Bahadur Prasad and Barjeev Tyagi, “Intelligent Control of Non Linear Inverted Pendulum Dynamical System with Disturbance Input Using Fuzzy Logic
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ABSTRACT: In this paper, adaptive network based fuzzy inference system (ANFIS) was used in control applications of a Heat Exchanger as interval type-2 fuzzy logic
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Deputy and Assistant Heads should have a 5 point pay range (ISR) on the Leadership scale, such that the maximum should not be more than the point below the Head’s ISR, and the
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[17], in which relative speed, distance headway and acceleration/deceleration rate of leading vehicle are the inputs to a fuzzy logic model.. Hybrid systems have
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Our approach is also compared with three evolving T2FLSs namely, self evolving interval type-2 fuzzy neural network (SEIT2FNN) utilising IT2FS in the antecedents and TSK interval
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Our approach is also compared with three evolving T2FLSs namely, self evolving interval type-2 fuzzy neural network (SEIT2FNN) utilising IT2FS in the antecedents and TSK interval
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economic service sector both in case of Indian (national government) and Odisha (sub-national. government) for the period 1980-81 to
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ABSTRACT: In this paper, adaptive network based fuzzy inference system (ANFIS) was used in control applications of a Shell and Tube Heat Exchanger as interval type-2 fuzzy
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In this report, development of linear and intelligent control techniques will be designed such as linear PID control, intelligent fuzzy logic control and hybrid fuzzy-PID
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If there are n processes in the ready queue and the time quantum is q, then each process gets 1/n of the CPU time in chunks of at most q time units at once. No process waits
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Abstract: This research work concentrates on developing a non linear control technique using PID control, Fuzzy Logic controller and SMC (Sliding Mode Controller)
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Thus, the performance of the user’s data processing in computer networks with the information security systems based on the adaptive safety control mechanism is reduced less,
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