Sharif Digital Repository

In this paper, an adaptive control scheme, based on fuzzy logic systems, for pH control is addressed. For implementation of the proposed scheme no composition measurement is required. Stability of the closed-loop system is established and it is shown that the solution of the closed-loop system is uniformly ultimately bounded and under a certain condition, asymptotical stability is achieved. Effectiveness of the proposed controller is tested through simulation and experimental studies. Results indicate that the proposed controller has good performances in set-point tracking and load rejection and much better than that of a tuned PI controller. © 2009 Elsevier Ltd. All rights reserved  

As the oil production from conventional oil reservoirs is decreasing, oil production through Enhanced Oil Recovery (EOR) processes is supposed to compensate for both the oil production reduction in matured oil reservoirs and the worldwide dramatic increase in oil demand. Therefore, developing a strategy to choose an optimized EOR technique is crucial to find a resolution for production decline in oil reservoirs. A screening tool recommending the most appropriate EOR method is proposed in this study. An expert fuzzy logic system is employed to screen four well-known EOR methods including miscible CO2 injection, miscible HC gas injection, polymer flooding and steam injection based on the... 

In this paper, a novel decentralized adaptive control scheme for multiagent formation control is proposed based on an integration of artificial potential functions with robust control techniques. Fully actuated mobile agents with partially unknown models are considered, where an adaptive fuzzy logic system is used to approximate the unknown system dynamics. The robust performance criterion is used to attenuate the adaptive fuzzy approximation error and external disturbances to a prescribed level. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, and applicability on a large diversity of autonomous... 

In this article, design of an adaptive control scheme for a class of uncertain single-input single-output systems in strict feedback form via a backstepping technique has been proposed. It is assumed that system output and its derivatives are available. By virtue of the observability concept, it is shown that for this class of systems there exists a one-to-one map, which maps output and its derivatives to system states. By means of this mapping and using linearly parametrised approximators, such as fuzzy logic systems or neural networks, the uncertain nonlinear dynamics and unavailable states are estimated. The proposed adaptive controller guarantees that the closed-loop system is uniformly... 

This paper deals with growth control of cancer cells population using type-1 and interval type-2 fuzzy logic. A type-1 fuzzy controller is designed in order to reduce the population of cancer cells, adjust the drug dosage in a manner that allows normal cells re-grow in treatment period and maintain the maximum drug delivery rate and plasma concentration of drug in an appropriate range. Two different approaches are studied. One deals with reducing the number of cancer cells without any concern about the rate of decreasing, and the other takes the rate of malignant cells damage into consideration. Due to the fact that uncertainty is an inherent part of real systems and affects controller... 

In this paper, an adaptive control scheme for multi-agent formation control is proposed. This control method is based on artificial potential functions integrated with adaptive fuzzy sliding mode control technique. We consider fully actuated mobile agents with completely unknown dynamics. An adaptive fuzzy logic system is used to approximate the unknown system dynamics. Sliding Mode Control (SMC) theory is used to force agents' motion to obey the dynamics defined by the simple inter-agent artificial potential functions. Stability proof is given using Lyapunov functions, which shows the robustness of controller with respect to disturbances and system uncertainties. Simulation results are... 

As the oil production from conventional oil reservoirs is decreasing, oil production through Enhanced Oil Recovery (EOR) processes is supposed to compensate for both the oil production reduction in matured oil reservoirs and the worldwide dramatic increase in oil demand. Therefore, developing a strategy to choose an optimized EOR technique is crucial to find a resolution for production decline in oil reservoirs. A screening tool recommending the most appropriate EOR method is proposed in this study. An expert fuzzy logic system is employed to screen four well-known EOR methods including miscible CO2 injection, miscible HC gas injection, polymer flooding and steam injection based on the... 

In this paper, an adaptive fuzzy controller, based on backstepping technique, has been proposed for temperature control of a general class of continuous stirred tank reactors (CSTRs). Using the observability concept, an adaptive fuzzy controller using temperature measurement has been designed. A fuzzy logic system is used to estimate the concentration dependent terms and other unknown system parameters appearing in the control law. It is shown that the closed loop system is asymptotically stable and influences of minimum approximation error and external disturbance on the L2 norm of the output tracking error can be attenuated arbitrarily. The performance of the proposed controller has been... 

This paper presents an approach that integrates clinical methods with Neuro-Fuzzy system in order to diagnose Neonatal Jaundice in newborns. First, a fuzzy logic system designed with medical rules to model the uncertainty that exists in medical diagnosis. Then a fuzzy neural network with an evolutionary learning helps the system to learn the new data gained from the patient and to help the fuzzy system to update itself in an online manner. By combining the aforementioned systems, the proposed approach can help physicians to diagnose jaundice with low risk cost associated with this disease. © 2006 IEEE  

In this study, a stable observer-based feedback controller has been designed for treatment of hepatitis C infectious disease under interferon (IFN) therapy. In order to consider the memory behavior and uncertain nature of this biological system, an unknown dynamics fractional-order (FO) model has been utilized for describing the interactions between the healthy cells, infected cells, and hepatitis C virus (HCV). To cope with unknown dynamics, the fuzzy logic system (FLS) has been utilized. Limitation of the drug efficacy due to its negative side effects has been taken into account as an input saturation. In order to estimate the unknown states which are required for treatment, a full-order... 

In this paper we propose to control a bipedal robot in an unstable position by means of a PID controller that gains are turned by a fuzzy logic system. For that, a model of planar 3 linked segment consisting of limb, trunk and extended arms with fixed base is used. Fuzzy if-then rules are constructed based on human expert knowledge and biomechanics studies for tuning of PID's gain. For construction of tuning rules, we have developed an optical measuring system to record experimental data of balance keeping of a human in an unstable position. The control model is based on three sets of different global variables: (1) limb orientation and its derivative, (2) trunk/upper attitude and its...