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Rough Sets, Fuzzy Sets, Data Mining and Granular Computing - 13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011. Proceedings; 01/2011
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International Journal of Control Automation and Systems 01/2011; 9(5):980-986. · 0.75 Impact Factor
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Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Istanbul, Turkey, 10-13 October 2010; 01/2010
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Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Istanbul, Turkey, 10-13 October 2010; 01/2010
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Proceedings of the 7th International Symposium on Communication Systems Networks and Digital Signal Processing, CSNDSP 2010, University of Northumbria at Newcastle, UK, 21-23 July 2010; 01/2010
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Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Istanbul, Turkey, 10-13 October 2010; 01/2010
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Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Istanbul, Turkey, 10-13 October 2010; 01/2010
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ABSTRACT: An end-to-end congestion control design synthesis algorithm for the available-bit-rate traffic in high speed asynchronous-transfer-mode
networks is studied via applying the synergy of fuzzy-based intelligence and immune control laws. A fuzzy immune controller
is designed to overcome the adverse effects in the network caused by unavoidable uncertainties such as number of users, available
bit-rate bandwidth, and propagated transmission delays. Also an algorithm is proposed that can guarantee the minimum cell
rate in order to ensure the fair and full utilization of the bandwidth. Simulation investigation has been carried out and
the results show the proposed control synthesis is robust and the system performs effectively in adaptive mode. Hence the
network’s quality-of-service in is guaranteed too.
10/2009: pages 205-222;
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ABSTRACT: Stability issues for switched systems whose subsystems are all fuzzy systems, either continuous-time or discrete-time, are
studied and new results derived. Innovated representation models for switched fuzzy systems are proposed. The single Lyapunov
function method has been adopted to study the stability of this class of switched fuzzy systems. Sufficient conditions for
quadratic asymptotic stability are presented and stabilizing switching laws of the state–dependent form are designed. The
elaborated illustrative examples and the respective simulation experiments demonstrate the effectiveness of the proposed method.
09/2008: pages 155-168;
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ABSTRACT: For the Asynchronous Transfer Mode (ATM) networks with time-varying multiple time-delays, a more realistic model for the available
bit rate (ABR) traffic class with explicit rate feedback is introduced. A fuzzy-immune controller is designed, which can adjust
the rates of ABR on-line, overcome the bad effect caused by the saturation nonlinearity and satisfy the weighted fairness.
Also, the sufficient condition that guarantees the stability of the closed-loop system with a fuzzy-immune controller is presented
in theory for the first time. The algorithm exhibits good performance, and most importantly, has a solid theoretical foundation
and can be implemented in practice easily. Simulation results show that the control system is rapid, adaptive, robust, and
meanwhile, the quality of service (QoS) is guaranteed.
Journal of Control Theory and Applications 07/2008; 6(3):253-258.
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Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008, December 9-11, 2008, Cancún, México; 01/2008
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Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008, December 9-11, 2008, Cancún, México; 01/2008
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Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008, December 9-11, 2008, Cancún, México; 01/2008
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Proceedings of the 47th IEEE Conference on Decision and Control, CDC 2008, December 9-11, 2008, Cancún, México; 01/2008
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FUZZ-IEEE 2007, IEEE International Conference on Fuzzy Systems, Imperial College, London, UK, 23-26 July, 2007, Proceedings; 01/2007
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FUZZ-IEEE 2007, IEEE International Conference on Fuzzy Systems, Imperial College, London, UK, 23-26 July, 2007, Proceedings; 01/2007
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ABSTRACT: A new robust adaptive control design synthesis, which employs both high-order neural networks and math-analytical results, for a class of complex nonlinear mechatronic systems possessing similarity property has been derived. This approach makes an adequate use of the structural feature of composite similarity systems and neural networks to resolve the representation issue of uncertainty interconnections and subsystem gains by on-line updating the weights. This synthesis does guarantee the real stability in closed-loop but requires skills to obtain larger attraction domains. Mechatronic example of an axis-tray drive system, possessing uncertainties, is used to illustrate the proposed technique
Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on; 10/2006
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ABSTRACT: A completed case study on fuzzy logic control of thermal processes has been carried out using a professional laboratory oven for industrial purpose as an experimental test rig. It involved system engineering design analysis, control synthesis, and implementation as well as application software and signal interface design and development. The resulting expertise and lessons learned are reported in this contribution. The structure of PD type of fuzzy logic controllers is closely discussed along with synthesis issues of membership functions and knowledge rule base. Special software was developed using Microsoft Visual Studio, C++ and Visual basic for GUI for a standard PC platform. The application software designed and implemented has four modules: FIS editor, Rule Editor, Membership Function Editor and Fuzzy Controller with Rule Viewer. Quality and performance of the overall fuzzy process control system have been investigated and validated to fulfill the required quality specifications.
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ABSTRACT: In the past decades, representation models of dynamical processes have been developed via both traditional math-analytical and less traditional computational-intelligence approaches. This challenge to system sciences goes on because essentially involves the mathematical approximation theory. A comparison study based on cybernetic input-output view in the time domain on complex dynamical processes has been carried out. An analytical decomposition representation of complex multi-input-multi-output thermal processes is set relative to the neural-network approximation representations, and shown that theoretical background of both emanates from Kolmogorov's theorem. The findings provided a new insight as well as highlighted the efficiency and robustness of fairly simple industrial digital controls, designed and implemented in the past, inherited from input-output decomposition model approximation employed.
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ABSTRACT: A model of a kind of uncertain switched fuzzy systems is presented first, in which each subsystem is an uncertain fuzzy system. Then the robust stabilization problem to the system is studied and a solution proposed. When the upper bounds of the disturbances are unknown, and the actuator is serious failure and the residual part of actuator can not make original system stable, a reliable robust adaptive controller is constructed to guarantee the closed-loop system is uniformly ultimately bounded via using switching technique and multiple Lyapunov function approach. The switching strategy achieving system uniformly ultimately bounded of the uncertain switched fuzzy system is given. An illustrative example is given that demonstrates the feasibility and the effectiveness of the proposed method.
