Adaptive Fuzzy Control of Nonlinear in Parameters Uncertain Chaotic Systems Using Improved Speed Gradient Method

This paper presents an adaptive fuzzy controller for Nonlinear in Parameters (NLP) chaotic systems with parametric uncertainties. In the proposed controller, the unknown parameters are estimated by the novel Improved Speed Gradient (ISG) method, which is a modification of Speed Gradient (SG) algorithm. ISG employs the Lagrangian of two suitable objective functionals for on-line estimation of system parameters. The most significant advantage of ISG is that it is applicable to NLP systems and it results in a faster rate of convergence for the estimated parameters than the SG method. Estimated parameters are used to design the fuzzy controller and to calculate the Lyapunov exponents of the chaotic system adaptively. Furthermore, established on the well-known Takagi–Sugeno (T-S) fuzzy model, a LMI (Linear Matrix Inequality)-based fuzzy controller is designed and is tuned using estimated parameters and Lyapunov exponents. Throughout the controller design procedure, several important issues in fuzzy control theory including relaxed stability analysis, control input performance specifications, and optimality are taken into account. Combination of ISG parameter estimation method and T-S-based fuzzy controller yields an adaptive fuzzy controller capable to suppress uncertainties in parameters and initial states of NLP chaotic systems. Finally, simulation results are provided to show the effectiveness of the ISG and adaptive fuzzy controller on chaotic Lorenz system and Duffing oscillator.     

Crisis in Urban Water Systems during the Reconstruction Period: A System Dynamics Analysis of Alternative Policies after the 2003 Earthquake in Bam-Iran

Quick restoration of critical infrastructure systems, such as water, electrical power, natural gas, and transportation systems, are essential for rapid and effective post disaster recovery and reconstruction process. A number of previous studies have assessed vulnerability of infrastructure systems to various hazards such as earthquakes, but seldom have the impacts of post disaster policies been considered. In its assessment of the water system in post disaster situation after Bam earthquake, this paper examines the impacts of various reconstruction as well as water management policies on the system failure in operation in terms of the ability of Bam urban water system to meet increased demand trends. Adopting a system dynamics modeling approach and the concept of viability loops, the paper will show that in order to minimize further crisis in the water system during the reconstruction period stricter water management policies need to be considered.     

Infective endocarditis in a hemodialysis patient: a dreaded complication

Infection is the most common cause of death in hemodialysis patients, after cardiovascular disease. Dialysis access infections, with secondary septicemia, contribute significantly to patient mortality. The most common source is temporary catheterization. Bacteremia occurs commonly in patients receiving hemodialysis, with infective endocarditis being a relatively uncommon, but potentially lethal complication. Valvular calcification is the most significant risk factor. The diagnosis of infective endocarditis is made clinically and confirmed with the echocardiographic modified Duke's criteria. The most common pathogen is Staphylococcus aureus and the mitral valve is the most common site. Staphylococcus aureus infective endocarditis is commonly associated with embolic phenomenon. A high index of suspicion is critical in the early recognition and management of infective endocarditis. However, prevention of bacteremia is undoubtedly the best strategy with the early placement of arteriovenous fistulae. In the case of temporary catheterization, the use of topical mupirocin or polysporin and gentamicin and/or citrate locking is beneficial. Although catheter salvage has not been studied in randomized trials, catheter removal remains standard therapy during bacteremia.     

Event‐based allocation of airline check‐in counters: a simple dynamic optimization method supported by empirical data

This paper studies the real‐life problem of dynamically optimizing the number of airport check‐in counters to allocate for a single flight. The main feature of our work is the use of empirical data collected at the Singapore Changi Airport, which drives the dynamic optimization model of a parallel queues system. We propose an event‐based dynamic programming model that simplifies considerably the optimization analysis even for large‐scale problems with 700+ booked passengers. We investigate the following research questions: (a) For a particular flight, what is the optimal number of counters the system should open with and what is the corresponding optimal total cost? (b) Given the state of the system at any event epoch, should we open another counter or not and what is the optimal cost‐to‐go from this state? The empirical data we collected at the airport are used to test the assumptions, estimate the key parameters, and run the computational experiments. We apply our model to 14 flights at the Singapore Changi Airport and identify cases in which, depending on the cost parameters, the model advocates the use of either a dynamic or a static policy. Although the model concerns only an exclusive‐use system, it is flexible enough to apply to other configurations such as a common‐use system or a single‐queue, multicounter system.     

Terminal sliding mode observers for uncertain linear systems with matched disturbance

In this paper, a terminal sliding mode observer (TSMO) for systems with general state‐space representation is proposed. The effects of uncertainties and matched disturbances are incorporated in the system dynamics. Compared to conventional sliding mode observers, which are capable of finite time convergence of the measured states’ (outputs) errors and asymptotic convergence of unmeasured states’ errors, the proposed TSMO guarantees finite time convergence of all states. Three appropriate Lyapunov functions are defined for proving robust and finite time convergence of all state estimation errors of the TSMO. In addition, to highlight the effectiveness of the methodology, the developed TSMO is applied to a well‐known realistic wind turbine model. Results confirm that the proposed TSMO estimates all the states in finite time with good accuracy.     

State Estimation of Stochastic Impulsive System Via Stochastic Adaptive Impulsive Observer

This paper develops stochastic adaptive impulsive observer (SAIO) for state estimation of stochastic impulsive systems. Proposed observer is applicable to linear and a class of nonlinear stochastic impulsive systems. In addition to stochastic noises, the observer considers effect of parametric uncertainty and estimates unknown parameters by suitable adaptation laws. Interestingly, for certain impulsive systems, SAIO gives continuous state estimations from a discrete sequence of system output measurements. New theorems related to stochastic impulsive systems' boundedness are also developed and utilized to prove the boundedness of SAIO state estimation errors. Presented simulation results illustrate the effectiveness of the observer.     

Synchronizing chaotic systems with parametric uncertainty via a novel adaptive impulsive observer

This paper proposes a new class of observers, called adaptive impulsive observers. These observers are capable of estimating the states and unknown parameters of an uncertain system using the output of the system at discrete jump times only. Through a proposed theorem, the stability of the states estimation error system is proved and an upper bound on the maximum possible impulses (jumps) interval is given. Due to these advantages, the proposed adaptive impulsive observer is used in a chaotic systems synchronization scheme. The presented simulation results show the effectiveness of the proposed observer even when the coupling signal is scalar. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society