statistical hydrodynamics of lattice gas automata we investigate the space and time behavior of spontaneous thermohydrodynamic fluctuations in a simple fluid modeled by a lattice gas automaton and develop the statistical mechanical theory of thermal lattice gases to compute the dynamical structure factor i e the power spectrum of the density correlation function a comparative analysis of the theoretical predictions with our lattice gas simulations is presented the main results are i the spectral function of the lattice gas fluctuations is fully compatible with the spectrum obtained from experimental measurements performed in real fluids ii in the long wavelength limit the correlations of lattice gas fluctuations are well described by the landau placzek theory iii at short wavelengths and or at low densities good agreement is obtained between the lattice gas simulation results and the boltzmann theory these results provide solid support to the validity of the thermal lattice gas automaton as a consistent model system for real fluids

adaptive robot under fuzzy control an arc welding industrial robot isotron 251 is treated its adaptation is considered as an attribute of the robot to trace an arbitrary pretaught welding seam by means of a noncontact laser sensor the control strategy is proposed to use a fuzzy model describing uncertainty of working conditions the experience shows how the notion of fuzzy sets powers is used for on line estimation prediction and control of robot motions the control algorithm has been tested by a three level microprocessor controller

direct digital control auto tuning and supervision using fuzzy logic abstract we describe algorithms for the design and implementation of fuzzy logic controllers and present results of their application to temperature control of a heated air stream auto tuning methods are studied for adjustment of conventional parameters to compensate for actual values of control variables or of external variables and for improvement of performance from observation of results conditions for verifying the consistency of the linguistic protocol with its implementation are presented in an appendix

on the application of fuzzy sets theory to the optimal flood control problem arising in water resources systems abstract we first survey the application of fuzzy sets theory to various problems occurring in water resources systems the problem of optimal flood control planning by an appropriate integration of structural and non structural measures with the objective of optimizing the flood damage reduction due to recurrent floods is modeled via fuzzy sets methodologies a two level optimization model appropriate for planning decisions first on a regional or local level and then on a national level is proposed a third phase involving coordination is appended in particular a fuzzy optimization model involving an adroit combination of fuzzy dynamic programming type reasoning and a branch and bound type search procedure is offered as a more utilitarian approach than its crisp equivalent the performance of the algorithm is illustrated with an example

force evaluation in the lattice boltzmann method involving curved geometry the present work investigates two approaches for force evaluation in the lattice boltzmann equation the momentum exchange method and the stress integration method on the surface of a body the boundary condition for the particle distribution functions on curved geometries is handled with second order accuracy based on our recent works mei et al j comput phys 155 307 1999 ibid 161 680 2000 the stress integration method is computationally laborious for two dimensional flows and in general difficult to implement for three dimensional flows while the momentum exchange method is reliable accurate and easy to implement for both two dimensional and three dimensional flows several test cases are selected to evaluate the present methods including i two dimensional pressure driven channel flow ii two dimensional uniform flow past a column of cylinders iii two dimensional flow past a cylinder asymmetrically placed in a channel with vortex shedding iv three dimensional pressure driven flow in a circular pipe and v three dimensional flow past a sphere the drag evaluated by using the momentum exchange method agrees well with the exact or other published results

hydrodynamic behavior of lattice boltzmann and lattice bhatnagar gross krook models we present a numerical analysis of the ranges of validity of classical and generalized hydrodynamics for lattice boltzmann and lattice bhatnagar gross krook bgk methods in two and three dimensions as a function of the collision parameters of these models our analysis is based on the wave number dependence of the evolution operator good ranges of validity are found as long as the bgk relaxation time is chosen smaller than or equal to unity the additional degree of freedom in a two parameter bgk model can give further improvements

mesoscopic modeling of flow and dispersion phenomena in fractured solids the problem of hydrodynamic dispersion in porous media is considered and numerical predictions of the mixing degree in a single intersection are provided the flow field in the intersection and adjacent pores or fractures is calculated using a lattice boltzmann model for single phase flow a particle tracking scheme is used subsequently that monitors the migration of solute particles in the area of the intersection taking into account the local flow field and a brownian field mixing is quantified in terms of the probability of solute transfer across the junction into the opposite fracture to circumvent the problem of large computational times for cases of fast flow compared to diffusion a lattice boltzmann advection diffusion model is used that offers significant savings on computational time without sacrificing accuracy it is shown that the solute dispersion in a fracture network is a strong function of the reynolds number even if the peclet number remains constant due to the extensive recirculation areas that may develop in regions close to the junction

experiments with the use of a rule based self organising controller for robotics applications abstract the rule based self organising controller soc has as one of its main advantages the fact that there is no need to have a mathematical description of the system to be controlled in this controller the rules are linguistic statements expressed mathematically through the concepts of fuzzy sets and correspond to the actions a human operator would take when controlling a given process this paper describes several experiments which were performed with soc the control was considered of both simulated linear and non linear processes the performance of the controller was investigated for step inputs as well as for waveforms which the process output had to track the effect of process noise was also considered it was shown that soc had a performance slightly superior to that of a pid controller when noise was present and the process had time varying coefficients as well as pronounced non linear characteristics this paper also reviews some of the successful initial work carried out in connection with the application of soc to a revolute joint robot arm this presented a system with highly non linear dynamics to each of several socs working in paralle the sampling times of only a few milliseconds were short compared with several minutes or even hours associated with previous applications of fuzzy controllers to cement kilns

solution of optimal control problems with lumped parameters having single or multiple goal objectives in fuzzy environment abstract in this paper optimal control problems ocp of both linear and nonlinear type with lumped parameters are considered continuous ocp with single or multiple objectives are transformed to finite dimensional optimization problems through discretization the formulation of goal optimal control problem gocp using goal programming methodology first given by levary 1986 for equal time subintervals is extended for unequal subintervals by a generalized formulation the concept of local and global goals proposed here is very useful for multicriteria dynamic optimization problems in several physical situations ocp involve fuzziness in their goals priorities parameters or relative weights and associated linguistic variables etc a new formulation of ocp in fuzzy environment is given as a fuzzy goal optimal control problem fgocp and the solution procedure is illustrated by linear and nonlinear examples

a heuristic self tuning fuzzy controller abstract in this paper a self tuning fuzzy controller based on the tuning of scaling factors is presented the tuning schemes are tuning the scaling factors is individual tuning rules the tuning rules are transformed into numeric tuning tables by applying suitable membership functions so that the adjustings of the scaling factors are merely matrix mappings since the tuning rules are constructed with the control signal and the output error and change in output error of the plant as their antecedent parts the tuning processes have the advantage of real time property simulation results with a perturbed servo and the inverted pendulum system as the controlled plants show the performance and adaptivity of the proposed controller

expert fuzzy controller abstract we describe a fuzzy controller based on our general purpose fuzzy expert system shell flops we take a decision theoretic view in designing an optimal fuzzy controller the variables in the decision problem are 1 the defuzzification rules 2 the fuzzification rules and 3 the fuzzy control rules the objective function is composed of fuzzy goals specified for each system output we differentiate between decision making under certainty risk or uncertainty depending whether or not random elements are present in the system an example is presented illustrating varying the defuzzification rules to improve system performance

fuzzy modelling and identification with genetic algorithm based learning abstract a ga based learning algorithm is proposed in this paper for the identification of tsk models the algorithm consists of four blocks partition block ga block tuning block and termination block the partition block is to determine an estimated partition of input variables the ga block is to optimise the structure of a tsk model the tuning block is to fine tune the parameters of the tsk model using the gradient descent based approach and the termination block checks that the resultant tsk model is satisfactory the proposed gabl algorithm has the advantage of simplicity flexibility high accuracy and automation the presented numerical examples indicate that the gabl algorithm is effective in constructing a good tsk model for complex nonlinear systems

model reference adaptive fuzzy control a linguistic space approach in this paper a model reference adaptive fuzzy controller with the adaptivity achieved by tuning both the scaling factors and the control rules is presented the proposed tuning strategy includes two parts 1 by referring a reference trajectory created in the linguistic space to tune the scaling factors and 2 by applying an auxiliary correction matrix generated by specific tuning rules to compensate the control rules since only the control signal the output error and change in output error of the plant are needed in the construction of the reference trajectory and the tuning rules the tuning strategy has the advantage of real time property simulation results with a damping process and an oscillating process as the controlled plants show the performance and adaptivity of the proposed controller

derivation and application of an expert fuzzy optimal control system abstract this paper presents derivation of a fuzzy optimal controller which may be used to develop a knowledge based expert control system for supervising and tuning of conventional feedback control loops a general theory based on the conceptual framework for optimization in a fuzzy environment is presented for the development of linear and nonlinear fuzzy optimal control systems this technique is based on integration of the optimal control theorem and fuzzy variables the resulting expert controller is expressed in the form of linguistic fuzzy rules representing the knowledge base for tuning of the feedback control loops tuning inferences are made from the response of local feedback control loops by applying the compositional rule of inference to the knowledge base

fuzzy self organizing controller and its application for dynamic processes abstract this paper deals with a self organizing controller used in real time and its application for dynamic processes the control policy of the controller is able to develop and improve automatically a new self organizing control algorithm which modifies the fuzzy control decision table is presented in this paper the control algorithm needs much less computation time and memory of the computer this paper provides two examples of the fuzzy self organizing control a set of experiment results is described it shows that the controller can be applied to some processes such as processes with time lag and non linearity or one whose parameter or running conditions are varied which were usually not controlled very well with a conventional controller

on pid controller tuning using orthonormal series identification abstract the step response of a closed loop system is identified by means of a laguerre expansion this offers certain advantages over arma models namely lack of bias in the estimates structural flexibility and the ability to precompute the regressors the laguerre coefficients of the retuned system are calculated in terms of the tuning constants and a quadratic performance index is optimized results from simulations and from industrial trials are given

studies on the output of fuzzy controller with multiple inputs abstract in this paper we discuss the output of a fuzzy controller in which an arbitrary number of fuzzy control inputs and an arbitrary number of fuzzy sets employed to fuzzify every linguistic variable are considered in the fuzzy control rules a rule base with a rule mapping concept is considered a defuzzifier with the general t norm and t conorm operators is formulated a triangular family is adopted so that the defuzzifier of the complete rule mapping is represented by a formula consisting of only some rules using a specific logic pair to evaluate values we derive that the output of the fuzzy controller can be simply represented by a linear parametric function of the inputs to the fuzzy controller

a method for closed loop automatic tuning of pid controllers abstract a simple method for the automatic tuning of pid controllers in closed loop is proposed a limit cycle is generated through a nonlinear feedback path from the process output to the controller reference signal the frequency of this oscillation is above the crossover frequency and below the critical frequency of the loop transfer function the amplitude and frequency of the oscillation are estimated and the control parameters are adjusted iteratively such that the closed loop transfer function from the controller reference to the process output attains a specified amplitude at the oscillation frequency

a rule self regulating fuzzy controller abstract the most effective way to improve the performance of a fuzzy controller may be to optimize the fuzzy control rules usually fuzzy control rules are generated by 1 translating the operators experience into fuzzy linguistic form directly 2 monitoring and summarizing the control behaviour of the operators 3 modelling the process to be controlled using fuzzy set theory 4 self organizing in running of the control systems different from the above means the authors in 10 have proposed a method to regulate fuzzy control rules where the control rules are represented by an analytic expression with a regulating factor the authors in this paper employ such a method and use a simplified fuzzy control algorithm which allows fuzzy control rules to be regulated on line thus constructing a rule self regulating fuzzy controller rsfc simulation results demonstrate that the performance of rsfc is better than that of a non rule regulating fuzzy controller

self diffusion in ca fluids tagged particle properties such as the diffusion coefficients and velocity autocorrelation function are calculated in the mean field approximation for all standard lattice gas cellular automata defined on hyper cubic square and triangular lattices and on a line tagged particle dynamics is introduced through maximally random or minimally random collision rules for a completely filled lattice the former reduces to a random walk the latter to ballistic motion

genetic algorithm based optimal fuzzy controller design in the linguistic space in this paper a genetic algorithm ga based optimal fuzzy controller design is proposed the design procedure is accomplished by establishing an index function as the consequent part of the fuzzy control rule the inputs of the controller after scaling are utilized by the index function for computing the output linguistic value this linguistic value can then be used to map the suitable fuzzy control actions this proposed novel fuzzy control rule has crisp input and fuzzified output characteristics the index function plays a role in mapping the desired fuzzy sets for defuzzification resulting in a controlled hypersurface in the linguistic space formed by the input fuzzy variables two types of index functions both linear and nonlinear are introduced for controlling systems with different degrees of nonlinearity the parameters of the index function are obtained by applying a simple ga with a suitable fitness function various controlled systems result in various parameter sets depending on their dynamics under the acquired optimal parameter set the optimal index function can be used to generate the desired control actions several simulation examples are given to verify the performance of the proposed ga based fuzzy controller

analytic solutions of linearized lattice boltzmann equation for simple flows a general procedure to obtain analytic solutions of the linearized lattice boltzmann equation for simple flows is developed as examples the solutions for the poiseuille and the plane couette flows in two dimensional space are obtained and studied in detail the solutions not only have a component which is the solution of the navier stokes equation they also include a kinetic component which cannot be obtained by the navier stokes equation the kinetic component of the solutions is due to the finite mean free path effect comparison between the analytic results and the numerical results of lattice gas simulations is made and they are found to be in accurate agreement

lattice boltzmann modeling of microchannel flow in slip flow regime we present the lattice boltzmann equation lbe with multiple relaxation times mrt to simulate pressure driven gaseous flow in a long microchannel we obtain analytic solutions of the mrt lbe with various boundary conditions for the incompressible poiseuille flow with its walls aligned with a lattice axis the analytical solutions are used to realize the dirichlet boundary conditions in the lbe we use the first order slip boundary conditions at the walls and consistent pressure boundary conditions at both ends of the long microchannel we validate the lbe results using the compressible navier stokes ns equations with a first order slip velocity the information preservation direct simulation monte carlo ip dsmc and dsmc methods as expected the lbe results agree very well with ip dsmc and dsmc results in the slip velocity regime but deviate significantly from ip dsmc and dsmc results in the transition flow regime in part due to the inadequacy of the slip velocity model while still agreeing very well with the slip ns results possible extensions of the lbe for transition flows are discussed

generating rules for fuzzy logic controllers by functions abstract in this paper we introduce a method of generating control rules for fuzzy logic controllers called parametric functions method by this method we can obtain control rules by adjusting several parameters

norm inequalities for a class of elementary operators generated by analytic functions with non negative taylor coefficients in ideals of compact operators related to p modified unitarily invariant norms

a self tuning fuzzy controller abstract the aim of a fuzzy controller is to compensate the dynamic characteristics of the controlled system it is the same purpose as for the fuzzy logic controller flc now the best design of the flc is required for achievement of this purpose but such a controller has not yet been completely designed because the fuzzy controller is constructed of control rules which are ambiguously described by conventional controller strategies and expert knowledge and because its structure theory is not well established yet that is in order to construct the best rules a highly skilled technique and a tuning technique using trial and error are required as a way to easily design a flc a method which improves a given standard flc is considered in this paper we propose a self tuning algorithm of the flc it has two functions in adjusting the scaling factors which are the parameters of the flc and in improving the control rules of flc by evaluating the control response at real time and the control results after operations we add these functions to the flc and design the self tuning fuzzy controller stfc this makes the flc a good controller

fuzzy optimal control the problem of fuzzy optimal control of nonlinear systems is formulated and solved on the basis of fuzzy mathematical programming the fuzzy optimal control problem is extended to the case of multicriteria optimal control a particular case of fuzzy optimal control with fuzzy objective function and crisp transversality conditions is also considered

an investigation into curved and moving boundary treatments in the lattice boltzmann method curved boundary treatments provide a means of improving the computational accuracy of the conventional stair shaped approximation used in lattice boltzmann lb simulations furthermore curved boundary treatments can be extended to the modeling of moving boundary problems simply by adding a momentum term to the bounced distribution functions at the solid surface this study commences by investigating three conventional interpolating treatments for curved boundaries in lb problems namely the filippova and hanel fh model o filippova d hanel grid refinement for lattice bgk models j comput phys 147 1998 219 228 bouzidi s model m bouzidi m firdaouss p lallemand momentum transfer of a boltzmann lattice fluid with boundaries phys fluids 13 11 2001 3452 3459 and yu s model d yu r mei w shyy a unified boundary treatment in lattice boltzmann method aiaa 2003 0953 new york 2003 previous investigations have indicated that the interpolations would break the mass conservation at the boundaries since the inaccuracy in evaluation of the momentum transfer at boundary leads to a net mass flux based on this reason a concept of the interpolation free treatment for modeling the curved and moving boundary conditions is proposed to overcome the drawback of these interpolation based curved boundary treatments in present study two interpolation free models are then proposed namely on site interpolation free osif and composite interpolation free cpif models these proposed models are initially applied to simulate the flow in the channels containing a stationary square block positioned at various locations along the longitudinal axis the simulations results are then compared with those obtained using the three conventional interpolating treatments the interpolation free models are then applied to the case of moving boundary problems in which a square block and a cylindrical block respectively move with a constant speed along a channel containing stationary flows to test the galilean effect of the proposed cpif model a couette flow past the stationary square cylinder block with the moving top bottom walls is simulated overall the numerical results show that the proposed interpolation free curved treatment models significantly improve the accuracy of the mass flux computation near the solid surface and thus enhance the accuracy of the momentum interaction at the moving boundaries

on line off line optimization of complex processes using a linguistic self organized optimizing control scheme abstract chemical processes usually have a complicated structure and are subjected to unknown long term and short term disturbances many process optimization schemes were developed under the assumption of the existence of a model that can predict the process steady state and or dynamics however such a model may not be precise nor even exist a rule based methodology without the need of such a model is hence developed in this work the optimizing control scheme developed here is actually a combination of a modified version of the linguistic control scheme developed by procyk and mamdani and the concept of reduced gradient optimization it is assumed that the objective function and constraints of the optimization problem are functions of manipulated variables and measurements only the optimizing control algorithm is also formulated into a look up table the rule based optimizing control scheme possesses three important properties adapting learning and decision making some numerical examples of multivariable nature and constrained situations are solved by this approach and compared with well known approaches it is shown that the method is superior to the previous methods a process system consisting of a series of cstr has been simulated as an illustrative example the simulation results show that the optimizing control scheme is promising and should be of interest to process industry

regular article an accurate curved boundary treatment in the lattice boltzmann method the lattice boltzmann equation lbe is an alternative kinetic method capable of solving hydrodynamics for various systems major advantages of the method are due to the fact that the solution for the particle distribution functions is explicit easy to implement and natural to parallelize because the method often uses uniform regular cartesian lattices in space curved boundaries are often approximated by a series of stairs that leads to reduction in computational accuracy in this work a second order accurate treatment of the boundary condition in the lbe method is developed for a curved boundary the proposed treatment of the curved boundaries is an improvement of a scheme due to o filippova and d hanel 1998 j comput phys 147 219 the proposed treatment for curved boundaries is tested against several flow problems 2 d channel flows with constant and oscillating pressure gradients for which analytic solutions are known flow due to an impulsively started wall lid driven square cavity flow and uniform flow over a column of circular cylinders the second order accuracy is observed with a solid boundary arbitrarily placed between lattice nodes the proposed boundary condition has well behaved stability characteristics when the relaxation time is close to 1 2 the zero limit of viscosity the improvement can make a substantial contribution toward simulating practical fluid flow problems using the lattice boltzmann method

analytical solution of axi symmetrical lattice boltzmann model for cylindrical couette flows abstract analytical solution for the axi symmetrical lattice boltzmann model is obtained for the low mach number cylindrical couette flows in the hydrodynamic limit the present solution is in excellent agreement with the result of the navier stokes equation since the kinetic boundary condition is used the present analytical solution using nine discrete velocities can describe flows with the knudsen number up to 0 1 meanwhile the comparison with the simulation data obtained by the direct simulation monte carlo method shows that higher order lattice boltzmann models with more discrete velocities are needed for highly rarefied flows

lattice boltzmann method for 3 d flows with curved boundary in this work we investigate two issues that are important to computational efficiency and reliability in fluid dynamic applications of the lattice boltzmann equation lbe 1 computational stability and accuracy of different lattice boltzmann models and 2 the treatment of the boundary conditions on curved solid boundaries and their 3 d implementations three athermal 3 d lbe models q15d3 q19d3 and q27d3 are studied and compared in terms of efficiency accuracy and robustness the boundary treatment recently developed by filippova and hanel 1998 j comp phys 147 219 and mei et al 1999 j comp phys 155 307 in 2 d is extended to and implemented for 3 d the convergence stability and computational efficiency of the 3 d lbe models with the boundary treatment for curved boundaries were tested in simulations of four 3 d flows 1 fully developed flows in a square duct 2 flow in a 3 d lid driven cavity 3 fully developed flows in a circular pipe and 4 a uniform flow over a sphere we found that while the 15 velocity 3 d q15d3 model is more prone to numerical instability and the q27d3 is more computationally intensive the q19d3 model provides a balance between computational reliability and efficiency through numerical simulations we demonstrated that the boundary treatment for 3 d arbitrary curved geometry has second order accuracy and possesses satisfactory stability characteristics

fuzzy adaptive control of a first order process abstract fuzzy adaptive control of a first order process with a varying gain and time constant is demonstrated the fuzzy adaptive controller is based on a fuzzy model based controller that uses an explicit fuzzy model of the process adaptation is achieved by the addition of on line identification of the fuzzy process model starting with a crude initial model the adaptive controller matches the model to the process to self tune the controller the model is further modified when the operating point is changed to adapt the controller to the new process conditions two different fuzzy identification algorithms are both shown to provide a successful fuzzy adaptive controller the robustness of the algorithms in the presence of process noise is investigated and improved by the addition of weighting factors

self learning fuzzy controllers based on temporal backpropagation a generalized control strategy that enhances fuzzy controllers with self learning capability for achieving prescribed control objectives in a near optimal manner is presented this methodology termed temporal backpropagation is model sensitive in the sense that it can deal with plants that can be represented in a piecewise differentiable format such as difference equations neural networks gmdh structures and fuzzy models regardless of the numbers of inputs and outputs of the plants under consideration the proposed approach can either refine the fuzzy if then rules of human experts or automatically derive the fuzzy if then rules if human experts are not available the inverted pendulum system is employed as a testbed to demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired fuzzy controller

cellular automaton fluids 1 basic theory continuum equations are derived for the large scale behavior of a class of cellular automaton models for fluids the cellular automata are discrete analogues of molecular dynamics in which particles with discrete velocities populate the links of a fixed array of sites kinetic equations for microscopic particle distributions are constructed hydrodynamic equations are then derived using the chapman enskog expansion slightly modified navier stokes equations are obtained in two and three dimensions with certain lattices viscosities and other transport coefficients are calculated using the boltzmann transport equation approximation some corrections to the equations of motion for cellular automaton fluids beyond the navier stokes order are given

a stability approach to fuzzy control design for nonlinear systems abstract by the application of fuzzy set theory a method for feedback control of nonlinear systems based on the principle of sliding mode control is developed called fuzzy sliding mode control the control method provides a simple way to achieve asymptotic stability of the systems other attractive features of the method include a minimal realization of the fuzzy controller and robustness against model uncertainties and external disturbances in addition the method is capable of handling the chattering problem inherent to sliding mode control simply and effectively a simulation study of an inverted pendulum system is presented to demonstrate these features of the method also it is indicated that the method is easy to use for practicing control engineers