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Colored self-compacting mortar (C-SCM) is a novel cementitious product that has been recently used in decoration and rehabilitation and has improved esthetic quality of architectural constructions. C-SCM is susceptible to strength decrease due to excessive pigment presence in the mixture. Optimum pigment content with respect to color intensity and mechanical performance is an important matter that should be determined to prevent mortar failure after construction. In this research, two inorganic pigments in production of colored self-compacting mortar were utilized. The impact of titanium dioxide (TiO2) and iron hydroxide (FeO(OH)) contents on behavior of C-SCMs was investigated in white and gray cement matrixes. Experiments included measurements of compressive strength of mortar cubes and cylinders, flexural strength and colorimetric properties. Analyses on compressive and flexural toughness were applied, as well. It was concluded that pigment content in mix design of colored self-compacting mortar could be optimized with regard to color quality in surface and mechanical strength of the product. Results implied that 5 and 2% of titanium dioxide were the saturation points of color and strength, respectively, and iron hydroxide at 10% was unsurpassed in C-SCMs containing white cement. Application of both pigments in gray SCMs caused the saturation points of color and strength to occur at 10 and 2%, respectively.

Abstract: Special emphasis is put on to correlating the changes in phase composition with wettability of hardened cement paste. The results were found in contradiction, because it was demonstrated by XRD analysis that by increment in curing ages, high energy products are developed in the matrix which increases surface free energy. In contrast, surface evaporation of the water and bulk hydration cause a decrease in hydrophilic properties of the surface free energy. It was concluded that the latter phenomenon has more important impact than surface free energy. [Copyright &y& Elsevier]

A smart decision-making framework based on genetic algorithms (GA) and fuzzy logic is proposed for control and energy management of micro-grids. Objectives are to meet the demand profile, minimize electricity consumption cost, and to modify air pollution under a dynamic electricity pricing policy. The energy demand in the micro-grid network is provided by distributed renewable energy generation (coupling solar and wind), battery storage and balancing power from the electric utility. The fuzzy intelligent approach allows the calculation of the energy exchange rate of the micro-grid storage unit as a function of time. Such exchange rate (or decision-making capability) is based on (1) the electrical energy price per kilowatt-hour (kWh), (2) local demand (load), (3) electricity generation rate of renewable resources (supply), and (4) air pollution measure, all of which are sampled at predefined rates. Then, a cost function is defined as the net dollar amount corresponding to electricity flow between micro-grid and the utility grid. To define the cost function one must consider the cost incurred by the owner of the micro-grid associated to its distribution losses, in addition to its demand and supply costs, in such a way that a positive cost translates to owner losses and a negative cost is a gain. Six likely scenarios were defined to consider different micro-grid configurations accounting for the conditions seen in micro-grids today and also the conditions to be seen in the future. GA is implemented as a heuristic (DNA-based) search algorithm to determine the sub-optimal settings of the fuzzy controller. The aforementioned net cost (which includes pricing, demand and supply measures) and air pollution measures are then compared in every scenario with the objective to identify best-practices for energy control and management of micro-grids. Performance of the proposed GA-fuzzy intelligent approach is illustrated by numerical examples, and the capabilities and flexibility of the proposed framework as a tool for solving intermittent multi-objective function problems are presented in detail. Micro-grid owners looking into adopting a smart decision-making tool for energy storage management may see an ROI between 5 and 10.

The production of sewage sludge from waste water treatment plants is increasing all over the world. Disposal of sewage sludge ash is a serious environmental problem. If we think of the areas needed for sludge ash disposal, we clearly understand the importance of reusing sewage sludge ash in concrete. This paper presents results related to the replacement of sand by sewage sludge ash. The sludge was characterized for chemical composition (XRF analysis), crystalline phases (XRD analysis) and pozzolanic activity. The effects of incineration on crystal phases of dry sludge were investigated. Two (W/C) ratios (0.55 and 0.45) and three sludge percentages (5%, 10% and 20%) by cement mass were used. The mechanical performance of SSAC at different curing ages (3, 7, 28 and 90 days) was assessed by means of mechanical tests. Results show that sewage sludge ash leads to a reduction in density and mechanical strength. Results also show that concrete with 20% of sewage sludge ash and W/C=0.45 has a 28 day compressive strength of almost 30MPa.

This paper compares the adhesion strength between three polymeric fibres (polypropylene (PP), nylon66 (N66) and polyacrylonitrile (PAN)) embedded in a cement paste. The specimens were prepared at a water to cement ratio (w/c) of 0.5 and tested after 7, 14 and 28 curing days. It was found that although the adhesion between the polymeric fibres to the cement matrix is an important factor, the energy absorption capacity or energy dissipation ability of the fibres, plays a more important role in the improvement of the cementitious composites fracture toughness. Scanning electron micrographs were used to characterize the fibres surface before and after the Pull-out tests.

In this paper, we propose the distributed bees algorithm (DBA) for task allocation in a swarm of robots. In the proposed scenario, task allocation consists in assigning the robots to the found targets in a 2-D arena. The expected distribution is obtained from the targets' qualities that are represented as scalar values. Decision-making mechanism is distributed and robots autonomously choose their assignments taking into account targets' qualities and distances. We tested the scalability of the proposed DBA algorithm in terms of number of robots and number of targets. For that, the experiments were performed in the simulator for various sets of parameters, including number of robots, number of targets, and targets' utilities. Control parameters inherent to DBA were tuned to test how they affect the final robot distribution. The simulation results show that by increasing the robot swarm size, the distribution error decreased.

Some new sheet hydroforming processes have been introduced during the last few years to increase the application and to overcome some of the limitations in conventional deep drawing. In recent years, the applications of sheet hydroforming have become increased. Nowadays, this technology has been largely accepted by industries for the production of different components with specific characteristics. Despite the advantages of the sheet hydroforming techniques, they have their own disadvantages. In this paper, a new sheet hydroforming technique is presented that improves the applications of the current sheet hydroforming processes. The proposed technique is applied to two complex non-symmetrical industrial parts. It is shown that the new technique can produce the products very well. In addition, it is shown that the forming pressure and load are very low compared with those of other hydrofoming methods.

One of the most critical and complicated steps in mining design is a suitable mining method selection, based on geological, geotechnical, geographical and economical parameters. There are many factors involved in mining method selection, which influence the decision making process. In this paper, technique for order preference by similarity to ideal solution (TOPSIS), with 13 criteria, is used to develop a suitable mining method for the Golbini No. 8 deposit in Jajarm, Iran. Six alternatives mining methods, i.e. conventional cut and fill, mechanised cut and fill, shrinkage stoping, sublevel stoping, bench mining and stull stoping, are evaluated. The studies show that the suitable mining method for this deposit with regard to the present situation is conventional cut and fill method.

The primary idea behind deploying sensor networks is to utilize the distributed sensing capability provided by tiny, low powered, and low cost devices. Multiple sensing devices can be used cooperatively and collaboratively to capture events or monitor space more effectively than a single sensing device. The realm of applications envisioned for sensor networks is diverse including military, aerospace, industrial, commercial, environmental, and health monitoring. Typical examples include: traffic monitoring of vehicles, cross-border infiltration detection and assessment, military reconnaissance and surveillance, target tracking, habitat monitoring, and structure monitoring, to name a few. Most of the applications envisioned with sensor networks demand highly reliable, accurate, and fault-tolerant data acquisition process. In this paper, we focus on innovative approaches to deal with multivariable, multispace problem domains (data integrity, energy-efficiency, and fault-tolerant framework) in wireless sensor networks and present novel ideas that have practical implementation in developing power-aware software components for designing robust networks of sensing devices.

Polymer adhesion and its evaluation are important from academic and industrial points of view. Today cords are used to reinforce rubber in various products. Cord–rubber adhesion can be evaluated using static and dynamic methods. The static methods are commonly used for qualification of raw materials. These methods are not suitable for prediction of durability of the cord/rubber system in real conditions. The dynamic adhesion tests (e.g., fatigue method) involve some important parameters to simulate the real conditions of cord/rubber composite usage. So they produce reliable results in comparison with static adhesion results. Increase in temperature of cord/rubber system occurs during utilization of product. Adhesion usually decreases with increasing temperature. So the static adhesion test (e.g., H‐pull test) results that are measured in the ambient temperature (23 ± 2°C) cannot be considered as the composite's performance in the utilization condition. Although heat build up occurs in the test samples during the fatigue test procedure, but this is not enough to illustrate the decreasing effect of the increased temperature on the results. The authors produced a heat chamber to improve the dynamic test. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2488–2494, 2006

AbstractThis paper presents a fusion between discrete-event systems specification (DENS) and intelligent tools from soft computing. DENS provides a robust and generic environrnent for modeling and simulation applications employing single workstation, distributed, and real-time platforms. Soft computing is a consortium of tools for natural intelligence stemming from approximate reasoning (fuzzy logic), learning (neural network or stochastic learning automaton), optimization (genetic algorithms and genetic programming), etc. The outcome of this fusion is what is called “Intelligent DENS,” called IDEVS here. IDEVS is an element of a virtual laboratory, called V-Lab®, which is based on distributed multi-physics, multi-dynamic modeling techniques for multiple platforms. This paper will introduce IDEVS and V-Lab®and a theme example for amultiagent simulation of a number of robotic agents with a slew of dynamic models and multiple computer work stations.

Abstract:  Image enhancement is a field that is being used in various areas and disciplines. Advances in computers, microcontrollers and DSP boards have opened new horizons to digital image processing, and have opened many avenues to the design and implementation of new innovative techniques. This paper compares image enhancement via the modification of the probability density function of the gray levels with the new techniques that involves the use of knowledge-base (fuzzy expert) systems that are capable of mimicking the behavior of a human expert. A fuzzy expert system based software for image enhancement, called SmartPhotoLab has been introduced for the above purpose.

The behaviour of absorbance peaks for the phenyl ring (C -- C) and the alkyl chain containing CH 2 and CH 3 groups of an antiferroelectric liquid crystal ((R-2-methylheptyloxycarbonylphenyl 4-[(4-decyloxy-3fluoro)benzoyloxy]benzoate) with acronym 10 FBBBC8 is investigated in SmC*, SmC A * and SmC n * phases. To explain the molecular orientation, infrared absorbances are studied as a function of polariser rotation angle at various applied voltage across the homogeneously aligned cell. It is found that the maximum polar angle between the smectic layer normal and the direction to the maximal absorbance together with their profiles for both the phenyl and the alkyl chain groups rotate in the same direction with the same polarity of the field for each smectic phase. The curves of dichroic ratio and apparent tilt angle against the applied field for the phenyl and the alkyl chain for each phase indicate correlation between the two molecular groups.

Polarised infrared Spectroscopy is used to study the behaviour of SmC*, SmCA* and SmCγ* phases of an antiferroelectric liquid crystal material. The degree of molecular orientation is expressed in terms of the dichroic ratio obtained from the absorbance profiles for various applied voltages. The molecular tilt angle is found as the absorbance profiles of the various peaks rotate clockwise and anticlockwise with the sign of the applied field. The absorbance profiles of the stretching bands are quantitatively analysed and the biasing parameters of the transition dipole moments located in the molecular core for each phase are calculated and compared.

ABSTRACTDesalination plants are essential for life in several parts of the world. They are complex systems which, fortunately, can he broken down into more or less independent subsystems. To improve the operating performance of these plants, new control methods are being tested and evaluated. Here, we have proposed a fuzzy logic based controller to control the temperature in the brine heater, a very nonlinear system. This controller has been favorably compared to more conventional approaches. Moreover, a stability study has been realized.

Large-scale systems have been of great interest to many system and control engineers in recent years. Many practical systems fall into this category. To name a few, one may consider power, transportation, economic and energy systems whose models are characterized by high dimensions, decentralized information structures and hierarchical interconnections. Due to large dimensions of these systems, their model reduction has had significant importance. In this paper one of the main classes of techniques of model reduction - aggregation is overviewed and a comparison on their characteristics, computational requirement and use in the near-optimum control of the full model is given

AbstractStability is the most important attribute of any system. A prerequisite for all stability criteria of control systems is the existence of a mathematical model. In contrast, fuzzy control systems are often designed based on heuristic human knowledge and without a mathematical model, hence, it has been a difficult task to determine stability of fuzzy control systems under such restrictions. This paper uses the Takagi/Sugeno type of fuzzy rules whose consequences are analytical, and singletons are used as a basis for a number of sufficiency conditions for stability. The schemes considered here are time-domain, but a brief survey which proceeds the main results considers frequency domain as well. Both Lyapunov and interval matrix criteria are presented with some proofs and numerical examples.

ABSTRACTIn recent years, evolution based knowledge optimization has gained a great deal of popularity due to its inherent ability in efficient and parallel search of complex and multi-modal landscapes. Application of Genetic Algorithms (GA) to knowledge enhancement involves several aspects. First is how to code a string to represent all the necessary degrees of freedom for search in the fuzzy knowledge domain. The second aspect is how to incorporate existing expert knowledge into the GA optimising algorithm, and in general, how to take advantage of several experts' opinions in creation of an initial population. Conventional applications of GA Fuzzy suggest using a random initial population. However, it is intuitively clear that any search routine could converge faster if starting points are good solutions. In this article, a methodology is illustrated which incorporates expert knowledge in creating an initial population while allowing for randomness among members of the population for diversity. Furthermore, the methodology is applied to step response optimization of a flexible link feedback control system. Various aspects of real time implementation of such system are discussed.

A hierarchical scheme is proposed for the optimal control of large-scale non-linear systems with multiple state and control delays. A linear approximation of a nonlinear system is defined about the precomputed and stored nominal trajectories. The system is then decomposed into N subsystems such that the delay terms and interaction terms can be treated as an extra input, named perturbation, to the linear non-delay subsystems. The scheme generates a partly closed-loop and partly open-loop control. The convergence of the algorithm is established. An example with quadratic cost is simulated and solved by the proposed scheme using the constant nominal trajectories. The results of computer simulation of the two control problems presented in the examples are included.

An imbedding solution for the matrix Riccati equation is presented in this paper. One or all of the system's matrices is first imbedded by introducing a parameter ∈, 0 ≤ ∈ 1 and then taking a total derivative of the Riccati equation which provides a Lyapunov equation. Making use of the solution of the latter equation the Riccati matrix is obtained by an integration in the space of the parameter ∈. The method can handle both stable and unstable systems. Three numerical examples illustrate the method, its imbedding scheme, and comparison with the exact and another iterative technique. The results show that for the cases where an approximate solution to the Riccati equation is needed, the method is rather attractive in both accuracy and speed. Very cheap solutions can be found with reasonable accuracy. For a fifteenth-order system, a solution within 0·4% of the exact answer was obtained in 30 sec on the HP-2100 computer.

A new approach to the sub-optimal control of non-linear time-delay systems is presented in this paper. It consists of three stages. In the first stage the original time-delay system state equation is expanded about its nominal functions. The resulting linear time-varying system with delay is then reduced to a linear non-delay non-homogeneous system whose optimal control is the same. The third stage is the application of the maximum principle to the transformed system leading to the desired sub-optimal control. The method is applied to a non-linear system.

Realistic models of power systems involve high-order nonlinear differential equations. The application of optimal control theory in optimizing such systems involves a high-order nonlinear two-point boundary-value problem whose solution is very cumbersome. In this paper the imbedding method of solving free-end, fixed-time optimal control problem is applied to a sixth-order nonlinear power system. Both the open and closed-loop controllers are considered. The results of this application are compared with those by hybrid linearization method considered by other authors. The results indicate that the two methods follow quite closely.

Denmark, as an industrial society of the Western Europe has had an increasing demand for energy sources-notably oil in recent years. The 1973 OPEC embargo has caused great concerns in this country in replacing oil by other sources wherever possible. Nuclear power remains to be a controversial issue in this country. With new sources of energy such as solar and wind remaining economically unfeasible coal and nuclear are two most reasonable replacements for very expensive oil. In this paper an attempt is made to develop a dynamic input-output model for energy sectors in Denmark using Leontief's economic models which is valid up to and including the year 2000. The model is programmed on an interactivebasis using York/APL on an IBM 370 computer.

In this paper fuzzy control and decision making are used to simulate the control of traffic flow at an intersection. Fuzzy logic can be used as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller a computer simulation is constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. The fuzzy logic controller proved to be a better method of control than conventional control methods, especially in the case of highly uneven traffic flow between different directions

In this paper, the application of a real-time fuzzy controller is presented in order to improve the power system stability. The above is done with the means of the fuzzy membership functions whose values are computed depending on the measured generator frequency and voltage. The controller was tested in real time for different loads on the generator. For comparison a proportional crisp controller was also design and tested under the same circumstances.

This paper proposes two simple adaptive control schemes of robot manipulators. The first one is the state feedback control which consists of feedforward from the desired position trajectory, PD feedback from the actual trajectory, and an auxiliary input. The second one is the feedforward/feedback control which consists of a feedforward term from the desired position, velocity, and acceleration trajectory based on the inverse of robot dynamics. The feedforward, feedback, and auxiliary gains are adapted using simple equations derived from the decentralized adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the detail parameters of the manipulator or the payload. Simulation results are presented in support of the proposed schemes. The results demonstrate that both controllers perform well with bounded adaptive gains.

The purpose of this paper is to provide an overview of the research being done in neural network approaches to robotics, outline the strengths and weaknesses of current approaches, and predict future trends in this area.

This paper proposes a near-optimum control algorithm for a highly nonlinear robot manipulator model via a parameter sensitivity method. The method uses Pontrvagin's maximum principle and the Riccati formulation of the linear state regulator problem. The effectiveness of the proposed method is verified by simulation results for a two-link planar robot.

Mouse blastocysts take up glutamine by specific transport systems. Glutamine is an important precursor for macromolecular synthesis and a potential alternative fuel to glucose. This study compared glutamine uptake in blastocysts and isolated inner cell masses and characterized the major participating systems in the latter. Inner cell masses take up glutamine by facilitated transport systems. The identity of these was investigated using substrate competition and kinetic studies. Na+-dependent uptake of 13 μmol glutamine l−1was inhibited by 60% by 1 mmol tryptophan l−1, 25% by 1 mmol 2-amino-2-norbornanecarboxylic acid l−1and 50% by 1 mmol lysine l−1. Furthermore, 1 mmol 2-methyl(amino)isobutyric acid (MeAIB) l−1inhibited uptake by 29%. Kinetic analysis of MeAIB-resistant uptake revealed a predominant Na+-dependent facilitated uptake system with Kmand Vmaxvalues of 434 ± 72 μmol l−1and 237 ± 38 fmol per inner cell mass per 10 min, respectively. The inhibition of Na+-dependent uptake by tryptophan, lysine and the analogue 2-amino-2-norbornanecarboxylic acid suggests that most uptake of glutamine by inner cell masses occurs via the same system that predominates in whole blastocysts, Bo, +. The period of assay was so brief that significant participation of the inner cell mass in whole blastocyst uptake was precluded showing that system Bo,+is expressed by both the trophectoderm and inner cell mass components of the blastocyst. However, MeAIB inhibited uptake by inner cell masses but not by blastocysts. This MeAIB-sensitive uptake had a Kmvalue of 4.3 ± 1.7 mmol l−1and a Vmaxvalue of 451 ± 119 fmol per inner cell mass per 10 min. These characteristics suggest the first embryonic appearance of system A, which is a common Na+-dependent transporter in many somatic cells. Significant inhibition of Na+-independent glutamine uptake by tryptophan suggests participation of the ubiquitous system L, while inhibition by lysine suggests that bo,+may also be expressed in inner cell masses. Thus glutamine uptake by inner cell masses occurs via several transport systems expressed in whole blastocysts, including Na+-dependent system Bo, +, and probably Na+-independent systems L and bo,+, but is supplemented by the first expression of Na+-dependent system A in these cells from which the fetus later develops.

Abstract:  One of the biggest challenges of any control paradigm is being able to handle large complex systems. A system may be called large-scale or complex, here, if its dimension (order) is so high and its model (if available) is nonlinear, interconnected with uncertain information flow such that classical techniques of control theory cannot easily handle the system. From a control theoretical point of view, fuzzy logic has been intermixed with all the important aspects of systems theory - modeling, identification, analysis, stability, synthesis, filtering, and estimation. However, the application of fuzzy control to large-scale complex systems is not a trivial task by any means. For such systems the size of the rule base in a typical fuzzy control architecture will be nearly infinite. In this paper an attempt is made to break some new ground on the applications of fuzzy control to complex systems. A new rule base reduction approach is suggested to manage large inference engines. Notions of rule hierarchy and sensor data fusion are introduced and combined to achieve system’s goals. The technique has been implemented on an SGS Thomson W.A.R.P. chip for an inverted pendulum with wine-balancing application.

The sensitivity of performance index with respect to parameter variations in the state equation of optimally designed linear time-delay systems is discussed by introducing the concept of ϱ-sensitivity for such systems. Two cases are considered depending on the nature of these variations. In one case the delay portion of the state equation is ignored completely, while in the other, the delay itself is set equal to zero. For both types of variations conditions for ϱ-sensitivity are obtained. Two examples illustrate the application of the results. The effects of parameter variations on the stability of perturbed system are also considered.

In this paper, an approach based on neural networks and mathematical models for detecting and diagnosing instrument failures in the pressurized water reactor(PWR) of the H.B. Robinson nuclear plant is presented. Multilayer neural networks are used at the first level for identification of plant parameters and at the second level for distinguishing parameter variations and uncertainties from possible faults, and as a pattern recognizer in the third level for the detection of faulty instruments. The design approach was able to simultaneously classify single and multiple anomalies such as sensor and actuator failures under plant parameter uncertainties.

Design and development of water resources systems has been vitally imponant to all nations and in particular to those with dry meteorological conditions. Several developing countries have extensive plans to utilize their existing water resources. An important aspect of such systems is their operation. Once observing the rivers inflows during a part icular time period, it is often necessary to determine the right amount of water to be allocated for different system activities downstream. Modeling of water resources systems depend strongly on their characteristics and the available data. Since the water inflows are stochastic by nature, deterministic models do not accurately describe the physical phenomena. A number of optimization schemes such as linear and dynamic programmings in deterministic forms have been applied to such systems. However, few stochastic programming approaches has been used. Two common methods of the latter are chance constraints and linear decision rules. The former scheme along with a linear program are used in this study to find the optimal management rule for a 5-reservoir water resources system located in the Province of Khuzestan in southwest Iran.

This paper proposes two simple schemes for adaptive control of robot manipulator, to achieve trajectory tracking. The state feedback controller consists of feedforward from the reference position trajectory, feedback from the actual trajectory, and an auxiliary input. The feedforward/feedback controller is different from the state feedback controller in that it consists of feedforward from the reference position, velocity, and acceleration trajectory based on “inverse” dynamics of robot manipulator. The feedforward and feedback gains and the auxiliary input are adapted using adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a prioriknowledge of the parameter of the manipulator or the payload. Simulation results are presented in support of the proposed schemes.

Local state feedback is used to design a decentralized controller for large-scale linear time-invariant systems. The controller is based on model reduction of the system to the order of the subsystems. A computationally efficient algorithm is presented. A 3-subsystem numerical example is used to illustrate the proposed decentralized controller.

The adaptive decentralized control of large scale systems (LSS) using local state feedback is investigated. The results are then applied to a liquid metal cooled nuclear reactor.

Silicon carbide whiskers, a strong material that resembles cat's whiskers, are produced, primarily, for strengthening ceramics and metals. The current method for producing these whiskers is to use a semibatch process, extremely difficult to model mathematically. An alternative model utilizes the expertise of operators accumulated from years of experience in initializing and running the process. We designed two expert systems in which the process can be set up and run by nonexperts. One system uses crisp logic and the other fuzzy logic. In this article, we compare the two systems.

The Lyapunoy stability of a form of singularly perturbed bilinear system is investigated. A theorem is proposed to show how to calculate the stabilizing controller for the whole system from a knowledge of the stability of the reduced-order model. A numerical example is given.

This paper describes the latest trends and theoretical developments involved with the modeling and control of Large Flexible Space Structures (LFSS). The paper addresses first the basic problems, characteristics and difficulties inherent in modeling and control of LFSS. Major source of error is the stiffness and damping operators of the dynamic model. Extensions of Linear Quadratic Gaussian (LQGI theory as applied to LFSS are presented, including frequency-shaped cost functionals and perturbation methods. The minimum data/maximum entropy approach which uses a stochastic design model to overcome difficulties found in LQGbased methods is described. Latest trends in system theory including Hankel-Norm model reduction, Balanced Realization, and Singular-Value Analysis are used to determine reducedorder controllers and models. Ad hoc methods such as component cost analysis and modal cost analysis are discussed in context with the closed-loop reduction problem of controller order versus performance. Another method described earlier as the minimum data/maximum entropy approach also addresses controller order versus performance. The paper also attempts to identify those areas of control science and large scale systems that appear to have an important role in understanding and solving LFSS modeling aud control.

A hierarchical scheme for the optimal control of large-scale non linear time-delay systems is proposed. A linear approximation of original system is defined about a nominal trajectory. The system is decomposed into N subsystems such that the delay terms as well as interaction terms can be treated as extra inputs to linear non-delay subsystems. A numerical example, constituting a 4-reservoir water resources system illustrates this approach.

Computer-aided design (CAD) has found a hew home in the control systems theory. Many control system's related problems such as analysis, design, estimation, filtering and simulation are now handled through CAD packages and languages. Through these software tools, even a novice computer programmer can take advantage of powerful computational and numerical algorithms for control systems problems. In this paper a CAD language for control and Kalman filtering will be presented. The language, called CONTROL. labis written in FORTRAN/77 and can run under UNIX or VMS on a DEC 11/780 VAX computer system.