A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Simultaneous material selection and geometry design of statically determinate trusses using continuous optimization

In this work, we explore simultaneous geometry design and material selection for statically determinate trusses by posing it as a continuous optimization problem. The underlying principles of our approach are structural optimization and Ashby’s procedure for material selection from a database. For simplicity and ease of initial implementation, only static loads are considered in this work with the intent of maximum stiffness, minimum weight/cost, and safety against failure. Safety of tensile and compression members in the truss is treated differently to prevent yield and buckling failures, respectively. Geometry variables such as lengths and orientations of members are taken to be the design variables in an assumed layout. Areas of cross-section of the members are determined to satisfy the failure constraints in each member. Along the lines of Ashby’s material indices, a new design index is derived for trusses. The design index helps in choosing the most suitable material for any geometry of the truss. Using the design index, both the design space and the material database are searched simultaneously using gradient-based optimization algorithms. The important feature of our approach is that the formulated optimization problem is continuous, although the material selection from a database is an inherently discrete problem. A few illustrative examples are included. It is observed that the method is capable of determining the optimal topology in addition to optimal geometry when the assumed layout contains more links than are necessary for optimality.

A water model study of the flow asymmetry inside a continuous slab casting mold

The work studies the extent of asymmetric flow in water models of continuous casting molds of two different configurations. In the molds where fluid is discharged through multiple holes at the bottom, the flow pattern in the lower portion depends on the size of the lower two recirculating domains. If they reach the mold bottom, the flow pattern in the lower portion is symmetrical about the central plane; otherwise, it is asymmetrical. On the other hand, in the molds where the fluid is discharged through the entire mold cross section, the flow pattern is always asymmetrical if the aspect ratio is 1:6.25 or more. The fluid jet swirls while emerging through the nozzle. The interaction of the swirling Jets with the wide sidewalls of the mold gives rise to asymmetrical flow inside the mold. In the molds with lower aspect ratios, where the jets do not touch the wide side walls, the flow pattern is symmetrical about the central plane.

Response And Stability Of A Stochastic Beam-Column Using Stochastic Fem

A beam-column resting on continuous Winkler foundation and discrete elastic supports is considered. The beam-column is of variable cross-section and the variation of sectional properties along the axis of the beam-column is deterministic. Young's modulus, mass per unit length and distributed axial loadings of the beam-column have a stochastic distribution. The foundation stiffness coefficient of the Winkler model, the stiffnesses of discrete elastic supports, stiffnesses of end springs and the end thrust, are all considered as random parameters. The material property fluctuations and distributed axial loadings are considered to constitute independent, one-dimension uni-variate homogeneous real stochastic fields in space. The foundation stiffness coefficient, stiffnesses of the discrete elastic supports, stiffnesses of end springs and the end thrust are considered to constitute independent random variables. Static response, free vibration and stability behaviour of the beam-column are studied. Hamilton's principle is used to formulate the problem using stochastic FEM. Sensitivity vectors of the response and stability parameters are evaluated. Using these statistics of free vibration frequencies, mode shapes, buckling parameters, etc., are evaluated. A numerical example is given.

Quantum entanglement in a noncommutative system

We explore the effect of two-dimensional position-space noncommutativity on the bipartite entanglement of continuous-variable systems. We first extend the standard symplectic framework for studying entanglement of Gaussian states of commutative systems to the case of noncommutative systems residing in two dimensions. Using the positive partial transpose criterion for separability of bipartite states, we derive a condition on the separability of a noncommutative system that is dependent on the noncommutative parameter theta. We then consider the specific example of a bipartite Gaussian state and show the quantitative reduction in entanglement originating from noncommutative dynamics. We show that such a reduction in entanglement for a noncommutative system arising from the modification of the variances of the phase-space variables (uncertainty relations) is clearly manifested between two particles that are separated by small distances.

Equatorial modes observed in atmospheric variables

Wavenumber-frequency spectral analysis of different atmospheric variables has been carried Out using 25 years of data. The area considered is the tropical belt 25 degrees S-25 degrees N. A combined FFT wavelet analysis method has been used for this purpose. Variables considered are outgoing long wave radiation (OLR), 850 hPa divergence, zonal and meridional winds at 850, 500 and 200 hPa levels, sea level pressure and 850 hPa geopotential height. It is shown that the spectra of different variables have some common properties, but each variable also has few features diffe:rent from the rest. While Kelvin mode is prominent in OLR, and zonal winds, it is not clearly observed in pressure and geopotential height fields; the latter two have a dominant wavenumber zero mode not seen in other variables except in meridional wind at 200 hPa and 850 hPa divergences. Different dominant modes in the tropics show significant variations on sub-seasonal time scales.

Synthesis of plane linkages to generate functions of two variables using point position reductionâII. Sliding inputs and outputs

The paper presents simple graphical procedures for the position synthesis of plane linkage mechanisms with sliding inputs and output to generate functions of two independent variables. The procedures are based on point position reduction and permit synthesis of the linkage to satisfy up to five arbitrarily selected precision positions.

Calculating the bound spectrum by path summation in action-angle variables

The density of states n(E) is calculated for a bound system whose classical motion is integrable, starting from an expression in terms of the trace of the time-dependent Green function. The novel feature is the use of action-angle variables. This has the advantages that the trace operation reduces to a trivial multiplication and the dependence of n(E) on all classical closed orbits with different topologies appears naturally. The method is contrasted with another, not applicable to integrable systems except in special cases, in which quantization arises from a single closed orbit which is assumed isolated and the trace taken by the method of stationary phase.

Studies on the reduction of hematite by carbon

Single pellet experiments have been carried out in a nitrogen atmosphere to study the reduction of hematite by graphite in the temperature range 925 to 1060°C. The effect of variables such as c/Fe2O3 molar ratio, pellet size, and so forth, has been investigated. Gas analysis data show a continuous decrease in CO2/CO ratio during reduction, the values being far away from Fe/FeO equilibrium for wustite reduction by CO. The activation energies associated with different degrees of reduction appear to be widely different suggesting a possible changeover in reaction mechanism during the progress of reduction. X-ray diffraction studies confirm the stepwise nature of hematite reduction.

A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.

Continuous Distribution Kinetics for Photopolymerization of Alkyl Methacrylates

The photopolymerization of methyl,ethyl,butyl, and hexyl methacrylates in solution was studied. The effect of initial initiator and monomer concentrations on the time evolution of polymer concentration (M) over bar (n) and PDI was examined. The reversible chain addition and beta-scission, and primary radical termination steps were included in the mechanism along with the classical steps. The rate equations were derived using continuous distribution kinetics and solved numerically to fit the experimental data. The regressed rate coefficients compared well with the literature data. The model predicted the instantaneous increase in (M) over bar (n) and PDI to steady state values. The rate coefficients exhibited a linear increase with the size of alkyl chain of the alkyl methacrylates.

Process variables in biomimetic synthesis of silver nanoparticles by aqueous extract of Azadirachta indica (Neem) leaves

Owing to widespread applications, synthesis and characterization of silver nanoparticles is recently attracting considerable attention. Increasing environmental concerns over chemical synthesis routes have resulted in attempts to develop biomimetic approaches. One of them is synthesis using plant parts, which eliminates the elaborate process of maintaining the microbial culture and often found to be kinetically favourable than other bioprocesses. The present study deals with investigating the effect of process variables like reductant concentrations, reaction pH, mixing ratio of the reactants and interaction time on the morphology and size of silver nanoparticles synthesized using aqueous extract of Azadirachta indica (Neem) leaves. The formation of crystalline silver nanoparticles was confirmed using X-ray diffraction analysis. By means of UV spectroscopy, Scanning and Transmission Electron Microscopy techniques, it was observed that the morphology and size of the nanoparticles were strongly dependent on the process parameters. Within 4 h interaction period, nanoparticles below 20-nm-size with nearly spherical shape were produced. On increasing interaction time (ageing) to 66 days, both aggregation and shape anisotropy (ellipsoidal, polyhedral and capsular) of the particles increased. In alkaline pH range, the stability of cluster distribution increased with a declined tendency for aggregation of the particles. It can be inferred from the study that fine tuning the bioprocess parameters will enhance possibilities of desired nano-product tailor made for particular applications.

Continuous-Flow Surface Aeration Systems

An aeration process in ail activated sludge plant is a continuous-flow system. In this system, there is a steady input flow (flow from the primary clarifier or settling tank with some part from the secondary clarifier or secondary settling tank) and output flow connection to the secondary clarifier or settling tank. The experimental and numerical results obtained through batch systems can not be relied on and applied for the designing of a continuous aeration tank. In order to scale up laboratory results for field application, it is imperative to know the geometric parameters of a continuous system. Geometric parameters have a greater influence on the mass transfer process of surface aeration systems. The present work establishes the optimal geometric configuration of a continuous-flow surface aeration system. It is found that the maintenance of these optimal geometric parameters systems result in maximum aeration efficiency. By maintaining the obtained optimal geometric parameters, further experiments are conducted in continuous-flow surface aerators with three different sizes in order to develop design curves correlating the oxygen transfer coefficient and power number with the rotor speed. The design methodology to implement the presently developed optimal geometric parameters and correlation equations for field application is discussed.

Rendering stiffer walls: a hybrid haptic system using continuous and discrete time feedback

Instability in conventional haptic rendering destroys the perception of rigid objects in virtual environments. Inherent limitations in the conventional haptic loop restrict the maximum stiffness that can be rendered. In this paper we present a method to render virtual walls that are much stiffer than those achieved by conventional techniques. By removing the conventional digital haptic loop and replacing it with a part-continuous and part-discrete time hybrid haptic loop, we were able to render stiffer walls. The control loop is implemented as a combinational logic circuit on an field-programmable gate array. We compared the performance of the conventional haptic loop and our hybrid haptic loop on the same haptic device, and present mathematical analysis to show the limit of stability of our device. Our hybrid method removes the computer-intensive haptic loop from the CPU-this can free a significant amount of resources that can be used for other purposes such as graphical rendering and physics modeling. It is our hope that, in the future, similar designs will lead to a haptics processing unit (HPU).