Microprocessor-controlled automatic focusing of a lens

Maximum intensity contrast has been used as a measure of lens defocus. A photodiode array under the control of 8085 microprocessor is used to measure the maximum intensity contrast and to position the lens for best focus. The lens is moved by a stepper motor under processor control at a speed of 350 to 500 steps/s. At this speed, focusing time was found to be between 5 and 8 s. Under coherent illuminating conditions, an accuracy of ± 50 μm has been achieved.

Self-tuning minimum-variance control of nonlinear systems of the Hammerstein model

Self-tuning is applied to the control of nonlinear systems represented by the Hammerstein model wherein the nonlinearity is any odd-order polynomial. But control costing is not feasible in general. Initial relay control is employed to contain the deviations.

Optimal control of arrivals to queues with delayed queue length information

We consider discrete-time versions of two classical problems in the optimal control of admission to a queueing system: i) optimal routing of arrivals to two parallel queues and ii) optimal acceptance/rejection of arrivals to a single queue. We extend the formulation of these problems to permit a k step delay in the observation of the queue lengths by the controller. For geometric inter-arrival times and geometric service times the problems are formulated as controlled Markov chains with expected total discounted cost as the minimization objective. For problem i) we show that when k = 1, the optimal policy is to allocate an arrival to the queue with the smaller expected queue length (JSEQ: Join the Shortest Expected Queue). We also show that for this problem, for k greater than or equal to 2, JSEQ is not optimal. For problem ii) we show that when k = 1, the optimal policy is a threshold policy. There are, however, two thresholds m(0) greater than or equal to m(1) > 0, such that mo is used when the previous action was to reject, and mi is used when the previous action was to accept.

Automatic Compilation of MATLAB Programs for Synergistic Execution on Heterogeneous Processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Partially integrated guidance and control of an air-dropped guided munition with explicit trajectory fixing

An innovative partially integrated guidance and control (PIGC) technique is developed for trajectory fixing by considering six degree-of-freedom (Six-DOF) nonlinear engagement dynamics for successful interception of ground targets by guided munitions. This trajectory fixing algorithm gives closed form solution, where two different trajectories are designed in x - h and x - y planes separately using simple quadratic equations. In order to follow designed trajectories commanded pitch and yaw rates are generated in outer loop using dynamic inversion technique. In inner loop these body rates are tracked using faster dynamic inversion loop by generating the necessary control surface deflections. Simulation studies with actuator dynamics have been carried out to account for three dimensional (3D) engagement geometry to demonstrate the usefulness of PIGC technique.

Electronic Control of Facial Selection in Additions to Sterically Unbiased Ketones and Olefins

By definition, the two faces of a pi bond are equivalent.1 However, they are rendered nonequivalent in most molecules because of the absence of a plane of symmetry encompassing the double bond and the adjacent substituents. As a result, additions to trigonal centers from the two faces need not be equally facile. Exploiting this stereodifferentiation in a controlled manner represents one of the core problems in organic synthesis. Evidently, the factors which determine such diastereoselection need to be delineated in as much detail as possible.

Ergodic control of partially observed Markov chains

The ergodic or long-run average cost control problem for a partially observed finite-state Markov chain is studied via the associated fully observed separated control problem for the nonlinear filter. Dynamic programming equations for the latter are derived, leading to existence and characterization of optimal stationary policies.

Synthesis of novel poly[(2,5-dimethoxy-p-phenylene)vinylene] precursors having two eliminatable groups: An approach for the control of conjugation length

Poly[(2,5-dimethoxy-p-phenylene)vinylene] (DMPPV) of varying conjugation length was synthesized by selective elimination of organic soluble precursor polymers that contained two eliminatable groups, namely, methoxy and acetate groups. These precursor copolymers were in turn synthesized by competitive nucleophilic substitution of the sulfonium polyelectrolyte precursor (generated by the standard Wessling route) using methanol and sodium acetate in acetic acid. The composition of the precursor copolymer, in terms of the relative amounts of methoxy and acetate groups, was controlled by varying the composition of the reaction mixture during nucleophilic substitution. Thermal elimination of these precursor copolymers at 250 degrees C, yielded partially conjugated polymers, whose color varied from light yellow to deep red. FT-IR studies confirmed that, while essentially all the acetate groups were eliminated, the methoxy groups were intact and caused the interruption in conjugation. Preliminary photoluminescence studies of the partially eliminated DMPPV samples showed a gradual shift in the emission maximum from 498 to 598 nm with increasing conjugation lengths, suggesting that the color of LED devices fabricated from such polymers can, in principle, be fine-tuned.

Supramolecular control of the magnetic anisotropy in two-dimensional high-spin Fe arrays at a metal interface

Magnetic atoms at surfaces are a rich model system for solid-state magnetic bits exhibiting either classical(1,2) or quantum(3,4) behaviour. Individual atoms, however, are difficult to arrange in regular patterns(1-5). Moreover, their magnetic properties are dominated by interaction with the substrate, which, as in the case of Kondo systems, often leads to a decrease or quench of their local magnetic moment(6,7). Here, we show that the supramolecular assembly of Fe and 1,4-benzenedicarboxylic acid molecules on a Cu surface results in ordered arrays of high-spin mononuclear Fe centres on a 1.5nm square grid. Lateral coordination with the molecular ligands yields unsaturated yet stable coordination bonds, which enable chemical modification of the electronic and magnetic properties of the Fe atoms independently from the substrate. The easy magnetization direction of the Fe centres can be switched by oxygen adsorption, thus opening a way to control the magnetic anisotropy in supramolecular layers akin to that used in metallic thin films.

Nucleophilic additions to 4-substituted snoutanones: getting a measure of long range electrostatic and orbital control of pi-face selectivity

Pentacyclic ketones 10a-e (snoutan-9-ones) undergo nucleophilic additions with the same facial preference as the corresponding norsnoutanones 9a-e, but with markedly reduced selectivity, revealing the involvement of electrostatic effects in the former and implying the importance of hyperconjugative orbital interactions in determining pi-face selectivity in the latter systems.

FPGA based digital platform for the control of AC drives

This paper presents the new trend of FPGA (Field programmable Gate Array) based digital platform for the control of power electronic systems. There is a rising interest in using digital controllers in power electronic applications as they provide many advantages over their analog counterparts. A board comprising of Cyclone device EP1C12Q240C8 of Altera is used for developing this platform. The details of this board are presented. This developed platform can be used for the controller applications such as UPS, Induction Motor drives and front end converters. A real time simulation of a system can also be done. An open-loop induction motor drive has been implemented using this board and experimental results are presented.

Enhancing field emission from a carbon nanotube array by lateral control of electrodynamic force field

Fluctuation of field emission current from carbon nanotubes (CNTs) poses certain difficulties for their use in nanobiomedical X-ray devices and imaging probes. This problem arises due to deformation of the CNTs due to electrodynamic force field and electron-phonon interaction. It is of great importance to have precise control of emitted electron beams very near the CNT tips. In this paper, a new array configuration with stacked array of CNTs is analysed and it is shown that the current density distribution is greatly localised at the middle of the array, that the scatter due to electrodynamic force field is minimised and that the temperature transients are much smaller compared to those in an array with random height distribution.

Some aspects of multilevel load-frequency control of a power system

The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.