Advanced disturbance observer design for mechanical positioning systems

Disturbance-observer (DOB)-based controller design is one of the most popular methods in the field of motion control. In this paper, the generalized disturbance compensation framework, named the robust internal-loop compensator (RIC) is introduced and an advanced design method of a DOB is proposed based on the RIC. The mixed sensitivity optimization problem, which is the main issue of DOB design, is also solved through the parametrization of the DOB in the RIC framework. Differently from conventional methods, the Q-filter is separated from the mixed sensitivity optimization problem and a systematic design law for the DOB is proposed. This guarantees the robustness and optimality of the DOB and enables the design for unstable plants.     

Wideband microstrip array antenna with sidelobe cancellationchannels

An antenna array for wideband operation (up to 70%) is presented. The structure has low windloading area and consists of parallel printed circuit boards (PCB) with microstrip dipoles, feed network and metal fences placed between the PCBs. The low profile, low weight antenna array forms the main beam and three difference patterns for sidelobe cancellation. Experimental results are compared with calculations for both microstrip dipole and array     

High-performance automatic target recognition through data-specificVLSI

Under the Mojave configurable computing project, we have developed a system for achieving high performance on an automatic target recognition (ATR) application through the use of configurable computing technology. The ATR system studied here involves real-time image acquisition from a synthetic aperture radar (SAR). SAR images exhibit statistical properties which can be used to improve system performance. In this paper, the Mojave configurable computing system uses field programmable gate arrays (FPGA's) to implement highly specialized circuits while retaining the flexibility of programmable components. A controller sequences through a set of specialized circuits in response to real-time events. Computer-aided design (CAD) tools have been developed to support the automatic generation of these specialized circuits. The resulting configurable computing system achieves a significant performance advantage over the existing solution, which is based on application specific integrated circuit (ASIC) technology     

Normal-incidence InAs self-assembled quantum-dot infrared photodetectors with a high detectivity

An InAs/AlGaAs quantum-dot infrared photodetector based on bound-to-bound intraband transitions in undoped InAs quantum dots is reported. AlGaAs blocking layers were employed to achieve low dark current. The photoresponse peaked at 6.2 /spl mu/m. At 77 K and -0.7 V bias, the responsivity was 14 mA/W and the detectivity, D*, was 10/sup 10/ cm/spl middot/Hz/sup 1/2//W.     

Recording of volume hologram using a beam pattern from taperedoptical fiber

A photorefractive volume hologram was recorded and probed using light diffracted from a tapered optical fiber as a reference beam. A single-mode fiber (SMF) was chemically etched and tapered to give a complicated beam pattern, and it is shown that the tapered optical fiber can be utilized to increase the storage density of the volume hologram. Spatial selectivity of the volume hologram with this method was increased by two times compared to the normal SMF referencing, which is due to the fact that the complicated beam pattern has little correlation with its shifted version     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.     

A new hybrid active power filter (APF) topology

In this paper, a new hybrid active power filter topology is presented. A higher-voltage, low-switching frequency insulated gate bipolar transistor (IGBT) inverter and a lower-voltage high-switching frequency metal oxide semiconductor field effect transistor (MOSFET) inverter are used in combination to achieve harmonic current compensation. The function of the IGBT inverter is to support utility fundamental voltage and to compensate for the fundamental reactive power. The MOSFET inverter fulfills the function of harmonic current compensation. To further reduce cost and to simplify control, the IGBT and MOSFET inverters share the same DC-link via a split capacitor bank. With this approach harmonics can be cancelled over a wide frequency range. Compared to the conventional APF topology, the proposed approach employs lower dc-link voltage and generates less noise. Simulation and experimental results show that the proposed active power filter topology is capable of compensating for the load harmonics     

On a stochastic nonlinear equation in one-dimensional viscoelasticity

In this paper we discuss an initial-boundary value problem for a stochastic nonlinear equation arising in one-dimensional viscoelasticity. We propose to use a new direct method to obtain a solution. This method is expected to be applicable to a broad class of nonlinear stochastic partial differential equations.

     

Some formulae for the q-Bernoulli and Euler polynomials of higher order

The purpose of this paper is to give a proof of Kummer type congruence for the q-Bernoulli numbers of higher order, which is an answer to a part of the problem in a previous publication (see Indian J. Pure Appl. Math. 32 (2001) 1565-1570).