A highly efficient novel azimuthal heliotrope

A new type of a single-axis azimuthal tracker is presented. The novel feature of this tracker is the ability to move the collector’s plane in two directions through a special support structure. This structure consists of a sliding mechanism on the central axis and a curved window on the cylindrical surface coaxial to the central axis. Consequently, the proposed novel heliotrope behaves similarly to a two-axis tracker. Two different windows designed on the cylindrical surface may be used to provide very high efficiencies throughout a year. Several performance measurements have been conducted on this novel tracker, a polar tracker and the reference two-axis tracker. Pyranometers, appropriately calibrated, were installed on all three systems to record the global incoming irradiance on the collector’s plane. It is shown that the new tracker system can be very efficient since its plane intercepts, at least, 98% of the insolation with respect to a two-axis tracker. The proposed system can be utilized in solar-related applications (photovoltaic or thermal).     

An adaptive tracking problem for a family of retarded time-delay plants

Most of the existing switching control techniques are developed specifically for finite-dimensional linear time-invariant (LTI) systems. In many practical applications, however, it is essential to take time delay into consideration in the modelling as the control system can be highly sensitive to delay. In this paper, a multi-model switching control algorithm is proposed for retarded time-delay systems. It is assumed that the plant is represented by a family of known multi-input multi-output, observable, LTI models with multiple delays in the states, and that corresponding to each model in the known family, there exists a high-performance finite-dimensional LTI controller. In addition, it is supposed that a bound on the magnitude of the external inputs and disturbances is available. It is then shown that the proposed switching controller can stabilize the uncertain system, and that under some mild conditions, output tracking can be achieved in the given problem setting. Copyright © 2007 John Wiley & Sons, Ltd.     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

Feedback tuning of bifurcations

The present paper studies a feedback regulation problem that arises in at least two different biological applications. The feedback regulation problem under consideration may be interpreted as an adaptive control problem for tuning bifurcation parameters, and it has not been studied in the control literature. The goal of the paper is to formulate this problem and to present some preliminary results.     

A family of lower- and higher-order transversal linearization techniques in non-linear stochastic engineering dynamics

Sample pathwise numerical integration of noise-driven engineering dynamical systems cannot generally be performed beyond a limited level of accuracy, especially when the noise processes are modelled using (filtered) white noises. Recently, a locally transversal linearization (LTL) strategy has been proposed by the author (Proc Roy Soc London A 2001; 457 :539–566) for direct integration of deterministic and stochastic non-linear dynamical systems. The present effort is focussed on a host of extensions along with detailed theoretical error analyses of the linearization approach, especially as applied to problems in non-linear stochastic engineering dynamics. Thus, to begin with, estimates of local and global error orders in the basic LTL scheme are obtained separately for the displacement and velocity vectors when the system is driven either by a set of additive noises or by an arbitrary combination of (independently evolving) additive and multiplicative noises. Following this, a new family of higher-order LTL schemes is proposed in order to improve upon the basic LTL method and the associated error orders are established. A stepwise implementation of the lower- and higher-order versions of the LTL method, along with certain computational aspects, is also outlined. The proposed schemes are numerically illustrated, to a limited extent, for a single degree-of-freedom (SDOF) and a two degree-of-freedom (TDOF) non-linear engineering systems under additive and/or multiplicative white noise excitations. Copyright © 2004 John Wiley & Sons, Ltd.     

A prolog based expert system for the allocation of quality assurance program resources

The worldwide proliferation of fraudulent materials has brought about the need for a new approach to the control of purchased material quality. Nuclear power, defense, aerospace and many other industries are affected by the supply of poor quality clones that presume to be original replacement parts. Safety considerations abound as these highly defective materials are used in systems that are critical to the preservation of human lives. Commonly utilized quality assurance programs have not effectively stopped the influx of fraudulent materials. These programs fail to concentrate inspection efforts on materials and inspection attributes that would effectively prevent the acceptance of fraudulent materials. herein a solution is presented to this problem in the form of an expert system application. Information commonly available in industry is formulated into a knowledge based system wherein advisories are given to the user regarding key purchased material receipt inspection strategies.     

Development of alternative technical systems

This paper considers the integration of alternative technical systems (TS) belonging to a wider class of competing TS, into a supersystem. The paper introduces the notion of alternative TS, shows the peculiarities of their incorporation into a supersystem, reveals the mechanisms used for such incorporation, and shows areas of application for the suggested method.     

Frequency domain identification of Wiener models

This paper proposes a frequency domain algorithm for Wiener model identifications based on exploring the fundamental frequency and harmonics generated by the unknown nonlinearity. The convergence of the algorithm is established in the presence of white noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be nonparametric.     

Markov analysis of qualitative dynamics1

Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.