A new method to test system diagnosability

A new necessary and sufficient condition for t-diagnosability of a system is proposed. It is shown that the new scheme is computationally more efficient than the existing one for checking the diagnosability of a system.     

Small torsional vibration superposed on finitely deformed state of a circular cylindrical rod of transversely isotropic elastic material

Starting with a class of small deformations superposed on a finitely deformed state of a transversely isotropic elastic solid, we study a problem of small torsional vibration superposed on homogeneous finitely deformed state of a circular cylindrical rod made of transversely isotropic elastic material. It has been found that free vibration is possible and, due to anisotropy, the speed of propagation of waves of torsion along the cylinder is increased or decreased according as the initial stressed state is under tension or compression.     

Implementation and test results of a wide-area measurement-based controller for damping interarea oscillations considering signal-transmission delay

The paper describes the implementation of a centralised control-design scheme in a real-time laboratory-based dynamic simulator. A centralised multivariable-control algorithm is designed employing remote feedback signals considering delay in signal transmission. The transmitted signals can be used for multiple-swing-mode damping using a single controller. Such an algorithm is numerically intensive owing to the high controller size and the predictor that takes care of the delay in signal transmission. The performance of the proposed controller is demonstrated by practical implementation using a rapid-prototyping controller mounted on a PC-ATX. Results of the experimental tests are shown for a detailed model of the power system implemented using Linux PC-based multiprocessor technology.     

A multiple-criteria decision problem for optimal management of farm resources under uncertainty - a case study

An attempt is made to minimize the total operational cost and specific energy for rice cultivation, when the constraints relating to the availability of power sources and crop yield are supposed to be stochastic in nature. The Sequential Linear Goal Programming algorithm has been used to solve the resulting multiple objective optimization problem.     

Photoconductivity in CuInSe2 films

CulnSe₂ films with different Cu/In ratios (0.4–1.2) were deposited on glass substrates by three source evaporation techniques. The films were polycrystalline in nature with partially depleted grains. Photoconductivity in the films was measured in the temperature range 170–370 K. The data at low temperatures (T < 300 K) were analyzed by using the grain boundary trapping model with monovalent trapping states. The intercrystalline barrier height in dark varied within 0.13 and 0.08 eV with the variation of Cu/In within 0.4 and 1.18. The variation of the barrier height with the intensity of the incident photons in the range 10–75 mW / cm² was analyzed to understand the carrier detrapping effect in the films under various illumination levels.     

Philosophical Dimensions of Information and Ethics in the Internet of Things (IoT) Technology

This article discusses the various dimensions of philosophy of information for the Internet of Things (IoT) technology. The aspects of attention, subjectivity, objectivity, happiness, key ethical concerns, and the need for algorithmic transparency and accountability in autonomous IoT applications that are necessary to build an IoT belief system have been highlighted here. The interplay of smart devices, smart services, and humans has been depicted to highlight trust permeability in human and IoT interfaces.     

Variance-penalized Markov decision processes: dynamic programming and reinforcement learning techniques

In control systems theory, the Markov decision process (MDP) is a widely used optimization model involving selection of the optimal action in each state visited by a discrete-event system driven by Markov chains. The classical MDP model is suitable for an agent/decision-maker interested in maximizing expected revenues, but does not account for minimizing variability in the revenues. An MDP model in which the agent can maximize the revenues while simultaneously controlling the variance in the revenues is proposed. This work is rooted in machine learning/neural network concepts, where updating is based on system feedback and step sizes. First, a Bellman equation for the problem is proposed. Thereafter, convergent dynamic programming and reinforcement learning techniques for solving the MDP are provided along with encouraging numerical results on a small MDP and a preventive maintenance problem.     

Cooperative adaptive control for synchronization of second‐order systems with unknown nonlinearities

This paper studies synchronization to a desired trajectory for multi‐agent systems with second‐order integrator dynamics and unknown nonlinearities and disturbances. The agents can have different dynamics and the treatment is for directed graphs with fixed communication topologies. The command generator or leader node dynamics is also nonlinear and unknown. Cooperative tracking adaptive controllers are designed based on each node maintaining a neural network parametric approximator and suitably tuning it to guarantee stability and performance. A Lyapunov‐based proof shows the ultimate boundedness of the tracking error. A simulation example with nodes having second‐order Lagrangian dynamics verifies the performance of the cooperative tracking adaptive controller. Copyright © 2010 John Wiley & Sons, Ltd.     

Optimization of conditions for hydrogen production from complex dairy wastewater by anaerobic sludge using desirability function approach

Present study deals with the multiple-response optimization for biohydrogen production using anaerobic sludge and outstanding approach to overcome the drawbacks of conventional response surface methodology (RSM). Dairy wastewater was used as source in batch fermentation was followed for this study. Response surface methodology (RSM), based on a three level, four variable Box–Behnken design, was employed to obtain the best possible combination of substrate concentration, pH, COD/N ratio and COD/P ratio for maximum H₂ yield (HY) and specific hydrogen production rate (SHPR). Experimental data were evaluated by applying RSM integrating a desirability function approach. The optimum H₂ yield and SHPR conditions were: substrate concentration 15.3 g COD/L, pH 5.5, COD/N ratio 100.5 and COD/P ratio 120 with maximum overall desirability D of 0.94. The confirmation experiment under these optimal condition showed a HY and SHPR of 13.54 mmol H₂/g COD and 29.91 mmol H₂/g-VSS.d, respectively. This was only 0.22% and 0.20%, respectively, different from the predicted values, suggesting that the desirability function approach with RSM was a useful technique to get the maximum H₂ yield and SHPR simultaneously.