A feedback-feed-forward steering control strategy for improving lateral dynamics stability of an A-double vehicle at high speeds

A control strategy based on H∞-type static output feedback combined with dynamic feed-forward is proposed to improve the high-speed lateral performance of an A-double combination vehicle (tractor–semitrailer–dolly–semitrailer) using active steering of the front axle of the dolly. Both feedback and feed-forward syntheses are performed via Linear Matrix Inequality (LMI) optimisation. From a practical point of view, the proposed controller is simple and easy to implement, despite its theoretical complexity. In fact, the measurement of the driver steering angle and only one articulation angle are required for the feed-forward and the feedback controllers, respectively. The results are verified using a high-fidelity vehicle model and confirm a significant reduction in yaw rate and lateral acceleration rearward amplification and also high-speed transient off-tracking, and subsequently improving the lateral stability and performance of the A-double combination vehicle during sudden lane change manoeuvres

Cellular automata simulation of topological effects on the dynamics of feed-forward motifs

<p>Abstract</p> <p>Background</p> <p>Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on the relationship between the specific architecture and the overall rate of the processes of the feed-forward family of motifs, including double and triple feed-forward loops. The search for the most efficient network architecture could be of particular interest for regulatory or signaling pathways in biology, as well as in computational and communication systems.</p> <p>Results</p> <p>Feed-forward motif dynamics were studied using cellular automata and compared with differential equation modeling. The number of cellular automata iterations needed for a 100% conversion of a substrate into a target product was used as an inverse measure of the transformation rate. Several basic topological patterns were identified that order the specific feed-forward constructions according to the rate of dynamics they enable. At the same number of network nodes and constant other parameters, the bi-parallel and tri-parallel motifs provide higher network efficacy than single feed-forward motifs. Additionally, a topological property of isodynamicity was identified for feed-forward motifs where different network architectures resulted in the same overall rate of the target production.</p> <p>Conclusion</p> <p>It was shown for classes of structural motifs with feed-forward architecture that network topology affects the overall rate of a process in a quantitatively predictable manner. These fundamental results can be used as a basis for simulating larger networks as combinations of smaller network modules with implications on studying synthetic gene circuits, small regulatory systems, and eventually dynamic whole-cell models.</p

DSOGI-PLL based power control method to mitigate control errors under disturbances of grid connected hybrid renewable power systems

The control of power converter devices is one of the main research lines in interfaced renewable energy sources, such as solar cells and wind turbines. Therefore, suitable control algorithms should be designed in order to regulate power or current properly and attain a good power quality for some disturbances, such as voltage sag/swell, voltage unbalances and fluctuations, long interruptions, and harmonics. Various synchronisation techniques based control strategies are implemented for the hybrid power system applications under unbalanced conditions in literature studies. In this paper, synchronisation algorithms based Proportional-Resonant (PR) power/current controller is applied to the hybrid power system (solar cell + wind turbine + grid), and Dual Second Order Generalized Integrator-Phase Locked Loop (DSOGI-PLL) based PR controller in stationary reference frame provides a solution to overcome these problems. The influence of various cases, such as unbalance, and harmonic conditions, is examined, analysed and compared to the PR controllers based on DSOGI-PLL and SRF-PLL. The results verify the effectiveness and correctness of the proposed DSOGI-PLL based power control method

Intelligence approach in improving business processes

Nowadays, business intelligence (BI) has the top-most priority for the contemporary enterprises. The aim of this paper is to emphasize the advantages of this computer based approach in improving business processes. Data analytics and modeling of sales prediction system for enterprise is realized with artificial neural networks (ANNs). For the purpose of this research are created over 100 artificial neural networks. Three types of artificial neural networks are designed and evaluated: Function fitting neural networks, Focused Time-delay neural networks and NARX (Non-linear autoregressive) neural networks. Also were performed simulations with different architectures that differ to the number of delays and the number of neurons in the hidden layer. The network prediction performance was evaluated with Average Percentage Error (APE) and Root Mean Square Error (RMSE). The obtained results show big accuracy in prediction of the product sale. The precise prediction has influence to optimization of most of the business processes such as: supply of raw materials, organization of production process, staff scheduling, plan the electricity demand, cost reduction etc

The Effects of International F/X Markets on Domestic Currencies Using Wavelet Networks: Evidence from Emerging Markets

This paper proposes a powerful methodology wavelet networks to investigate the effects of international F/X markets on emerging markets currencies. We used EUR/USD parity as input indicator (international F/X markets) and three emerging markets currencies as Brazilian Real, Turkish Lira and Russian Ruble as output indicator (emerging markets currency). We test if the effects of international F/X markets change across different timescale. Using wavelet networks, we showed that the effects of international F/X markets increase with higher timescale. This evidence shows that the causality of international F/X markets on emerging markets should be tested based on 64-128 days effect. We also find that the effects of EUR/USD parity on Turkish Lira is higher on 17-32 days and 65-128 days scales and this evidence shows that Turkish lira is less stable compare to other emerging markets currencies as international F/X markets effects Turkish lira on shorten time scale.F/X Markets; Emerging markets; Wavelet networks; Wavelets; Neural networks

Designing of Algorithmfor Calculation of Signal to Noise Ratio for Paralytic Patients Performing Various Activities

Surface electromyography has been used to disease diagnosis, pathologic analysis and muscular disorder. In this paper, we introduce an MATLAB based algorithmfor processing of sEMG signals of paralytic patients. The signal to Noise ratio has been investigated using Hamming window, Hanning window and Rectangular window. In this paper ten paralytic subjects have contributed by performing different finger movement activities. A comparative analysis of signal to noise ratio for finger movement activities has been calculated using hamming, hanning and rectangular window