Journal of Artificial Intelligence in Electrical Engineering
Volume:5 Issue: 18, Summer 2016

The main problem of vehicle vibration comes from road roughness. An active suspension system possesses the ability to reduce acceleration of sprung mass continuously as well as to minimize suspension deflection, which results in improvement of tire grip with the road surface. Thus, brake traction control and vehicle maneuverability can be improved consider ably .This study developed a new active suspension system for a quarter-car model. The designed system is based on neural network controller with an input as a regressor and it provided through a lag network that includes reference input , system output and control signal system to the previous sate. In this paper, the system is based on neural network controller that is a regressor input provided through a lag network, including reference input, system output and control signal to previous state. The neural network outputs are the same control signals applied to the suspension system. Feedback system is taken as the output of the displacement body and is applied to lag network. Roughness of the road surface is considered as a reference input. To train, the neural network uses different idea by introducing a cost function for the system and optimizing it, the best coefficients are selected for the neural network.

Robots play such remarkable roles in humans’ modern lives that performing many tasks without them is impossible. Using robotic systems is gradually increasing the tasks allocated to them and they are becoming more complex and critical. Software reliability is one of the most significant requirements of robots. For enhancing reliability, systems should be inherently designed to be tolerable of soft errors. In this study, via software, a method was proposed to enhance the reliability of the software embedded within robots against soft errors with minimum efficiency overhead. In as much as the research method was based on experiment, a set of programs was used as benchmarks. Indeed, errors were injected at the execution time of programs for evaluating them. The data related to the execution behavior of the programs were accumulated and then were analyzed. Simplescaller simulation software was used for investigating program behavior in the presence of the injected error. [2]

The major aim of this article is modeling of nonlinear systems with friction structure that, this method is essentially extended based on taylore expansion polynomial. So in this study, the taylore expansion was extended in the generalized form for the differential equations of the statespace form. The proposed structure is based on multi independent variables taylore extended. According to the proposed method, in order to extract state-space form modeling, it is needed to some samples of the measured value of system states and/or their combination. Then, the matrix of measured values and response vectors of derived states were forming by these measured value of system states. By use of the presented equations and the measured values, the coefficients of polynomials were calculated as the model of state-space of studied nonlinear system. The result of proposed simulation using proposed algorithm show, that it is importable having an independent information system under test to system identification. A few suggestion were proposed to decrease of the dependence of the measured samples, the results of algorithm with different parameters show that proposed algorithm perform better. Of course in during the evaluation of algorithm, the results of different experimental were used.

The meaning of the term ‘hypertrophy’ is the increasing size. Heart hypertrophy is a symptom of increase in the thickness of the heart muscle and the left ventricular hypertrophy is the most common type. The causes of hypertrophy heart disease are high blood pressure, aortic valve stenosis and sport activities, respectively. The assessment of this amount by using ECGsignal analysis is essential because the risk of heart disease. Ventricular hypertrophy increases the timely diagnosis. The ECG signal demonstrates heart electric activities and includes some characteristic points such as P wave, QRS complex, and the T wave is formed. In this study an algorithm has been presented for the assessment of diagnosis of ventricular hypertrophy. In The presented algorithm, first picks of ECG signal have been assessed and then a high degree of statistical information such as skewness, kurtosis, R peak height, and cumulants has also been used.

The ability to move in complex environments is one of the most important features of human beings and animals. In this work, we exploit a bio-inspired method to generate different gaits in a bipedal locomotion system. We used the 4-cell CPG model developed by Pinto [21]. This model has been established on symmetric coupling between the cells which are responsible for generating oscillatory signals. These signals are served as activation signals sent to muscle groups. We used the Morris-Lecar equations as internal nonlinear dynamics of the cells, and considered a diffusive type to model couplings between the cells. We succeeded to obtain periodic solutions corresponding to the bipedal gaits of walk, run, two legged jump, and two legged hop, extracted from the 4-cell CPG model, by numerical simulations. In fact, gait generation is done by the adjustment of the coupling weights which are justifying correct phase differences between the oscillatory outputs of the cells. Moreover, in order to optimize the performance of the produced gaits, a non-dominated sorting genetic algorithm is utilized to adjust the coupling weights.

In this article the place and capacity of combined heat and power [CHP] prediction unit was determined dynamically with use of modified particle swarm optimization (MPSO). It was done in optimization palace and with a capacity of CHP as a production resource with the aim to increase the reliability capacity. Decrease the loss and provide the electrical and thermal energies of industrial city. The function of the optimization to the interest of CHP usage was described on its cost. It was considered as the cost of investments, operation, and Repair and keeping the CHP units in the function. It was proposed that load distribution and limits of CHP production be seen as units’ condition as optimization issue condition. The problem was described as dynamic programming and it was used based on the interests of programming and inflation annually in the determined and thermal energies’ price. The simulation results show the positive effects of CHP units in the electrical energy production of industrial city.

In recent years, along with rapid developments in technology, computer systems have increasingly become more integrated and more modular. Indeed, the reliability and efficiency of computer systems are of high significance. Hence, the quantitative evaluation of the optimization of reliability indexes in computer systems is considered to be a crucial issue. Reliability enhancement of computer systems against electromagnet and radiation interferences is a critical requirement in industries. Enhancing reliability can prevent system failure and fault and avoid financial and humanistic losses. Accordingly, software can play outstanding roles in reducing the number of errors in software programs. Consequently, software can enhance the reliability of computer systems. In this paper, an efficient software-based method was proposed to enhance the reliability of computer systems against soft errors. The results of the experiments revealed that the proposed method had lower overhead, higher efficiency and higher error coverage than the earlier methods.