Search

Speech recognition can be an important tool in today’s society for hand-free or voice-driven implementation. Using simple commands or triggers, it is possible for speech impaired human beings to communicate with increased ease of understanding. With the advent of various soft computing methods, a large class of nonlinearities can be handled. Artificial Neural Networks (ANN) have been applied in finding the solution for speech recognition. A lot of work is going on in this regard and mostly positive results have been achieved. Now, the research is being done to minimize the rate of error in obtaining the solution. In this paper, a comprehensive study of use of artificial neural networks in speech recognition is studied and proposes methods for training of the neural network so that an appropriate neural output can be obtained which is as close to the desired output. The paper demonstrates that ANN can indeed form the basis for a general-purpose speech recognition and neural network offers clear advantages over conventional methods. MATLAB simulation has been carried out to validate the results.

The algorithm of modulation recognition using a single higher-order cumulant as the characteristic parameter is usually limited, and the recognition performance needs to be improved, for this reason, a recognition method is proposed, which uses the combination of multiple higher-order cumulants to construct the characteristic parameters, so that it contains more signal characteristics, and realizes the recognition of multiple signals of MASK, MPSK, and MFSK. The MATLAB simulation shows that it has a better recognition rate.

This paper presents a delineation of passive islanding detection techniques. APV-connected microgrid system is studied and simulated in MATLAB/Simulink and a trip signal is generated in case of detection of islanding. Broadly classified, the two methods of islanding detection are remote and local methods. Passive methods being one of local methods that utilize local parameters are used for the analysis. Local parameters at PCC are taken into account and compared with threshold to generate trip signal for breaker so as to disconnect the DG after islanding. Passive islanding detection technique being of the most sophisticated technique in implementation has a great disadvantage of non-detectable zone, still can be used in small system where remote technique becomes cumbersome in implementation.

Application of firefly algorithm (FA) tuned integral double derivative (IDD) and proportional integral double derivative (PIDD) controllers are addressed in this article. Two identical areas have been anticipated with a thermal unit as the first one, hydropower as a second system, and gas power plant as the third component in each area. At the outset, the IDD controller has been employed, and then, PIDD controller has been employed to exhibit its supremacy when evaluating against IDD controller in terms of dynamic responses. FA has been used to attain the gains of IDD and PIDD controllers. Robustness analysis has been accompanied to find the dominance of the PIDD controller through MATLAB simulation.

Firstly, this method employs Gaussian fitting based on the phase transform generalized cross-correlation (PHAT-GCC) method to get a more precise location of the peak, which makes TDE precision into sub-sampling point level. Secondly, the post-processing algorithm of time delay based on mean and median is exploited to deal with abnormal fluctuation of TDE. The real-life data and MATLAB simulation show that the proposed method is obviously advantageous over the PHAT-GCC method on the precision of TDE and anti-noise performance under the complex environment.

This paper presents a novel method for tuberculosis bacteria segmentation in microscopic images. Manual identification of the bacterial cell is a very difficult process. The automation in tuberculosis bacteria detection is the object of this article using microscopic image processing. In the proposed segmentation method, firstly image enhancement is done followed by the bacteria region masking. Further, the marking of bacteria points is performed by the marked point process model. Finally, the complete bacteria are identified by the superellipse and supervised variational contour models. MATLAB simulation results confirm the superiority of the proposed method as compared with the state of the art methods, on the basis of segmentation accuracy, F1-score, and Dice similarity coefficient.

In this paper, the pure electric brake of the train and the vector control of the asynchronous motor without speed sensor are studied, respectively. The pure electric brake of the train is controlled by a combination of regenerative brake and reverse brake. The estimation method of the feedback speed is based on the Model Reference Adaptive System (MRAS), and both the traditional MRAS and the improved MRAS are analyzed. In this paper, pure electric brake and MRAS estimation are combined to get a better system. Finally, by using the improved MRAS speed estimation method, a simulation of the pure electric brake with speed sensorless control is established with MATLAB simulation software to verify the study.

In this paper, multilevel inverter configuration called dual-inverter (DI) topology is presented in favor of asynchronous motor drive. The topology is easy in constriction as well as easy to operate when compared with other multilevel inverter configurations. Two special kinds of PWM methods are presented in favor of DI topology to recover the excellence of production voltage as well as decrease the common-mode voltage value. To test the concert of the PWM methods in favor of DI topology, first theoretical studies are carried and next model analysis is carried; here, MATLAB simulation model as well as outcome is presented.

This paper proposes sliding mode control (SMC) and PID control-techniques for designing a controller for a second-order stable process. In this paper, the controllers are designed using sliding mode control and Skogestad internal model control (SIMC)-PID control technique and the parameters of these controllers are obtained by the particle swarm optimization (PSO) technique. MATLAB simulation is performed for the second-order plus delay time process (SOPDT) using step input. The results found by the proposed methods are compared with the recently reported methods in the literature. The proposed controller ensures more robustness to parameter variations and fast disturbance rejection capability.

MATLAB provides matrix operations, drawing functions and data, implementing algorithms, creating user interfaces, connecting programs to other programming languages, and providing a graphical interface to Windows. According to the characteristics of MATLAB simulation software, this paper explores its application in automation teaching.

In this review paper, we studied and implementing techniques of HESS for EV. It is very important to perform EV. This is well performed in matlab simulation on EV For HESS consists Li-ion batteries, sup-cap, to charging and discharging the EV. Main controlling system is designed using ANN to performing to get their result by using PI controller. It reduces the calculation complexity of system by reducing the values of proportional constant and integral constant calculations. The neural network promotes self-learning of system and reduces fluctuation if any. An innovation for down to energy is the capacity to store any energy for short time and recover the energy.

This study explains about the SIMO plant statistics of observer-based control to a rotational electro-mechanical system. A robust linear quadratic regulator controller is proposed here, in this study, to observe all the states after recognizing the linear model. The unknown states were determined by the method and for the tuning of the weighted matrices various methods were applied. This full state feedback controller was able to produce faster and smoother output stabilization, which leads to better robustness. The model is highly nonlinear, and model identification is done by MATLAB simulation procedure.

This paper introduces a simulation of three-phase grid-connected solar photovoltaic system. The objective of this paper is to represent a grid synchronization strategy by using the current control method. The focus is to design an inverter control topology which will enable inverter to synchronize with the grid. The theoretical concept of the grid synchronization is described in detail here. The MATLAB simulation results for grid integration of solar PV system agrees with the theoretical concept.

Underwater Wireless Sensor Networks (UWSNs) play a major role in many aquatic applications. Underwater sensors were deployed over a given three-dimensional area. Dynamic and unpredictable nature of the underwater environment is resulting in void communications, interrupting the flow of data to the sink node. Sensor nodes, which are part of void communications are called void nodes, and in multi-hop communication nodes depend on void which are called trap. Any deployed node can become a void or trap not only after their deployment but also during their initial deployment. Most popularly used random deployment strategy in UWSNs always results in the many voids and traps. To countermeasure, the shortfall additional nodes are deployed, which may result in still worse condition. The first objective of this paper is highlighting void and trap node problems in random deployment strategy. In the second objective, we are proposing a systematic way of sensor node deployment that overcomes void and trap problems arising in random deployment in UWSNs. Through the MATLAB simulation drawbacks of random and benefits of systematic deployment strategies are demonstrated using a count of void & trap nodes, volume of the area covered, and count of retained void & traps.

Manipulators are widely used in all areas of science and technology. Effective trajectory tracking and quick deflection suppression are the two main aspect of research for a flexible manipulator. The paper reports aperiodic signal like trajectory tracking control for a planar assumed modes modelled two-link flexible manipulator (TLFM). The aperiodic chaotic signal is used as a desired trajectory for the TLFM. Thus, designing of a robust controller for the aperiodic signal tracking control is a challenging task. A backstepping based adaptive SMC technique is designed for the considered problem. In adaptive SMC, the gain of the switching control law is estimated online. The effectiveness of the considered controller is compared to an available backstepping controller. It is found that the designed backstepping based adaptive SMC perform better in terms of smaller tracking time, quick tip deflection suppression and lesser, smoother control efforts. Proposed trajectory strategy is validated on a two-link flexible manipulator in MATLAB simulation environment.

This paper presents the study of the effect of transformer’s turn ratio mismatch on the performance of dual active bridge (DAB) converter. DAB converter was part of the components of a solid state transformer (SST) where it provides galvanic isolation as well as interface systems with different voltage level. In this study, a DAB circuit was developed and the performance was examined in both MATLAB Simulation and hardware-in-the-loop (HIL) simulation. The DAB system was examined under five different transformer ratio. The behavior of the DAB shows a comparable results under both test platform. The real-time performance of DAB converter has shown an efficiency up to 95.91%.

The functioning of the lung tissues will be affected by asthma; the proper treatment needs to be given to the asthma patients to ensure the human’s safety. In the earlier research work, vote-based ensemble classifier approach is utilized for disease diagnosis. Nevertheless, the level of the disease may differ for every patient in terms of different factors like age and environmental situations which might affect the proper treatment. This problem is resolved by presenting the asthma disease finding and level categorization technique (ADF-LCT) which is utilized to detect the various categories of asthma disease level in terms of patient’s health status. In the proposed work, the Bayesian network is utilized to detect the existence of the disease by calculating the probability difference among the asthma genome profile and the input gnome details. Then, the disease level is detected by classifying patient’s health details into three main categories such as low severe asthma (LSA), middle severe asthma (MSA), high severe asthma (HSA), and very high severe asthma (VHSA). The overall research of the work is executed in MATLAB simulation environment by utilizing the genome expression which proved proposed work leads to efficient prediction outcome.

This paper introduces that the modeling of proton exchange fuel cell has been considered for MATLAB simulation of FC model. Additionally, the possible contrivance of the parametric effects and their interrelationships are deliberated. In this investigation, the significant operating parameters such as reactants (hydrogen and oxygen) flow pressures, membrane resistance, operating temperature are considered. The obtained results as I–V or polarization curves have been carried out for the study of PEMFC behavior. The results show good pacts between the simulated and commercial available PEMFC model. Moreover, the power management schemes are designed and investigated.

Based on predictive control theory and transparent control structure, this paper presents that Dynamic Matrix Control (DMC) is used in temperature control system of chromatograph to deal with the time delay problem. Firstly, the principle of DMC algorithm is introduced. Then, the temperature control system of chromatograph is constructed in the form of multilayer hierarchical structure, including sectional PID and DMC. According to the MATLAB simulation research and experimentation results on the chromatograph, this method can effectively obtain a better tracking performance, compared with the PID control system, and is valuable in industry control field.

Horizontal damage zone is an important index to reflect the anti missile capability of ship-to-air missile. First, research the ship-to-air missile’s horizontal damage zone problem. By the ship-to-air missile and target as far as the meeting point determine the boundary of horizontal damage zone. Then, analyzing the characteristics of different cooperative mode operation, and according to the different mode of cooperation gives the method of calculation of ship-to-air missile’s horizontal damage zone. Last, giving an example of formation air defense operation, by Matlab simulation verifies the correctness of the conclusion.