The presented work explored the possibility of developing a discrete wavelet transform-based repetitive control (DWTRC) strategy along with a proportional controller for a liquid level system (LLS) to track a periodic reference signal. The modified DWTRC with a P control system is a type of servo mechanism, effective for periodic reference input. The entire effort derives from two distinct parts. First, the tracking performance and stability measure of the system with inclusion of a repetitive controller (RC) in presence of P controller that has been studied and compared with conventional P and PI controllers in both time and frequency domains, subjected to periodic command to establish the usefulness of the former. The most obvious disadvantage of the RC with P control is the requirement of large memory for the presence of RC, and the memory requirement linearly increases with both repetition time and sampling frequency. Second, to overcome this difficulty, deployment of the discrete wavelet transform (DWT) in the RC loop is done to reduce the problem of memory requirement, and ensures efficient and high-speed computation due to the filtering and data reduction property of DWT. Finally, the effectiveness of DWTRC is validated through saving memory and optimizing the tracking error with variation of the wavelet order and its decomposition level.
Haze and fog removing from videos and images has got massive concentration in the field of video and image processing because videos and images are severely affected by fog in tracking and surveillance system, object detection. Different defogging techniques proposed so far are based on polarisation, colour‐line model, anisotropic diffusion, dark channel prior (DCP) etc. However, these methods are unable to produce output image with desirable quality in the presence of dense fog and sky region. In this study, the authors have proposed a novel fog removal technique where DCP is applied on the low‐frequency component of empirical wavelet transformation coefficients of the foggy input image. They apply unsharp masking on wavelet coefficients of the embedded wavelet transformed image for improving the sharpness of the output image. Later contrast limited adaptive histogram equalisation technique is used as a post‐processing task to the inverse transformed image for producing the sharp and high contrast output. Finally, the colour and intensity of the contrast‐enhanced image are uplifted through S‐channel and V‐channel gain adjustment. The proposed method provides significant improvement to the overall quality of the output image compared to contemporary techniques. The quantitative and qualitative measurements confirm the claims.
In the present paper, a modified obstruction free pressure sensor-based flow transducer has been developed using Hall sensors. This technique is a modified version of the earlier inductive method. In this transducer, the fluid pressure in the pipeline is taken as the flow sensing parameter, and various drawbacks of the earlier inductive technique are eliminated. A prototype unit of the transducer is developed and studied in the present work. The transducer consists of two identical C-type Bourdon gauges, each fitted with an identical permanent magnet and Hall sensor assembly to sense the fluid pressure under flow condition and static pressure under no flow condition. The difference between the two Hall sensor outputs is found to vary nonlinearly with flow rate. The mathematical relations describing the working of the prototype unit are derived in the paper. The static characteristic curves of the proposed flow transducer are determined experimentally and reported in the paper. The characteristic curves are found to follow the derived equations to a very good extent with negligible percentage deviation from best-fit nonlinear characteristic.
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