1. Control Methodology 2. Dynamical Systems 3. Applications to Social and Environmental Problems

Dynamics and Control

Detection of Alzheimer's disease (AD) from magnetic resonance images can help neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain. Currently, scholars have proposed several approaches to automatically detect AD. In this study, we aimed to develop a novel AD detection system with better performance than existing systems. 28 ADs and 98 HCs were selected from OASIS dataset. We used inter-class variance criterion to select single slice from the 3D volumetric data. Our classification system is based on three successful components: wavelet entropy, multilayer perceptron, and biogeography-base optimization. The statistical results of our method obtained an accuracy of 92.40 ± 0.83%, a sensitivity of 92.14 ± 4.39%, a specificity of 92.47 ± 1.23%. After comparison, we observed that our pathological brain detection system is superior to latest 6 other approaches.

Single slice based detection for Alzheimer's disease via wavelet entropy and multilayer perceptron trained by biogeography-based optimization

Water level sensing: State of the art review and performance evaluation of a low-cost measurement system

Triangular functions (TF) method for the solution of nonlinear Volterra–Fredholm integral equations

A denoising method for a hydropower unit vibration signal based on variational mode decomposition (VMD) and approximate entropy is proposed. The signal was decomposed by VMD into discrete numbers of modes, then the approximate entropy of each mode was computed. These modes were reconstructed according to a preset threshold of the approximate entropy. Finally, the denoising of the hydropower unit vibration signal can be achieved. A simulation signal and real signals of hydropower unit vibration were used to verify the proposed method. The results showed that the proposed method had a good denoising performance and was better than the wavelet transform method in the signal-to-noise ratio (SNR), root mean square error (RMSE) and partial correlation index. It was ideally suited for the online denoising of the hydropower unit vibration signal.

Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy

An evolutionary optimization-based design of Smith delay compensator for cascade control of MIMO time-delay industrial process

This paper deals with the development of a three term controller with varying resolution applicable to a standard third order plant. In the proposed controller, multi resolution property of WT is employed to decompose the error signal into frequency components at different levels of the decomposition. The values thus obtained are weighted by tuned constants and summed up to yield the final driving output. Calculated performance quotients infer that the designed one needs lesser time to attain specified time domain response as well as improved extraneous disturbance suppression potency compared to conventional counterpart. Also the same has an ability to provide smooth control signal. National Instruments (NI) LabVIEW software is used to develop this controller.

http://ieeexplore.ieee.org/iel7/7400053/7413696/07413742.pdf

Anindita Sengupta

Papers

An evolutionary optimization-based design of Smith delay compensator for cascade control of MIMO time-delay industrial process

Performance study of multiresolution PI controller for third order system