RDOA based Emitter Localization using Constrained Least Square Algorithm under NLOS Environment

In this paper, we apply Kalman filter and constrained least square (CLS) algorithm for compensating these noises. With the proposed two algorithms, we can confirm high accuracy for localization. A simulation demonstrates the performance of our proposed algorithm. 

Speed Tracking of SPMSM via Super-Twisting Logarithmic Fast Terminal Sliding-Mode Control

This study investigates the speed control of permanent magnet synchronous motors in the presence of external load disturbances via fast terminal sliding-mode control (FTSMC). First, to enhance the speed tracking performance, a logarithmic FTSMC method based on a novel sliding surface is proposed to improve the previously introduced FTSMC. Second, we have derived an enhanced settling time, demonstrating its superiority over that of recently introduced exponential FTSMC through the utilization of a logarithmic sliding surface. Third, the proposed logarithmic FTSMC and exponential FTSMC are compared to demonstrate that the convergence time of the logarithmic FTSMC is less than that of the exponential FTSMC. Forth, super-twisting reaching law is adopted in logarithmic FTSMC to counteract perturbations since it has an ability against various unknown disturbances, such as parameter mismatch, load torque variation, and friction force. Finally, the simulation results show that the proposed strategy can effectively improve the dynamic performance and robustness of permanent magnet synchronous motor systems

Laser-Interferometric Broadband Seismometer for Epicenter Location Estimation

In this paper, we suggest a seismic signal measurement system that uses a laser interferometer. The heterodyne laser interferometer is used as a seismometer due to its high accuracy and robustness. Seismic data measured by the laser interferometer is used to analyze crucial earthquake characteristics. To measure P-S time more precisely, the short time Fourier transform and instantaneous frequency estimation methods are applied to the intensity signal ( I y ) of the laser interferometer. To estimate the epicenter location, the range difference of arrival algorithm is applied with the P-S time result. The linear matrix equation of the epicenter localization can be derived using P-S time data obtained from more than three observatories. We prove the performance of the proposed algorithm through simulation and experimental results

Neural Network-Based Laser Interferometer Compensation for Seismic Signal Detection

We propose a seismic wave detection method in the frequency domain using a heterodyne laser interferometer, which is used in ultraprecision fields as a displacement measurement device. In seismology, it is important to accurately measure seismic waves. To overcome the limited frequency range and low resolution of accelerometers and velocimeters and to enhance the precision of seismic data analysis, we use the heterodyne laser interferometer as a seismic detection apparatus. We apply the data fusion algorithm with the adaptive standard deviation ratio (ς) derived from the neural network to improve the laser interferometer’s measurement precision. Moreover, by using the interferometric characteristics, we analyze the seismic data in the frequency domain. To determine the location of the epicenter from the body wave propagation analysis, we apply the STA/LTA algorithm to the measurement data. The effectiveness of the proposed laser interferometric seismometer is shown through experiments to locate the precise epicenter

Sliding-Mode Control for Flight Stability of Quadrotor Drone Using Adaptive Super-Twisting Reaching Law

In this study, a sliding-mode controller is designed using an adaptive reaching law with a super-twisting algorithm. A dynamic model of a drone is designed with a quadrotor that has four motors and considers disturbances and model uncertainties. Given that the drone operates as an under-actuated system, its flight stability and maneuverability are influenced by the discontinuous signal produced by the reaching law of the sliding-mode control. Therefore, this study aims to improve the sliding-mode control and stability of drone flight using the proposed adaptive law, which is based on exponential properties. The discontinuous signal of a conventional strategy is overcome using the super-twisting algorithm, and the drone rapidly reaches equilibrium using the proposed adaptive law that utilizes the sliding surface value. The proposed control strategy covers a higher dimension than the conventional sliding-mode control strategy; the system stability is proven using the strict Lyapunov function. The reaching time estimation results are introduced and used to compare the respective reaching times of the control strategies. To verify the superior performance of the proposed control method, multiple experiments are conducted under various situations and realizations. The simulation results prove that the proposed control method achieved a superior rapid response, stable maneuvering, and robustness with shorter reaching time

Earthquake Magnitude Estimation Using a Total Noise Enhanced Optimization Model

In this paper, a heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is introduced to measure ground vibration and seismic waves as a seismometer. The seismic wave is measured precisely through the displacement variation obtained by the heterodyne laser interferometer. The earthquake magnitude is estimated using only the P-wave magnitudes for the first 3 s through the total noise enhanced optimization (TNEO) model. We use data from southern California to investigate the relationship between peak acceleration amplitude ( P d ) and the earthquake magnitude ( M g ). For precise prediction of the earthquake magnitude using only the P d value, the TNEO model derives the relation equation between P d and the magnitude, considering the noise present in each measured seismic data. The optimal solution is obtained from the TNEO model based objective function. We proved the performance of the proposed method through simulation and experimental results

Hybrid TDOA and AOA Localization using Weighted Least Square via RSS

In this paper, we propose an estimation technique based on hybrid time differential-of-arrival (TDOA) and angle-of-arrival (AOA) that allows the application of weighted least squares (WLS). The accuracy of localization is a very significant problem since the measurement data can be affected by environmental noise

Speed Regulation for PMSM with Super-Twisting Sliding-Mode Controller via Disturbance Observer

This paper focuses on the speed regulation of a permanent-magnet synchronous motor (PMSM) with an uncertain extended load disturbance. A novel super-twisting sliding-mode control (NSTSMC) was proposed via a nonlinear integral sliding surface and a modified reaching law, effectively suppressing the chattering phenomenon. In addition, the NSTSMC can improve the convergence performance with a 0.04 s settling time, satisfying the super-twisting algorithm stability condition. For the novel integral sliding surface, the integral power term of the system state variables was incorporated into the conventional sliding surface to effectively improve the convergence rate and anti-disturbance ability. Moreover, an extended sliding-mode disturbance observer (ESO) was used to estimate the lumped extended disturbance and add the corresponding feedback compensation value from the sliding-mode disturbance observer to the output of the speed controller for the improved robustness of the system. The ESO-NSTSMC was developed to improve the performance of PMSM speed regulation by combining the advantages of the novel integral sliding surface, achieving a settling time of 0.01 s without overshoot. We confirm the performance of the proposed NSTSMC through a PMSM speed simulation and demonstrate that the controller can enhance the dynamic performance and robustness of the system