The discrimination between earthquakes and artificial explosions is a significant issue in seismic analysis to efficiently prevent and respond to seismic events. However, the discrimination of seismic events is challenging due to the low incidence rate. Moreover, the similarity between earthquakes and artificial explosions with a local magnitude derives a nonlinear data distribution. To improve the discrimination accuracy, this paper proposes machine-learning-based seismic discrimination methods—support vector machine, naive Bayes, and logistic regression. Furthermore, to overcome the nonlinear separation problem, the kernel functions and regularized logistic regression are applied to design seismic classifiers. To efficiently design the classifier, P- and S-wave amplitude ratios on the time domain and spectral ratios on the frequency domain, which is converted by fast Fourier transform and short-time Fourier transform are selected as feature vectors. Furthermore, an adaptive synthetic sampling algorithm is adopted to enhance the classifier performance against the seismic data imbalance issue caused by the non-equivalent number of occurrences. The comparisons among classifiers are evaluated by the binary classification performance analysis methods.

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.

A modified sigmoid sliding mode control (MS-SMC) approach is proposed for stabilizing and tracking a quadrotor system with a nonlinear sliding surface, where the dynamics model is underactuated, highly coupled, and nonlinear. The constructed nonlinear sliding surface is based on the traditional sliding mode surface with a modified sigmoid function, allowing the initial value to quickly reach equilibrium. A new type of nonlinear SMC is applied for performance improvement of the quadrotor using the proposed modified sigmoid sliding surface. To control the quadrotor effectively, a double-loop control method is used to design the control rate, in which the position subsystem is the outer loop, and the attitude subsystem is the inner loop.With the Lyapunov function, the stability of the overall closed-loop system is ensured by stabilizing each subsystem step by step. Moreover, from a practical point of view, the system performance under the model uncertainties and external disturbances are also considered. The simulation results show that the proposed MS-SMC performs better than the conventional sliding mode control (CSMC) and the back-stepping sliding mode control (BS-SMC) in terms of stabilization and tracking against external disturbances.

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To enhance the position and attitude-control of quadrotor for trajectory tracking, we propose a fast decay function utilizing exponential property to improve the performance of global sliding-mode control, allowing the initial value to quickly reach equilibrium. The main research is focused on deriving the finite settling time using the proposed decay function and presenting a detailed calculation process, instead of making a simple modification to a monotonic exponential-decay function. Moreover, we adopt an adaptive control law to ensure the robustness of the quadrotor, even without knowing the upper bound for disturbances. In addition, we perform time-varying mass simulations because the quadrotor's load mass may change during maneuvering. Furthermore, using the Lyapunov function, the stability of the entire closedloop system is ensured by the step-by-step stabilization of each subsystem. The simulation results show that the rapid global sliding-mode control (RGSMC) we designed is more effective than the conventional global sliding-mode control and adaptive sliding mode control with respect to stabilization and tracking against external disturbances. Hence, the fast decay property of the proposed global function is verified.