Optimal full-state feedback observer integrated backstepping control of chemical processes with unknown internal dynamics.

This paper studies the estimation and control problems of chemical processes with unknown internal dynamics. An observer with optimal full-state feedback characteristics for estimating the state variables and unknown dynamics is presented. Unlike other observers that need to know the frequency characteristics of the system, the pole of the proposed observer is determined automatically in a LQR formulation and the observer stability is also inherently ensured. In order to suppress the unknown internal dynamics, the proposed observer is then applied to the control design leading to an observer integrated backstepping control method. The proposed method does not depend on the detailed mathematical model of the system while the stability of the closed-loop system is guaranteed. The stability of the closed-loop system is proven in the Lyapunov sense. Extensive numerical simulations are presented to validate the proposed method.

GPU-based fast processing for a distributed acoustic sensor using an LFM pulse.

We carried out a fast processing investigation based on a graphics processing unit (GPU) for a distributed acoustic sensor using a linear frequency modulation pulse. The moving window cross-correlation calculations are realized on the GPU, which makes use of parallel computing. We analyzed the effect of the thread number in a block on the GPU streaming multiprocessor utilization efficiency and then compared the acceleration under different calculation scales. By maximizing the streaming multiprocessor utilization efficiency and large calculation scale, a maximum acceleration ratio of 86.01 was obtained.