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With the aim of assessing differentiation of greenhouse gas emissions as manipulated by plastic film mulching (PFM) from paddy field from a year-round perspective, we determined net ecosystem CO2 exchange (NEE, CO2 flux), CH4 and N2O fluxes from a rice–rapeseed rotation field. PFM and non-mulching (NM) treatments were set from 2014 to 2017 (May 2014 to April 2015, May 2015 to April 2016 and May 2016 to April 2017 were set as Annual 1, Annual 2 and Annual 3, respectively) in Southwest China. Compared with NM, CH4 emissions were increased by 60.00% (P

An adaptive dynamic surface control (DSC) scheme is proposed for the multi-input multi-output attitude control of near-space hypersonic vehicles (NHV). The proposed control strategy can improve the control performance of NHV despite uncertainties and external disturbances. The proposed controller combines dynamic surface control and radial basis function neural network (RBFNN) and is designed to control the longitudinal dynamics of NHV. The DSC technique is used to handle the problem of “explosion of complexity” inherent to the conventional backstepping method. RBFNN is used to approximate the unknown nonlinear function, and a robustness component is introduced in the controller to cancel the influence of compound disturbance and improve robustness and adaptation of the system. Simulation results show that the proposed strategy possesses good robustness and fast response.

This paper proposes an anti-disturbance control scheme for the near space vehicle (NSV) based on terminal sliding mode (TSM) technique and disturbance observer method. To tackle the system uncertainty and the time-varying unknown external disturbance of the NSV, a disturbance observer based on TSM technique is designed which can render the disturbance estimate error convergent in finite time. Furthermore, an auxiliary design system is introduced to analyze the input saturation effect. Based on the developed disturbance observer and the auxiliary design system, an anti-disturbance attitude control scheme is developed for the NSV using the TSM technique to speed up the convergence of all signals in closed-loop system. For the closed-loop system, the stability is rigorously proved by using the Lyapunov method and we guarantee the finite time convergence of all closed-loop system signals in the presence of the integrated affection of the system uncertainty, the input saturation, and the unknown external disturbance. Simulation study results are given to show the effectiveness of the developed TSM anti-disturbance attitude control scheme using the disturbance observer and the auxiliary system for the NSV.

This paper describes the design of guaranteed transient performance based attitude control for the near space vehicle (NSV) with control input saturation using the backstepping method. To improve the robust controllability of the NSV, the parameter adaptive method is used to tackle the integrated effect of unknown time-varying disturbance and control input saturation. Based on the backstepping technique and parameter estimated outputs, a robust attitude control scheme is proposed for the NSV with input saturation. A novel robust attitude control scheme is then proposed based on a prescribed performance bound (PPB) which characterizes the convergence rate and maximum overshoot of the attitude tracking error. The closed-loop system stability under both the developed robust attitude control schemes is proved using Lyapunovs method and uniformly asymptotical convergence of all closed-loop signals is guaranteed. Finally, simulation results are given to show the effectiveness of both the proposed robust constrained attitude control schemes.

In this paper, a robust synchronization control scheme is proposed for chaotic systems in the presence of system uncertainties and unknown external disturbances. For the synchronization error system, the compound disturbance which is estimated using the disturbance observer cannot be directly measured. If the gain matrix is properly chosen, the disturbance observer can approximate the unknown compound disturbance well. And then, the constrained robust synchronization control scheme is presented for uncertain chaotic systems based on the output of disturbance observer. In the design of a robust synchronization control scheme, the effect of unknown control input constraint has been explicitly considered to guarantee the synchronization performance. Numerical simulation results are presented to illustrate the effectiveness of the proposed constrained synchronization control scheme for uncertain chaotic systems.

This paper is concerned with the problem of hypersonic vehicle (HSV) attitude control system in uncertain flight conditions. The problem can be expressed as the adaptive robust control for a class of uncertain nonlinear systems. Based on the description of the aerodynamic structure and the model of flight control system of a certain kind of HSV, the ideal nonlinear generalized predictive control (NGPC) law based on uncertain nonlinear model is raised first to optimize the receding-horizon criterion of tracking errors. Then the online support vector regression (SVR) is employed to identify the uncertain item in the ideal control law. It is the compensating part of the controller. In addition, the stability of the close-loop system is analyzed using the Lyapunov method. The developed control strategy is well-implemented in this HSV attitude control system, and the simulation results compared with both nominal NGPC and RBF neural network disturbance observer show the good robustness and disturbance attenuation ability of this strategy and demonstrate the efficiency of online SVR algorithm.

In this paper, a robust control scheme is proposed for a class of time-delay uncertain nonlinear systems with unknown input using the sliding mode observer. The sliding mode state observer is given with radial basis function neural networks, and then the robust control scheme is presented based on the designed sliding mode observer. The developed observer-based control scheme consists of two parts. One term is a linear controller and the other term is a neural network controller. Using the Lyapunov method, a criterion for bounded stability of the closed-loop system is developed in terms of linear matrix inequalities. Finally, a simulation example is used to illustrate the effectiveness of the proposed robust control scheme.

This paper presents a novel fuzzy tracking control method, which is used for the reentry attitude tracking problem of a reusable launch vehicle. Based on Takagi-Sugeno fuzzy description of reentry attitude dynamics, the tracking error of attitude angles is studied. Without the need of an augmented system, exponential stability of the tracking error can be obtained by a fuzzy feedforward controller. In addition, to achieve a good tracking performance, H∞ and decay rate ν control methods are considered. The solutions to the robust fuzzy tracking control problem can be obtained by applying linear matrix inequalities and fuzzy logic controller tools. The simulation results demonstrate the effectiveness of the proposed method.

In this paper, a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network. The sensor fault and the system input uncertainty are assumed to be unknown but bounded. The radial basis function (RBF) neural network is used to approximate the sensor fault. Based on the output of the RBF neural network, the sliding mode observer is presented. Using the Lyapunov method, a criterion for stability is given in terms of matrix inequality. Finally, an example is given for illustrating the availability of the fault diagnosis based on the proposed sliding mode observer.

Long-term seismic activity prior to the December 26, 2004, off the west coast of northern Sumatra, Indonesia, M W=9.0 earthquake was investigated using the Harvard CMT catalogue. It is observed that before this great earthquake, there exists an accelerating moment release (AMR) process with the temporal scale of a quarter century and the spatial scale of 1 500 km. Within this spatial range, the M W=9.0 event falls into the piece-wise power-law-like frequency-magnitude distribution. Therefore, in the perspective of the critical-point-like model of earthquake preparation, the failure to forecast/predict the approaching and/or the size of this earthquake is not due to the physically intrinsic unpredictability of earthquakes.