Robust Guaranteed Cost Control for Yaw Control of Helicopter

针对具有时变不确定性且不确定性界为椭球的线性系统提出了一种新的具有自适应机制的鲁棒保性能控制器设计方法。首先,引入一个具有可由自适应律在线调整的可调参数的目标模型,通过该参数来保证由目标模型与被控模型所获得的误差系统渐近稳定。结合保证目标模型稳定性的设计,最终形成保证闭环系统稳定且控制器增益仿射依赖于可调参数的鲁棒保性能跟踪控制器。应用于安装在试验平台上的小型直升机航向控制中,仿真试验表明了该方法的有效性。

Microcystin-RR-induced accumulation of reactive oxygen species and alteration of antioxidant systems in tobacco BY-2 cells

Microcystins are cyclic heptapeptide hepatoxins produced by cyanobacteria. It has been shown that microcystins have adverse effects on animals and on plants as well. Previous researches also indicated that microcystins were capable of inducing oxidative damage in animals both in vivo and in vitro. In this study, tobacco BY-2 suspension cell line was applied to examine the effects of microcystin-RR on plant cells. Cell viability and five biochemical parameters including reactive oxygen species (ROS), superoxide dismutase (SOD), catalase (CAT), glutathione peroxide (GPX) and peroxide dismutase (POD) were investigated when cells were exposed to 50 mg/L microcystin-RR. Results showed that microcystin-RR evoked decline of the cell viability to approximately 80% after treating for 144 h. ROS levels, POD and GPX activities of the treated cells were gradually increased with a time dependent manner. Changes of SOD and CAT activities were also detected in BY-2 cells. After 168 h recovery, ROS contents, POD, GPX and CAT activities returned to normal levels. These results suggest that the microcystin-RR can cause the increase of ROS contents in plant cells and these changes led to oxidant stress, at the same time, the plant cells would improve their antioxidant abilities to combat mirocystin-RR induced oxidative injury. (c) 2005 Elsevier Ltd. All rights reserved.

基于运动速度的机器人学习控制

为了使机器人跟踪给定的期望轨线，提出了一种新的基于机器人运动重复性的学习控制法．在这种方法中机器人通过重复试验得到期望运动，这种控制法的优点：一是对于在期望运动附近非线性机器人动力学的近似表达式的线性时变机械系统产生期望运动的输入力矩可不由估计机器人动力学的物理参数形成；二是可以适当的选择位置、速度和加速度反馈增益矩阵，从而加快误差收敛速度；三是加入了加速度反馈，减少了速度反馈，减少了重复试验的次数．这是因为在每次试验的初始时刻不存在位置和速度误差，但存在加速度误差．另外，这种控制法的有效性通过ＰＵＭＡ５６２机器人的前三个关节的计算机仿真结果得到验证。

Time-Frequency Analysis of Nonlinear Systems: The Skeleton Linear Model and the Skeleton Curves

The joint time-frequency analysis method is adopted to study the nonlinear behavior varying with the instantaneous response for a class of S.D.O.F nonlinear system. A time-frequency masking operator, together with the conception of effective time-frequency region of the asymptotic signal are defined here. Based on these mathematical foundations, a so-called skeleton linear model (SLM) is constructed which has similar nonlinear characteristics with the nonlinear system. Two skeleton curves are deduced which can indicate the stiffness and damping in the nonlinear system. The relationship between the SLM and the nonlinear system, both parameters and solutions, is clarified. Based on this work a new identification technique of nonlinear systems using the nonstationary vibration data will be proposed through time-frequency filtering technique and wavelet transform in the following paper.

On the invariant representation of spin tensors with applications

The invariant representation of the spin tensor defined as the rotation rate of a principal triad for a symmetric and non-degenerate tensor is derived on the basis of the general solution of a linear tensorial equation. The result can be naturally specified to study the. spin of the stretch tensors and to investigate the relations between various rotation rate tensors encountered frequently in modern continuum mechanics. A remarkable formula which relates the generalized stress conjugate to the generalized strain in Hill's sense. to Cauchy stress, is obtained in invariant form through the work conjugate principle. Particularly, a detailed discussion on the time rate of logarithmic strain and its conjugate stress is made as the principal axes of strain arc not fixed during deformation.

Determining of the delay time for a heating ventilating and air-conditioning plant using two weighted neural network approach

This paper presents an two weighted neural network approach to determine the delay time for a heating, ventilating and air-conditioning (HVAC) plan to respond to control actions. The two weighted neural network is a fully connected four-layer network. An acceleration technique was used to improve the General Delta Rule for the learning process. Experimental data for heating and cooling modes were used with both the two weighted neural network and a traditional mathematical method to determine the delay time. The results show that two weighted neural networks can be used effectively determining the delay time for AVAC systems.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Identification of nonlinear dynamic systems: Time-frequency filtering and skeleton curves

The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system (GSLS). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. Moreover, an identification method is proposed through the skeleton curves and the time-frequency filtering technique.

Identification of Nonlinear Systems Through Time-Frequency Filtering Technique

In the previous paper, a class of nonlinear system is mapped to a so-called skeleton linear model (SLM) based on the joint time-frequency analysis method. Behavior of the nonlinear system may be indicated quantitatively by the variance of the coefficients of SLM versus its response. Using this model we propose an identification method for nonlinear systems based on nonstationary vibration data in this paper. The key technique in the identification procedure is a time-frequency filtering method by which solution of the SLM is extracted from the response data of the corresponding nonlinear system. Two time-frequency filtering methods are discussed here. One is based on the quadratic time-frequency distribution and its inverse transform, the other is based on the quadratic time-frequency distribution and the wavelet transform. Both numerical examples and an experimental application are given to illustrate the validity of the technique.

Optimal bounded control of first-passage failure of strongly non-linear oscillators under combined harmonic and white-noise excitations

A procedure for designing the optimal bounded control of strongly non-linear oscillators under combined harmonic and white-noise excitations for minimizing their first-passage failure is proposed. First, a stochastic averaging method for strongly non-linear oscillators under combined harmonic and white-noise excitations using generalized harmonic functions is introduced. Then, the dynamical programming equations and their boundary and final time conditions for the control problems of maximizing reliability and of maximizing mean first-passage time are formulated from the averaged Ito equations by using the dynamical programming principle. The optimal control law is derived from the dynamical programming equations and control constraint. Finally, the conditional reliability function, the conditional probability density and mean of the first-passage time of the optimally controlled system are obtained from solving the backward Kolmogorov equation and Pontryagin equation. An example is given to illustrate the proposed procedure and the results obtained are verified by using those from digital simulation. (C) 2003 Elsevier Ltd. All rights reserved.

Direct dynamical test for deterministic chaos and optimal embedding of a chaotic time-series

We propose here a local exponential divergence plot which is capable of providing an alternative means of characterizing a complex time series. The suggested plot defines a time-dependent exponent and a ''plus'' exponent. Based on their changes with the embedding dimension and delay time, a criterion for estimating simultaneously the minimal acceptable embedding dimension, the proper delay time, and the largest Lyapunov exponent has been obtained. When redefining the time-dependent exponent LAMBDA(k) curves on a series of shells, we have found that whether a linear envelope to the LAMBDA(k) curves exists can serve as a direct dynamical method of distinguishing chaos from noise.

Single attosecond pulse generation using two-color polarized time-gating technique

It is proposed that single attosecond pulses be generated via high-order harmonic generation by using a two-color pump pulse with time dependent ellipticity. The two-color pump pulse is created by the fundamental field and its second harmonic: the fundamental field is left-circularly polarized and the second harmonic is right-circularly polarized. Numerical simulations show that single attosecond pulses can be produced in the cut-off region by using the synthesis of 20 fs left-hand and right-hand circularly polarized pulses with a pulse delay of 20 fs. The attosecond pulses produced this way are much stronger than that produced by a few-cycle linear polarized pulse of comparable intensity. (c) 2005 Optical Society of America