渠首水位实时调控模型——以船行灌区一支渠为例

很多大中型灌区在输配水过程中存在水位衔接不当的问题,加之田面高程存在起伏,使得灌溉时往往存在部分田面不能上水或受淹等问题。本文提出了空间灌溉率的概念,并利用GIS的三维分析功能研究了其与渠道渠首水位之间的关系。分析表明,空间灌溉率与渠首水位之间的关系符合Logistic曲线;针对船行灌区一支渠,得到该Logistic曲线的参数,并确定了一支渠渠首和干渠渠首不同空间灌溉率所需的水位,为灌区水位实时调控提供基础数据。     

控制图在复极电解槽控制中的应用

根据离子膜制碱工艺的特点，与控制图的应用理论相结合，寻找控制对象并选择控制图的类型。通过选择合适的工艺参数，使用控制图的数据处理技术对实际数据进行处理，绘制出控制图，利用参数波动符合正态分布的特点对控制图的波动情况进行分析，用来诊断电解槽运行的受控情况。     

航空胶片显影液调整的计算机处理方法

为解决航空胶片显影液调整问题，采用了Visual Basic6.0开发了“显影液化学分析调整软件，该系统具有一定的应用价值。     

GRM-2SD120棉线缠绕机

介绍了GRM－2SD120棉线缠绕机的结构原理，重点介绍了该机的锭子部分，口型部分，锭子盘，中胶部分，传动原理，电气原理及主要技术参数。     

基于全概率公式直接推求管运洪水

本文为保证防洪安全的前提下充分发挥水库的综合效益,提出了基于全概率公式推求管运洪水的方法,并详细阐述了其基本原理;提出了在资料较短或前、后汛期洪水特性大致相同的情况下运用全概率公式推求管运洪水的实际方法;以马边站的洪水资料进行实例研究,其结果表明基于全概率公式推算出来的管运洪水既能使水库工程达到防洪标准,又能充分发挥水库的综合效益。     

超磁致伸缩作动器的率相关Hammerstein模型与H∞鲁棒跟踪控制

利用Hammerstein模型对超磁致伸缩作动器（Giant magnetostrictive actuators,GMA）的率相关迟滞非线性进行建模,分别以改进的 Prandtl-Ishlinskii（Modified Prandtl-Ishlinskii）模型和外因输入自回归模型（Autoregressive model with exogenous input,ARX）代表Hammerstein模型中的静态非线性部分和线性动态部分,并给出了模型的辨识方法. 此模型能在1～100Hz频率范围内较好地描述GMA的率相关迟滞非线性. 提出了带有逆补偿器和H∞鲁棒控制器的二自由度跟踪控制策略,实时跟踪控制实验结果证明了所提策略的有效性.     

Modeling and global trajectory tracking control for an over-actuated MAV

This paper deals with an original micro aerial vehicle (MAV) design, the Omnicopter MAV. It has two central coaxial rotors with fixed-pitch propellers and three perimeter mounted ducted fans with servo motors performing thrust vectoring. Compared with traditional rotary wing MAVs that have inherent underactuation, the Omnicopter possesses some advantages in mobility, for example, lateral translation with zero attitude and hover with nonzero attitude. The trajectory tracking control design, global stability analysis, and control allocation are demonstrated through numerical simulation. The advantage of zero attitude translation is illustrated through experimental results.     

Robust control of variable speed autonomous underwater vehicle

Set point tracking control of autonomous underwater vehicle (AUV) via robust model predictive control (RMPC) is considered. Input-constrained RMPC with integral action, which has been developed in our previous work, is used to control the AUV in this study. In order to derive a RMPC control rule, non-linear dynamics of AUV with six degree of freedom is linearized at certain operating points. So, horizontal and vertical plane dynamics of system are represented by linear models which have polytopic uncertainties. Since the derived control rule will be used in real time, the computation time should be reduced. To overcome this computational time problem and get rid of trial–error step of Algorithm 1, a new algorithm is proposed here. The simulations are carried out using the control rule based on this algorithm and these results are presented.     

Human tracking system based on adaptive multi-feature mean-shift for robot under the double-layer locating mechanism

Human tracking has been a challenging task for robot in the past decades. In this paper, to realize the human following in a cluttered environment, a human tracking system based on adaptive multi-feature mean-shift (AMF-MS) under the double-layer locating mechanism (DLLM) is proposed to solve the problem of distinguishing target, occlusion, and quick turning. The DLLM, considering the course location processing and fine location processing, is designed to estimate the person’s position using the fusion of heterogeneous data. As an ID tag attached on target can be detected by RF antennas, the course locating method can track the target easily and quickly. The Bayes rule is introduced to calculate the probability where the tag exists due to the instability of RF signals. In the fine locating step, the AMF-MS is proposed because it can reduce computational load and represent target by multi-feature histogram function. Meanwhile, we combine extended Kalman filter and AMF-MS to overcome MS’s inability of occlusion. To control the robot following the target person precisely, an intelligent gear shift strategy based on fuzzy control is implemented by analyzing the robot structure. Experiments demonstrate that the proposed approach is robust to handle complex tracking conditions, and show the system has an optimum performance.     

Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.