Discrete state space modeling and control of nonlinear unknown systems

A novel procedure for integrating neural networks (NNs) with conventional techniques is proposed to design industrial modeling and control systems for nonlinear unknown systems. In the proposed approach, a new recurrent NN with a special architecture is constructed to obtain discrete-time state-space representations of nonlinear dynamical systems. It is referred as the discrete state-space neural network (DSSNN). In the DSSNN, the outputs of the hidden layer neurons of the DSSNN represent the system's (pseudo) state. The inputs are fed to output neurons and the delayed outputs of the hidden layer neurons are fed to their inputs via adjustable weights. The discrete state space model of the actual system is directly obtained by training the DSSNN with the input–output data. A training procedure based on the back-propagation through time (BPTT) algorithm is developed. The Levenberg–Marquardt (LM) method with a trust region approach is used to update the DSSNN weights. Linear state space models enable to use well developed conventional analysis and design techniques. Thus, building a linear model of a system has primary importance in industrial applications. Thus, a suitable linearization procedure is proposed to derive the linear state space model from the nonlinear DSSNN representation. The controllability, observability and stability properties are examined. The state feedback controllers are designed with both the linear quadratic regulator (LQR) and the pole placement techniques. The regulator and servo control problems are both addressed. A full order observer is also designed to estimate the state variables. The performance of the proposed procedure is demonstrated by applying for both single-input single-output (SISO) and multiple-input multiple-output (MIMO) nonlinear control problems.     

Automating studies of the technical state of dangerous mechanical systems

Automation of the process of studying the dynamics of the technical state of dangerous machines and constructions by combined application of object-oriented modeling of data and knowledge, model- and precedent-based reasoning, and mathematical modeling is suggested. Automation ensures the efficient performance of preproject studies and also the timely interpretation of parameters of the technical state and identification of failure and damage precursors at the stage of operation, aimed at ensuring reliability and technogenic safety.     

Adaptive extended state space predictive control for a kind of nonlinear systems

This paper presents an adaptive nonlinear predictive control design strategy for a kind of nonlinear systems with output feedback coupling and results in the improvement of regulatory capacity for reference tracking, robustness and disturbance rejection. The nonlinear system is first transformed into an equal time-variant system by analyzing the nonlinear part. Then an extended state space predictive controller with a similar structure of a PI optimal regulator and with P-step setpoint feedforward control is designed. Because changes of the system state variables are considered in the objective function, the control performance is superior to conventional state space predictive control designs which only consider the predicted output errors. The proposed method is tested and compared with latest methods in literature. Tracking performance, robustness and disturbance rejection are improved.     

Estimation of the probability of mechanical systems breakdown by technical state modeling

This study considers the general model of estimating changes in technical state of mechanical systems caused by external action. This model makes it possible to estimate their effect on the probability of breakdowns. The considered examples include the destruction probabilities for crank rods of the opposite compressor to be simultaneously affected by cyclical loading and wear.     

Improved control using extended non-minimal state space MPC and modified LQR for a kind of nonlinear systems

Inspired by the state space model based predictive control, this paper presents the combination design of extended non-minimal state space predictive control (ENMSSPC) and modified linear quadratic regulator (LQR) for a kind of nonlinear process with output feedback coupling, which shows improved control performance for both model/plant match and model/plant mismatch cases. In many previous control methods for this kind of nonlinear systems, the nonlinear part is treated in different ways such as ignored, represented as a rough linear one or assumed to be time-variant when corresponding predictive control methods are designed. However, the above methods will generally lead to information loss, resulting in the influenced control performance. This paper will show that the ENMSSPC-LQ control structure will further improve closed-loop control performance concerning tracking ability and disturbance rejection compared with previous predictive control methods.     

非确定工作状态下机械系统可靠性分析

产品的可靠性是设计出来的,在产品设计阶段如何预计其可靠性水平,为产品设计提供参考显得尤为重要。通过建立零件失效率与零件状态向量、系统失效率与零件失效率、系统状态向量与零件状态向量之间的关系,最终建立起系统状态向量与系统失效率之间的联系。由于系统状态的不确定性,使得系统在工作过程中的可靠性水平也表现出不确定性。利用蒙特卡洛方法,以某机床主轴传动系统为例,利用系统状态向量与系统失效率之间的关系,对非确定工作状态下主轴传动系统的失效率进行了统计规律分析。     

Power and energy in mechanical systems

Damping characteristics of mechanical systems subjected to steady state and transient loading are quantified in terms of power and energy dissipation. A mathematical model of a non-linear single degree of freedom system is used in developing power and energy dissipation equations for steady state and impulse transient loading. Simplified equations for power and energy dissipated in slightly non-linear systems are developed. More elaborate and accurate power and energy equations are also developed for grossly non-linear, impulse loaded systems. Assessment of the validity and accuracy of all equations developed, is facilitated by analog computer simulation studies.     

A micro-coupling for micro mechanical systems

The error motions of micro mechanical systems, such as micro-spindles, increase with the increasing of the rotational speed, which not only decreases the rotational accuracy, but also promotes instability and limits the maximum operational speed. One effective way to deal with it is to use micro-flexible couplings between the drive and driven shafts so as to reduce error motions of the driven shaft. But the conventional couplings, such as diaphragm couplings, elastomeric couplings, bellows couplings, and grooved couplings, etc, cannot be directly used because of their large and complicated structures. This study presents a novel micro-coupling that consists of a flexible coupling and a shape memory alloy(SMA)-based clamp for micro mechanical systems. It is monolithic and can be directly machined from a shaft. The study performs design optimization and provides manufacturing considerations, including thermo-mechanical training of the SMA ring for the desired Two-Way-Shape-Memory effect(TWSMe). A prototype micro-coupling and a prototype micro-spindle using the proposed coupling are fabricated and tested. The testing results show that the prototype micro-coupling can bear a torque of above 5 N · mm and an axial force of 8.5 N and be fitted with an SMA ring for clamping action at room temperature(15 ℃) and unclamping action below –5 ℃. At the same time, the prototype micro-coupling can work at a rotational speed of above 200 kr/min with the application to a high-speed precision micro-spindle. Moreover, the radial runout error of the artifact, as a substitute for the micro-tool, is less than 3 μm while that of turbine shaft is above 7 μm. It can be concluded that the micro-coupling successfully accommodates misalignment errors of the prototype micro-spindle. This research proposes a micro-coupling which is featured with an SMA ring, and it is designed to clamp two shafts, and has smooth transmission, simple assembly, compact structure, zero-maintenance and balanced motions.     

Adaptive diagnosis of the bilinear mechanical systems

A generic adaptive approach is proposed for diagnosis of the bilinear mechanical systems. The approach adapts the free oscillation method for bilinearity diagnosis of mechanical systems. The expediency of the adaptation is proved for a recognition feature, the decrement of the free oscillations. The developed adaptation consists of variation of the adaptive likelihood ratio of the decrement with variation of the resonance frequency of the bilinear system. It is shown that in the cases of the frequency-independent and the frequency-dependent internal damping, the adaptation is expedient. To investigate effectiveness of the adaptation in these cases, a numerical simulation was carried out. The simulation results show that use of the adaptation increases the total probability of the correct diagnosis of system bilinearity.     

空间光学系统反射镜轻量化技术综述

分别从材料选择、制造工艺、结构形式等方面对国内外空间光学系统反射镜的轻量化技术进行了系统的评述,分析了轻型反射镜技术的现状和发展趋势。针对国内的技术水平,对今后的研究工作提出了几点建议。     

机械拼接时间延迟积分CCD空间相机的振动参数检测

为了获取空间相机在轨摄像期间的振动幅频特性,提出了一种基于TDICCD拼接技术的空间相机振动参数检测方法。根据TDICCD拼接原理,利用拼接结构中的重叠成像区域在不同时刻对同一景象成像,通过灰度投影算法对所成图像进行比对求取相对偏移量,拟合偏移量数据,进而根据拟合结果计算出空间相机振动参数。实验结果表明:对于一维单一频率的振动,频率相对误差小于0.5%,振幅绝对误差小于1个像元;对于一维混合频率的振动,频率相对误差小于3%,振幅绝对误差小于2个像元;对于沿推扫方向和垂直推扫方向均为单频振动的二维振动,频率相对误差小于1%,振幅绝对误差小于2个像元。实验结果验证了检测方法的正确性,达到了不增加额外设施,仅利用相机自身结构就能精确测量相机振动参数的目的,并为后续图像复原提供了数据基础。     

空间红外光学系统技术综述

红外光学系统用于探测目标自身辐射,可昼夜工作。随着空间技术的飞速发展,对空间分辨力以及对观测目标覆盖面积的要求越来越高,大口径大视场的空间红外光学系统在空间对地以及对其它星球遥感观测中广泛应用。介绍了大口径大视场空间红外光学系统的几种结构形式及其优缺点和发展趋势。     

Stress state of cylindrical pipe with variable mechanical properties

The use of multilayer pipe whose yield point varies over the thickness is considered. The plastic deformation of pipe whose yield point varies over the volume is discussed.     

Robustness of discrete-time state feedback control systems

This paper presents stability robustness results for linear multivariable discrete-time systems with uncertainties. Robust stability of the full-state feedback linear quadratic regulator in the presence of perturbations of the system parameters is investigated. These results are based on recently developed bounds on structured perturbations of a stable linear discrete-time system. The paper applies these results to a paper-machine head box system example.     

基于状态空间的电力有源滤波器控制策略

基于状态空间法对通过LCL与电网连接的电力有源滤波器进行了建模,通过对LCL滤波器特性的分析,应用全状态反馈来抑制LCL滤波器的谐振.在建模基础上把电网影响引入观测器设计,研究了电网建模对状态估计效果的影响,并解决了电网对APF补偿输出造成的无功问题.给出了电网电压前馈的规律.最后的仿真结果证明了该设计的正确性.     

一种基于状态空间离散化的粒子滤波器

粒子滤波是一种基于蒙特卡罗仿真的最优回归贝叶斯滤波算法。这种方法不受线性化误差和高斯噪声假定的限制,适用于任何状态转换或测量模型,因此能够很好地解决非线性、非高斯环境下系统的状态估计问题。在它的设计中最重要的一步就是建议分布的选取。传统的算法需要在整个状态空间中进行计算,这浪费了大量的计算时间。该文提出一种新的建议分布的构造方法,它基于状态空间离散化的思想来构造建议分布。仿真结果表明,相对传统的算法这种粒子滤波器能用更少的粒子产生更准确的估计值。     

对在用起重机械安全技术检测结果的分析

本文通过对各类生产企业在用的七种类型起重机进行全面的安全技术检测,从机械与结构和电气与安全装置两方面提出普遍存在的事故隐患,并对事故隐患、技术缺陷形成原因进行分析总结。为起重机械隐患的治理和设计、制造、安装、使用、维修以及安全技术监督检验、监察等提供参考。     

Manufacture of electronic systems by mechanical systems based on multicoordinate executive devices

The use of multicoordinate executive devices in electronic manufacturing is considered. The performance of electronic equipment may be significantly improved by using l-coordinate devices. In contrast to traditional executive devices, these may function simultaneously as manipulators, transport systems, and vibration suppressors.     

Expert systems in mechanical and manufacturing engineering

This paper consists of two parts. In the first part, the technology underlying the field of knowledge engineering is reviewed to highlight the nature of expert systems and their internal organisation. The review focuses on the two key elements of these intelligent programs, the knowledge base and the inference mechanism. It is seen that the knowledge base can be constructed as a collection of facts and rules, as a hierarchy of frames storing information on classes of objects or concepts and specific instances of these, or as a network of nodes representing these objects or concepts, interconnected by arcs standing for relations between them. In the second part, recent applications of expert systems in mechanical and manufacturing angineering are surveyed. Expert systems developed for these applications are discussed under three headings according to whether they solve derivation problems (such as equipment and process selection, machine condition monitoring, fault diagnosis, etc.), formation problems (synthesis and analysis of machine elements and machine systems), or problems involving a degree of derivation as well as formation (process planning, production scheduling, system configuring).