FIGURE 2.5 Advanced intelligent automatic system with
multi-control levels, knowledge base, inference mechanisms, and interfaces. for maintenance or even redundancy actions, economic optimization, and coordination. The tasks of the higher levels are sometimes summarized as ―process management.‖ Special Signal Processing The described methods are partially applicable for nonmeasurable quantities that are reconstructed from mathematical process models. In this way, it is possible to control damping ratios, material and heat stress, and slip, or to supervise quantities like resistances, capacitances, temperatures within components, or parameters of wear and contamination. This signal processing may require special filters to determine amplitudes or frequencies of vibrations, to determine derivated or integrated quantities, or state variable observers. Model-based and Adaptive Control Systems The information processing is, at least in the lower levels, performed by simple algorithms or software-modules under real-time conditions. These algorithms contain free adjustable parameters, which have to be adapted to the static and dynamic behavior of the process. In contrast to manual tuning by trial and error, the use of mathematical models allows precise and fast automatic adaptation.
图2.5先进的智能自动系统控制的多层次，知识库，推理机制，和接口。为维
护甚至冗余行动，经济优化，协调。有时上级的任务归纳为―过程管理。‖特别处理描述
的方法是不可测数量从数学的过程模型重建部分适用的信号。通过这种方式，它是可以控制阻尼比，材料和热应力，滑，或监督内元件的电阻，电容，温度，或磨损和污染参数数量。这个信号处理，可能需要特殊的过滤器，以确定振动的振幅或频率，以确定衍生化或综合的数量，或状态变量的观察员。基于模型的自适应控制系统的信息处理，至少在较低的水平，简单的算法或软件模块实时条件下进行。这些算法包含免费的可调参数，它必须适应过程的静态和动态的行为。在对比试验和错误的手动调谐，运用数学模型允许精确和快速的自动适应。
The mathematical models can be obtained by identification and
parameter estimation, which use the measured and sampled input and output signals. These methods are not restricted to linear models, but also allow for several classes of nonlinear systems. If the parameter estimation methods are combined with appropriate control algorithm design methods, adaptive control systems result. They can be used for permanent precise controller tuning or only for commissioning [20]. .2002 CRC Press LLC
可以通过识别和参数估计，它使用的测量和采样的输入和输出信号的数学模型。
这些方法不仅限于线性模型，但也让几类非线性系统。如果参数估计方法相结合，与相应的控制算法的设计方法，自适应控制系统的结果。它们可以用于永久精确的控制器调整，或只为调试[20]。 2002的CRC出版社有限责任公司
FIGURE 2.6 Scheme for a model-based fault detection.
Supervision and Fault Detection With an increasing number of automatic functions (autonomy), including electronic components, sensors and actuators, increasing complexity, and increasing demands on reliability and safety, an integrated supervision with fault diagnosis becomes more and more important. This is a significant natural feature of an intelligent mechatronic system. Figure 2.6 shows a process influenced by faults. These faults indicate unpermitted deviations from normal states and can be generated either externally or internally. External faults can be caused by the power supply, contamination, or collision, internal faults by wear, missing lubrication, or actuator or sensor faults. The classical way for fault
detection is the limit value checking of some few measurable variables. However, incipient and intermittant faults can not usually be detected, and an in-depth fault diagnosis is not possible by this simple approach. Model-based fault detection and diagnosis methods were developed in recent years, allowing for early detection of small faults with normally measured signals, also in closed loops [21]. Based on measured input signals, U(t), and output signals, Y(t), and process models, features are generated by parameter estimation, state and output observers,and parity equations, as seen in Fig. 2.6.
图2.6基于模型的故障检测计划。自动功能越来越多（自治），包括电子元件，
传感器和执行器，日益复杂化，和日益增长的需求，可靠性和安全性，故障诊断与综合监督的监督和故障检测变得越来越重要。这是一个显著的智能机电一体化系统的自然特征。图2.6显示了断层影响的一个过程。这些错误表明从正常状态未经许可的偏差，可以产生外部或内部。外部故障可能是由电源，污染，或碰撞，磨损的内部故障，缺少润滑，或执行器或传感器故障。故障检测的经典方法是限制少数一些可测量的变量的值检查。然而，起动和intermittant故障不能通常被检测，并进行了深入的故障诊断是不是这种简单的方法可能。基于模型的故障检测和诊断方法是近年发展起来的，与通常的测量信号的小故障的早期检测，也是在封闭循环[21]。根据测得的输入信号，U（t）和输出信号，Y（T），和流程模型，参数估计，状态和输出观察员生成的特点是，和奇偶方程在图。2.6。
These residuals are then compared with the residuals for normal
behavior and with change detection methods analytical symptoms are obtained. Then, a fault diagnosis is performed via methods of classification or reasoning. For further details see [22,23]. A considerable advantage is if the same process model can be used for both the (adaptive) controller design and the fault detection. In general, continuous time models are preferred if fault detection is based on parameter estimation or parity equations. For fault detection with state estimation or parity equations, discrete-time models can be used. Advanced supervision and fault diagnosis is a basis for improving reliability and safety, state dependent maintenance, triggering of redundancies, and reconfiguration. Intelligent Systems (Basic Tasks) The information processing within mechatronic systems may range between simple control functions and intelligent control. Various definitions of intelligent control systems do exist, see [24–30]. An intelligent control system may be organized as an online expert system, according to Fig. 2.5, and comprises . multi-control functions (executive functions), . a knowledge base, . inference mechanisms, and. communication interfaces. .2002 CRC Press LLC
这些残差是正常行为的残差与分析症状得到的变化检测方法相比。然后，故障
诊断是通过分类或推理方法。更多详情请参见[22,23]。相当大的优势是，如果同样的过程模型，可用于（自适应）控制器的设计和故障检测。一般情况下，连续时间模型是首选，如果故障检测参数估计或奇偶方程的基础上。故障检测与状态估计或奇偶方程，离散时间模型都可以使用。先进的监督和故障诊断是提高可靠性和安全，依赖国家维护，引发裁员，和重新配置的基础。智能系统（基本任务）在机电一体化系统的信息处理的