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首页> 外文学位 >OPTIMAL ESTIMATION ALGORITHMS FOR SYSTEMS WITH MULTIPLE TIME MODES AND DELAYED MEASUREMENTS.
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OPTIMAL ESTIMATION ALGORITHMS FOR SYSTEMS WITH MULTIPLE TIME MODES AND DELAYED MEASUREMENTS.

机译：具有多种时间模式和延迟测量的系统的最佳估计算法。

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When controlling a process, the state of the system must be known before control action can be taken. Using variational calculus, state estimators were derived for systems whose parameters are distributed in space as well as time. These distributed-parameter state estimation algorithms were studied on systems which displayed multiple dynamic time modes in the states and time delays in the measurements. These traditionally overlooked phenomena can cause estimators to become computationally intensive and slow to respond to process dynamics.; Singular perturbation theory was used to simplify the set of complex stiff estimation equations which arises when multiple time modes are present in a dynamic system. The singular perturbation technique allows one large Kalman-type estimator to be broken down into a set of smaller estimators. These smaller estimators were able to predict the process states well in simulations. Only when very poor initial conditions were used was the difference between the complete estimator and the singular perturbation estimators noticed.; Two new estimation algorithms were developed for systems with measurement delays; one for systems with pure time-delays and the other for systems with dynamic delays. The first of these algorithms was able to reduce the measurement errors incurred by pure time-delayed measurements. When dynamic measurements were present, a transformation of the system helped to minimize the estimated error. These techniques were studied via simulations on a continuous stirred slurry tank reactor, a heated bar and a gas phase tubular reactor.; Finally, all the new techniques were combined and tested on a real-time styrene pilot plant system. This system exhibits multiple dynamic time modes in the reactor states (temperature, concentration and activity), along with dynamic and pure time delays in the measuring devices used. The process was monitored, controlled, and estimated using a distributed-computer network that included three separate computers. The combined estimators were able to estimate the measurable reactor states (temperature and concentration), along with the unmeasurable reactor catalyst activity. Using only a small number of measured temperatures (2) and the outlet reactor concentrations, the estimators correctly predicted these states to within 4% of their actual values. The catalyst activity was studied for various steam-to-oil ratios (SOR) and inlet reactor temperatures.
机译：在控制过程时，必须先了解系统的状态，然后才能采取控制措施。使用变分演算，为参数在空间和时间中分布的系统得出状态估计器。这些分布参数状态估计算法是在显示状态中多个动态时间模式以及测量中的时间延迟的系统上进行研究的。这些传统上被忽视的现象可能导致估计器变得计算量大，并且对过程动态的响应速度变慢。奇异摄动理论用于简化一组复杂的刚性估计方程，该方程在动态系统中存在多个时间模式时会出现。奇异摄动技术允许将一个大的Kalman型估计器分解为一组较小的估计器。这些较小的估计器能够在模拟中很好地预测过程状态。仅当使用非常差的初始条件时，才注意到完整估计量与奇异摄动估计量之间的差异。针对具有测量延迟的系统，开发了两种新的估计算法：一种用于纯延时系统，另一种用于动态延时系统。这些算法中的第一个能够减少纯时间延迟测量引起的测量误差。当进行动态测量时，系统的转换有助于最小化估计的误差。通过在连续搅拌淤浆罐反应器，加热棒和气相管式反应器上的模拟研究了这些技术。最后，将所有新技术组合在一起，并在实时苯乙烯中试装置系统上进行了测试。该系统在反应器状态（温度，浓度和活度）中表现出多种动态时间模式，并且在所用测量装置中具有动态和纯时间延迟。使用包括三台独立计算机的分布式计算机网络对过程进行监视，控制和估算。组合的估计器能够估计可测量的反应器状态（温度和浓度）以及不可测量的反应器催化剂活性。估计器仅使用少量的测得温度（2）和出口反应堆浓度，就能正确地将这些状态预测为实际值的4％以内。研究了各种蒸汽/油比（SOR）和入口反应器温度下的催化剂活性。

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