Thermal enrichment of coldwater streams by heated stormwater in summer months is often overlooked and even exacerbated by traditional management practices that typically account for flow moderation and pollutant removal only. Initiated in 1999, this study evaluated and identified innovative and traditional approaches to moderate this temperature impact by monitoring and analyzing the hydrologic and thermal regimes of an urban stormwater treatment system consisting of two traditional wet detention ponds and an enhanced natural wetland. Data analysis clearly shows temperature increases in the open detention ponds and the ability of the wetland to mitigate this thermal enrichment. Event-based thermal loading and temperature regime analysis indicated flow reduction via infiltration and effective vegetative cover in the wetland were the primary mechanisms for mitigating stormwater thermal enrichment. Using the concept of temperature equivalent, we also established the locations and strength of thermal enrichment areas. A heat transfer model was developed to simulate runoff temperature. Results indicated that rainfall characteristics, temperature difference between rainfall and the ground surface, and the runoff flow depth were the most important factors affecting runoff temperature.
This monograph provides the reader with a systematic treatment of robust filter design, a key issue in systems, control and signal processing, because of the fact that the inevitable presence of uncertainty in system and signal models often degrades the filtering performance and may even cause instability. The methods described are therefore not subject to the rigorous assumptions of traditional Kalman filtering. The monograph is concerned with robust filtering for various dynamical systems with parametric uncertainties and focuses on parameter-dependent approaches to filter design. Classical filtering schemes, like H2 filtering and HÂ¥ filtering, are addressed and emerging issues such as robust filtering with constraints on communication channels and signal frequency characteristics are discussed. The text features:
Â· design approaches to robust filters arranged according to varying complexity level and emphasizing robust filtering in the parameter-dependent framework for the first time;
Â· guidance on the use of special realistic phenomena or factors to describe problems more accurately and to improve filtering performance;
Â· a unified linear matrix inequality formulation of design approaches for easy and effective filter design;
Â· demonstration of the techniques of matrix decoupling technique, the generalized Kalman?Yakubovich?Popov lemma, the free weighting matrix technique and the delay modelling approach, in robust filtering;
Â· numerous easy-to-follow simulation examples, graphical and tabular illustrations to help the reader understand the filter design approaches developed; and
Â· an account of emerging issues on robust filtering for research to inspire future investigation.
Robust Filtering for Uncertain Systems will be of interest to academic researchers specializing in linear, robust and optimal control and estimation and to practitioners working in tracking and network control or signal filtering, detection and estimation. Graduate students learning control and systems theory, signal processing or applied mathematics will also find the book to be a valuable resource.
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