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The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ..., new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The water and wastewater industry has undergone many changes in recent years. Of particular importance has been a renewed emphasis on improving resource management with tighter regulatory controls setting new targets on pricing, industry efficiency and loss reduction for both water and wastewater with more stringent environmental discharge conditions for wastewater. Meantime, the demand for water and wastewater services grows as the population increases and wishes for improved living conditions involving, among other items, domestic appliances that use water. Consequently, the installed infrastructure of the industry has to be continuously upgraded and extended, and employed more effectively to accommodate the new demands, both in throughput and in meeting the new regulatory conditions. Investment in fixed infrastructure is capital-intensive and slow to come on-stream. One outcome of these changes and demands is that the industry is examining the potential benefits of, and in many cases using, more advanced control systems.
In the research Model Predictive Control on Open Water Systems', the relatively new control methodology Model Predictive Control is configured for application of water quantity control on open water systems, especially on irrigation canals and large drainage systems. The methodology applies an internal model of the open water system, by which optimal control actions are calculated over a prediction horizon. As internal model, two simplified models are used, the Integrator Delay model and the Saint Venant model. Kalman filtering is applied to initialize the internal models. The optimization uses an objective function in which conflicting objectives can be weighed. In most of the cases, these conflicting objectives are keeping the water levels at different locations in the water system within a range around setpoint and executing this by using as little control effort or energy as possible.
This book meets head-on the difficulty of making practical use of new systems theory, presenting a selection of varied applications together with relevant theory. It shows how workable identification and control solutions can be derived by adapting and extrapolating from the theory. Each chapter has a common structure: a brief presentation of theory; the description of a particular application; experimental results; and a section highlighting, explaining and laying out solutions to the discrepancy between the theoretical and the practical.
Urban drainage systems (UDSs) are complex large-scale systems that carry stormwater and wastewater throughout urban areas. During heavy rain scenarios, UDSs are not able to handle the amount of extra water that enters the network and flooding occurs. Usually, this might happen because the network is not being used efficiently, i.e., some structures remain underused while many others are overused. This thesis proposes a control methology based on mean field game theory and model predictive control that aims to efficiently use the existing network elements in order to minimize overflows and properly manage the water resource. The proposed controller is tested on a UDS located in the city of Barcelona, Spain, and is compared with a centralized MPC achieving similar results in terms of flooding minimization and wastewater treatement plant usage, but only using local information on non-centralized controllers and using less computation times.
This book aims to contribute to the conceptual and practical knowledge pools in order to improve the research and practice on the sustainable development of smart cities by bringing an informed understanding of the subject to scholars, policymakers, and practitioners. This book seeks articles offering insights into the sustainable development of smart cities by providing in-depth conceptual analyses and detailed case study descriptions and empirical investigations. This way, the book will form a repository of relevant information, material, and knowledge to support research, policymaking, practice, and transferability of experiences to address aforementioned challenges. The scope of the book includes the following broad areas, with a particular focus on the approaches, advances, and applications in the sustainable development of smart cities: • Theoretical underpinnings and analytical and policy frameworks; • Methodological approaches for the evaluation of smart and sustainable cities; • Technological developments in the techno-enviro nexus; • Global best practice smart city case investigations and reports; • Geo-design and applications concerning desired urban outcomes; • Prospects, implications, and impacts concerning the future of smart and sustainable cities.
This book reports on the implementation of evolutionary-game theory in the design of distributed optimization-based controllers. First, it discusses how the classical population-game approach can contribute to and complement the design of optimization-based controllers. It shows how the features of this approach can be exploited to extend their capabilities in the solution of distributed optimization problems, and examines density games in order to consider multiple coupled constraints and preserve the non-centralized information requirements. Furthermore, it establishes a close relationship between the possible interactions among agents in a population with constrained information sharing among different local controllers. It also discusses coalitional games, focusing on the Shapley power index and proposes an alternative method of computing the latter, which reduces computational time, as well as a different way of finding it using distributed communication structures. All the proposed strategies are then tested on various control problems, such as those related to the Barcelona water supply network, multiple continuous stirred tank reactors, various unmanned aerial vehicle systems, and a water distribution system. This thesis, examined at the Universitat Politècnica de Catalunya and Universidad de los Andes in 2017, received the award for best thesis in control from the control group of the Spanish Committee of Automatic Control (CEA) in the same year.