Distributed and Decentralized Kalman Filtering for Cascaded Fractional Order Systems

This paper presents a distributed Kalman filter algorithm for cascaded systems of fractional order. Certain conditions are introduced under which a division of a fractional system into cascaded subsystems is possible. A functional distribution of a large scale system and of the state estimation algorithm leads to smaller and scalable nodes with reduced memory and computational effort. Since each subsystem performs its calculations locally, a central processing node is not needed. All data which are required by subsequent nodes are communicated to them unidirectionally. Also a comparison between the Fractional Kalman Filter (FKF) and the Cascaded Fractional Kalman Filter (CFKF) is given by an example

Towards continuous biomanufacturing a computational approach for the intensification of monoclonal antibody production

Current industrial trends encourage the development of sustainable, environmentally friendly processes with reduced energy and raw material consumption. Meanwhile, the increasing market demand as well as the tight regulations in product quality, necessitate efficient operating procedures that guarantee products of high purity. In this direction, process intensification via continuous operation paves the way for the development of novel, eco-friendly processes, characterized by higher productivity compared to batch (Nicoud, 2014). The shift towards continuous operation could advance the market of high value biologics, such as monoclonal antibodies (mAbs), as it would lead to shorter production times, decreased costs, as well as significantly less energy consumption (Konstantinov and Cooney, 2015, Xenopoulos, 2015). In particular, mAb production comprises two main steps: the culturing of the cells (upstream) and the purification of the targeted product (downstream). Both processes are highly complex and their performance depends on various parameters. In particular, the efficiency of the upstream depends highly on cell growth and the longevity of the culture, while product quality can be jeopardized in case the culture is not terminated timely. Similarly, downstream processing, whose main step is the chromatographic separation, relies highly on the setup configuration, as well as on the composition of the upstream mixture. Therefore, it is necessary to understand and optimize both processes prior to their integration. In this direction, the design of intelligent computational tools becomes eminent. Such tools can form a solid basis for the: (i) execution of cost-free comparisons of various operating strategies, (ii) design of optimal operation profiles and (iii) development of advanced, intelligent control systems that can maintain the process under optimal operation, rejecting disturbances. In this context, this work focuses on the development of advanced computational tools for the improvement of the performance of: (a) chromatographic separation processes and (b) cell culture systems, following the systematic PAROC framework and software platform (Pistikopoulos et al., 2015). In particular we develop model-based controllers for single- and multi-column chromatographic setups based on the operating principles of an industrially relevant separation process. The presented strategies are immunized against variations in the feed stream and can successfully compensate for time delays caused due to the column residence time. Issues regarding the points of integration in multi-column systems are also discussed. Moreover, we design and test in silico model-based control strategies for a cell culture system, aiming to increase the culture productivity and drive the system towards continuous operation. Challenges and potential solutions for the seamless integration of the examined bioprocess are also investigated at the end of this thesis.Open Acces

Coordination Strategies for Human Supervisory Control of Robotic Teams

Autonomous mobile sensor teams are crucial to many civilian and military applications. These robotic teams often operate within a larger supervisory system, involving human operators who oversee the mission and analyze sensory data. Here, both the human and the robotic system sub-components, as well as interactions between them, must be carefully considered in designing effective mission coordination strategies. This dissertation explores a series of representative sub-problems relating to the analysis and coordination of both mobile sensors and human operators within supervisory systems. The content herein is presented in three parts: Part I focuses on coordinating operator behavior independently (operator-focused methods), Part II focuses on coordinating mobile-sensor behavior independently (sensor-focused methods), and Part III focuses on jointly coordinating both operator and mobile sensor behavior (joint methods). The content herein is primarily motivated by a particular application in which Unmanned Aerial Vehicles collect visual imagery to be analyzed by a remotely located operator, although many of the results apply to any system of similar architecture. Specifically, with regard to operator-focused methods, Chapter 2 illustrates how physiological sensing, namely eye tracking, may provide aid in modeling operator behavior and assessing the usability of user interfaces. The results of a pilot usability study in which human observers interact with a supervisory control interface are presented, and eye-tracking data is correlated with various usability metrics. Chapter 3 develops robust scheduling algorithms for determining the ordering in which operators should process sensory tasks to both boost performance and decrease variance. A scenario-based, Mixed-Integer Linear Program (MILP) framework is presented, and is assessed in a series of numerical studies. With regard to sensor-focused methods, Chapters 4 and 5 consider two types of supervisory surveillance missions:Chapter 4 develops a cloud-based coverage strategy for persistent surveillance of planar regions. The scheme operates in a dynamic environment, only requiring sporadic, unplanned data exchanges between a central cloud and the sensors in the field. The framework is shown to provide collision avoidance and, in certain cases, produce convergence to a Pareto-optimal coverage configuration. In chapter 5, a heuristic routing scheme is discussed to produce Dubins tours for persistent surveillance of discrete targets, each with associated visibility and dwell-time constraints. Under some assumptions, the problem is posed as a constrained optimization that seeks a minimum-length tour, while simultaneously constraining the time required to reach the first target. A sampling-based scheme is used to approximate solutions to the constrained optimization. This approach is also shown to have desirable resolution completeness properties.Finally, Chapter 6 explores joint methods for coordinating both operator and sensor behavior in the context of a discrete surveillance mission (similar to that of Chapter 5), in which UAVs collect imagery of static targets to be analyzed by the human operator.In particular, a method is proposed to simultaneously construct UAV routes and operator schedules, with the goal of maintaining the operator's task load within a high-performance regime and preventing unnecessary UAV loitering. The full routing/scheduling problem is posed as a mixed-integer (non-linear) program, which can be equivalently represented as a MILP through the addition of auxiliary variables. For scalability, a MILP-based receding-horizon method is proposed to incrementally construct suboptimal solutions to the full optimization problem, which can be extended using a scenario-based approach (similar to that of Chapter 3) to incorporate robustness to operator uncertainty

Exploring Controls Education: A Re-Configurable Ball and Plate Platform Kit - Expanded Version

The kit is an expanded version of: Bay, C.J. and Rasmussen, B.P., 2016, "Exploring Controls Education: A Re-Configurable Ball and Plate Platform Kit", American Control Conference (ACC) 2016, Boston, MA, USA. It includes a manual, the software code needed to operate the kit, .stl files for the 3-D printed parts, and a supply list.This kit contains materials for building a re-configurable ball-plate balancer that can be 3-D printed and used in controls education