Estimation and Control of Robotic Radiation-Based Processes

This dissertation presents a closed-loop control and state estimation framework for a class of distributed-parameter processes employing a moving radiant actuator. These radiation-based processes have the potential to significantly reduce the energy consumption and environmental impact of traditional industrial processes. Successful implementation of these approaches in large-scale applications requires precise control systems. This dissertation provides a comprehensive framework for: 1) integration of trajectory generation and feedback control, 2) online distributed state and parameter estimation, and 3) optimal coordination of multiple manipulated variables, so as to achieve elaborate control of these radiation-based processes for improved process quality and energy efficiency. The developed framework addresses important issues for estimation and control of processes employing a moving radiant actuator from both practical and theoretical aspects. For practical systems, an integrated motion and process control approach is first developed to compensate for disturbances by adjusting either the radiant power of the actuator or the speed of the robot end effector based on available process measurements, such as temperature distribution. The control problem is then generalized by using a 1D scanning formulation that describes common characteristics of typical radiant source actuated processes. Based on this 1D scanning formulation, a distributed state and parameter estimation scheme that incorporates a dual extended Kalman filter (DEKF) approach is developed to provide real-time process estimation. In this estimation scheme, an activating policy accompanying the moving actuator is applied in order to reduce the computational cost and compensate for observability changes caused by the actuator\u27s movement. To achieve further improvements in process quality, a static optimization and a rule-based feedback control strategy are used to coordinate multiple manipulated variables in open-loop and closed-loop manners. Finally, a distributed model predictive control (MPC) framework is developed to integrate process optimization and closed-loop coordination of manipulated variables. Simulation studies conducted on a robotic ultraviolet (UV) paint curing process show that the developed estimation and control framework for radiant source actuated processes provide improved process quality and energy efficiency by adaptively compensating for disturbances and optimally coordinating multiple manipulated variables

An Adaptive Overcurrent Coordination Scheme to Improve Relay Sensitivity and Overcome Drawbacks due to Distributed Generation in Smart Grids

Distributed Generation (DG) brought new challenges for protection engineers since standard relay settings of traditional system may no longer function properly under increasing presence of DG. The extreme case is coordination loss between primary and backup relays. The directional overcurrent relay (DOCR) which is the most implemented protective device in the electrical network also suffers performance degradation in presence of DG. Therefore, this paper proposes the mitigation of DG impact on DOCR coordination employing adaptive protection scheme (APS) using differential evolution algorithm (DE) while improving overall sensitivity of relays . The impacts of DG prior and after the application of APS are presented based on interconnected 6 bus and IEEE 14 bus system. As a consequence, general sensitivity improvement and mitigation scheme is proposed

Cooperation in Industrial Systems

ARCHON is an ongoing ESPRIT II project (P-2256) which is approximately half way through its five year duration. It is concerned with defining and applying techniques from the area of Distributed Artificial Intelligence to the development of real-size industrial applications. Such techniques enable multiple problem solvers (e.g. expert systems, databases and conventional numerical software systems) to communicate and cooperate with each other to improve both their individual problem solving behavior and the behavior of the community as a whole. This paper outlines the niche of ARCHON in the Distributed AI world and provides an overview of the philosophy and architecture of our approach the essence of which is to be both general (applicable to the domain of industrial process control) and powerful enough to handle real-world problems

Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl

Blockchain Solutions for Multi-Agent Robotic Systems: Related Work and Open Questions

The possibilities of decentralization and immutability make blockchain probably one of the most breakthrough and promising technological innovations in recent years. This paper presents an overview, analysis, and classification of possible blockchain solutions for practical tasks facing multi-agent robotic systems. The paper discusses blockchain-based applications that demonstrate how distributed ledger can be used to extend the existing number of research platforms and libraries for multi-agent robotic systems.Comment: 5 pages, FRUCT-2019 conference pape

Sliding Mode Reference Coordination of Constrained Feedback Systems

[EN] This paper addresses the problem of coordinating dynamical systems with possibly different dynamics (e.g., linear and nonlinear, different orders, constraints, etc.) to achieve some desired collective behavior under the constraints and capabilities of each system. To this end, we develop a new methodology based on reference conditioning techniques using geometric set invariance and sliding mode control: the sliding mode reference coordination (SMRCoord). The main idea is to coordinate the systems references. Starting from a general framework, we propose two approaches: a local one through direct interactions between the different systems by sharing and conditioning their own references and a global centralized one, where a central node makes decisions using information coming from the systems references. In particular, in this work we focus in implementation on multivariable systems like unmanned aerial vehicles (UAVs) and robustness to external perturbations. To show the applicability of the approach, the problem of coordinating UAVs with input constraints is addressed as a particular case of multivariable reference coordination with both global and local configuration.Research in this area is partially supported by Argentine government (ANPCyT PICT 2011-0888 and CONICET PIP 112-2011-00361), Spanish government (FEDER-CICYT DPI2011-28112-C04-01), and Universitat Politecnica de Valencia (Grant FPI/2009-21)Vignoni, A.; Garelli, F.; Picó, J. (2013). Sliding Mode Reference Coordination of Constrained Feedback Systems. Mathematical Problems in Engineering. 2013:1-11. https://doi.org/10.1155/2013/764348S1112013Information consensus in multivehicle cooperative control. (2007). IEEE Control Systems, 27(2), 71-82. doi:10.1109/mcs.2007.338264Cao, Y., Yu, W., Ren, W., & Chen, G. (2013). An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination. 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