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The next stage for robotics development is to introduce autonomy and cooperation with human agents in tasks that require high levels of precision and/or that exert considerable physical strain. To guarantee the highest possible safety standards, the best approach is to devise a deterministic automaton that performs identically for each operation. Clearly, such approach inevitably fails to adapt itself to changing environments or different human companions. In a surgical scenario, the highest variability happens for the timing of different actions performed within the same phases. This paper presents a cognitive control architecture that uses a multi-modal neural network trained on a cooperative task performed by human surgeons and produces an action segmentation that provides the required timing for actions while maintaining full phase execution control via a deterministic Supervisory Controller and full execution safety by a velocity-constrained Model-Predictive Controller.

In this paper we propose a new methodology to model surgical procedures that is specifically tailored to semi-autonomous robotic surgery. We propose to use a restricted version of statecharts to merge the bottom-up approach, based on data-driven techniques (e.g., machine learning), with the top-down approach based on knowledge representation techniques. We consider medical knowledge about the procedure and sensing of the environment in two concurrent regions of the statecharts to facilitate re-usability and adaptability of the modules. Our approach allows producing a well defined procedural model exploiting the hierarchy capability of the statecharts, while machine learning modules act as soft sensors to trigger state transitions. Integrating data driven and prior knowledge techniques provides a robust, modular, flexible and re-configurable methodology to define a surgical procedure which is comprehensible by both humans and machines. We validate our approach on the three surgical phases of a Robot-Assisted Radical Prostatectomy (RARP) that directly involve the assistant surgeon: bladder mobilization, bladder neck transection, and vesicourethral anastomosis, all performed on synthetic manikins.

In reconfigurable manufacturing systems (RMSs), the architecture of a system can be modified during its operation. This reconfiguration can be caused by many motivations: processing rework and failures, adding new products, adding new machines, etc. In RMSs, sharing of resources may lead to deadlocks, and some operations can therefore remain incomplete. The objective of this article is to develop a novel two-step solution for quick and accurate reconfiguration of supervisory controllers for deadlock control in RMSs with dynamic changes. In the first step, the net rewriting system (NRS) is used to design a reconfigurable Petri net model under dynamic configurations. The obtained model guarantees boundedness behavioral property but may lose the other properties of a Petri net model (i.e., liveness and reversibility). The second step develops an automatic deadlock prevention policy for the reconfigurable Petri net using the siphon control method based on a place invariant to solve the deadlock problem with dynamic structure changes in RMSs and achieve liveness and reversibility behavioral properties for the system. The proposed approach is tested using examples in the literature and the results highlight the ability of the automatic deadlock prevention policy to adapt to RMSs configuration changes.

Made available in DSpace on 2018-11-29T20:09:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-07-10 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) This study presents a synergistic operation between a battery energy storage (BES) and a photovoltaic generator (PVG) system to assist management of microgrids. The BES and the PVG work synergistically in a virtual single agent. The single agent consists of a group containing the BES, the PVG, and the loads in a feeder. The single agent results in a virtual distributed energy resource, capable to obey orders imposed by the supervisory controller (SC). The loads within the single agent seem not existent anymore to the SC, but they kept fed all the time. This is convenient to the microgrid in terms of management because the SC interacts with only one element and not more with all elements within the single agent. The synergistic operation arises when the SC demands orders to the single agent. To make the single agent obey the SC, the BES and PVG need to decide their operation mode, working synergistically for each other. The conservative power theory is applied to quantify active power, reactive energy, and harmonic currents in points of interest along the microgrid. The efficacy of the synergistic operation is verified through experimental results. Univ Fed Santa Catarina, Dept Engn, Rua Pomerode 710, BR-89065300 Blumenau, SC, Brazil Sao Paulo State Univ, Inst Sci & Technol, Ave Tres Marco 511, BR-18087180 Sorocaba, SP, Brazil Univ Estadual Campinas, Sch Elect & Comp Engn, Ave Albert Einstein 400, BR-13083852 Campinas, SP, Brazil Colorado Sch Mines, Dept Elect Engn & Comp Sci, 1610 Illinois St,8400, Golden, CO 80401 USA Sao Paulo State Univ, Inst Sci & Technol, Ave Tres Marco 511, BR-18087180 Sorocaba, SP, Brazil FAPESP: 2012/23914-5 FAPESP: 2017/22629-9 FAPESP: 2016/08645-9 CNPq: 421281/2016-2 CNPq: 302257/2015-2

Battery energy storage systems are a key factor for enabling a continuous increase of the fraction of photovoltaics in the Swedish electricity grid. One big challenge is to utilise all potential services of such a storage system. The aim of this study was to improve the supervisory controller for an existing battery storage and photovoltaic solution marketed by the Swedish company Ferroamp AB. This has been done by developing a combined peak reduction and time-of-use bill management algorithm, together with a simulation and evaluation software for optimisation of algorithm parameters. The algorithms and tools were evaluated using an installation made by Ferroamp AB and Vattenfall Eldistribution AB as a case study. Sensitivity analyses has been performed on economic parameters and length of the algorithm training data set. Improvement of economic profit, in this case study, were 300 % compared to the currently used algorithm and 32 % compared to a conventional threshold peak reduction algorithm. Despite this improvement, the battery energy storage system is shown to be non-profitable, with the economic profit only covering 36 % of the investment costs, not taking interest rate into account. Like in many other studies, power storage was found more profitable than energy storage. An increase of the grid power tariff and the grid energy fee of 30 % to 40 % is found to make the system viable. One interesting finding is that by using the proposed optimal algorithm, 55 % of the cycle life of the battery storage is still accessible for other services when considering 10 years of economic depreciation time for the system.

This paper presents a methodology to design and utilize a supervisory controller for networked power converters in residential applications. Wireless networks have been interfaced to multiple power factor correction (PFC) converters which are proposed to support reactive power. Unregulated reactive power support from PFC converters could cause reactive power deficiency and instability. Therefore, a supervisory controller is necessary to govern the operation of PFC converters. WiFi and WirelessHART networks have been used to implement the supervisory controller. Different nodes of the power network are connected by wireless communication links to the supervisory controller. Asynchronous communication links latency and uncertain states affect the control and response of the PFC converters. To overcome these issues, the supervisory controller design method has been proposed based on the system identification and the Ziegler-Nichols rule. The proposed supervisory controller has been validated by using a hardware-in-the-loop (HIL) test bed. The HIL testbed consisted of an OP4510 simulator, a server computer, Texas Instrument-Digital Signal Controllers (TI-DSCs), WiFi and WirelessHART modules. Experimental results show that the proposed supervisory controller can help to support and govern reactive power flow in a residential power network. The proposed method of controller design will be useful for different small-scale power and wireless network integration.

Using the CIF 3 toolset, we illustrate the general idea of controller synthesis for product line engineering for a prototypical example of a family of coffee machines. The challenge is to integrate a number of given components into a family of products such that the resulting behaviour is guaranteed to respect an attributed feature model as well as additional behavioural requirements. The proposed correctness-by-construction approach incrementally restricts the composed behaviour by subsequently incorporating feature constraints, attribute constraints and temporal constraints. The procedure as presented focusses on synthesis, but leaves ample opportunity to handle e.g. uncontrollable behaviour, dynamic reconfiguration, and product- and family-based analysis.

This paper deals with an implementation of a new matrix-based supervisory controller of flexible manufacturing system (FMS). A design method is applied to the laboratory setup of a finite-buffer multiple reentrant flowline FMS which contains one 5-degree of freedom (DOF) robot, few transporters, pistons and other elements (sensors, programable logic controller and personal computers). Control of the FMS is based on a matrix model approach which significantly reduces a computational effort and simplifies conversion of dispatching rules to the software program. The results obtained during experiments have confirmed effectiveness of the matrix-based FMS controller.

WOS: 000248954500013, Colored Petri net model which is a model of discrete event systems is considered in this work. A supervisory controller which enforces reversibility and liveness simultaneously is presented. Furthermore, the algorithms, written by pseudo-code, are presented for the supervisory controller design. A program is developed to implement these algorithms.

WOS: 000241648900004, Discrete event systems which are modeled by automata are considered in this work. The algorithms which determine the set of deadlock states and the reversible set, and design the deadlock avoidance controller and the reversibility enforcement controller are introduced for these systems. Moreover, a program is developed to implement these algorithms.

International audience; This paper presents a method for implementing a controller synthesized by PN-based SCT theory. Despite the great acceptance of SCT in controller design, there are problems with its practical implementation. Sequential Function Chart, as an international standard programming language, is used for implementing PN-based controllers. One problem in the implementation step is the occurrence of simultaneous events in mutually exclusive transitions. In SFC standards, it is possible to define a constant priority (e.g. left to right). A method for developing dynamic priority is presented in this research. If two users have requests for a common resource simultaneously, priority goes to the one that did not use the resource in the earlier turn. Existence of non-safe places in PN model is another problem in the implementation process. In this paper an alternative for this problem is also presented. Therefore, if the controller model becomes non-safe, it could implement using SFC. Finally the idea is demonstrated using an example.