Dynamic Combinatorial Libraries: From Exploring Molecular Recognition to Systems Chemistry

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

Increasingly automated procedure acquisition in dynamic systems

Procedures are widely used by operators for controlling complex dynamic systems. Currently, most development of such procedures is done manually, consuming a large amount of paper, time, and manpower in the process. While automated knowledge acquisition is an active field of research, not much attention has been paid to the problem of computer-assisted acquisition and refinement of complex procedures for dynamic systems. The Procedure Acquisition for Reactive Control Assistant (PARC), which is designed to assist users in more systematically and automatically encoding and refining complex procedures. PARC is able to elicit knowledge interactively from the user during operation of the dynamic system. We categorize procedure refinement into two stages: diagnosis - diagnose the failure and choose a repair - and repair - plan and perform the repair. The basic approach taken in PARC is to assist the user in all steps of this process by providing increased levels of assistance with layered tools. We illustrate the operation of PARC in refining procedures for the control of a robot arm

Advanced control systems research at UPC Terrassa Campus

Advanced Control Systems (SAC) is a multidiscip linary research group involving UPC professors and Spanish National Research Council (CSIC) researchers, focused on the wide subject of control and supervision of dynamic systems. The group uses theory of signal/systems tools, modelling, simulation and optimization in order to face real problems of systems and automated processes, specifically in the next subjects: Optimal/predictive control of large scale systems (mainly related with water cycle) ; Data validation ; Fault diagnosis ; Fault tolerant control system design ; Dynamic system monitoring and maintenance aiding ; Advanced control systems design, mainly focused on UAV control. The activities of research of the SAC group are framed in what today is known as TIC technologies, and their main objective is to develop tools that allow to improve the functioning of systems (aerogenerators, cars, airplanes, UAVs, etc.) and complex technological processes, (networks of water distribution, management of water quality, etc). It is understood as an improvement from the fact of achieving certain benefits of operation, until the planning of tasks in order to reduce costs or improving environmental aspectsPeer Reviewe

Interoperability between a dynamic reliability modeling and a Systems Engineering process – Principles and Case Study

International audienceIndustrial systems are often large, and complex, in terms of structure, dynamic interactions between subsystems and components, dynamic operational environment, ageing, etc. The dynamic reliability approach is a convenient framework to model the behavior of such systems. However, there is a price to pay, e.g. in terms of amount of data, size of state graphs, volume of reliability calculations, and combination of various engineering activities. A sound Systems Engineering process, benefiting from the improvement of most recent tools, may be a fruitful approach to decrease these difficulties. Although feasibility demonstrations have been done for conventional, static, approaches of dependability, interoperability between dynamic reliability modeling and Systems Engineering has not the same maturity level. The article explains how, on the basis of Systems Engineering (SE) process definitions, a Meta-model defines a framework for integrating the safety into SE processes. It supports a "hub automaton", that is the key element for interoperability with the tools and activities required for a dynamic reliability assessment. The case study is the dynamic assessment of availability of a feed-water control system in a power plant steam generator, presented in previous articles

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions

Dynamic Combinatorial Libraries: From Exploring Molecular Recognition to Systems Chemistry

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines

Two-input two-output port model for mechanical systems

This paper proposes a double input output port transfer to model complex mechanical systems composed of several sub-systems. The sub-structure decomposition is revisited from the control designer point of view. The objective is to develop modelling tools to be used for mechanical/control co-design of large space flexible structures involving various substructures (boom, links of robotic arm,...) connected one to each other through dynamics local (actuated) mechanisms inducing complex boundary conditions. The double input output port model of each substructure is a transfer where accelerations and external forces at the connection points are both on the model inputs and outputs. Such a model : * allows to the boundary conditions linked to interactions with the other substructures to be externalized outside the model, * is defined by the only substructure own dynamic parameters, * allows to build the dynamic model of the whole structure by just assembling the double port models of each substructure. The principle is first introduced on a single axis spring-mass system and then extented to the 6 degress-of-freedom case. This generalization uses the clamped-free substructure dynamic parameters such as finite element softwares can provide