Input-output subsystem

Alcantara V, Padilla E (2009) Input-output subsystems and pollution an application to the service sector and CO2 emissions in Spain. Ecol Econ 68(3) 905-914... 

This representation is also called normal form and it is graphically depicted in Figure 3. It can be seen that the normal form is composed of three parts respectively given by the subsystems (4a), (4b) and (4c). The first part presents a linear structure and it is given by a chain of r — 1 integrators, whereas the second part has a nonlinear structure, where the input-output relationship explicitly appears. Finally, the last part is conformed by the dynamics of the n — r complementary functions. This part is called internal dynamics because it cannot be seen from the input-output relationship (see Figure 3) and whose structure can be linear or nonlinear. 

This system clearly appears decomposed into a linear subsystem zi, which is the only responsible for the input-output behavior, and a non linear subsystem Z2, whose behavior is stable. Then, by defining the control error as e = St — S ), it is clear to observe that the solution of the linear subsystem is given by e = exp —Kc t), which implies that St S as t oo. ... 

Once the large internal flow rates have been set via appropriate control laws, the index of the DAE system (7.21) is well defined, and a state-space realization (ODE representation) of the slow subsystem can be derived. This representation of the slow dynamics of the column can be used for the derivation of a model-based nonlinear controller to govern the input-output behavior of the column, namely to address the control of the product purity and of the overall material balance. To this end, the small distillate and bottoms flow rates as well as the setpoints of the level controllers are available as manipulated inputs. 

Create a SIPOC and/or Process Map (see Techniques 45 and 46) to document the current solution s inputs, outputs, customers, and suppliers, and any associated processes. Use this information to make a list of the process steps, systems, subsystems, or components that are linked to the focus topic. For example, part of the process of using a credit card is carrying a physical card, which can be lost or stolen and subsequently used by identity thieves. 

Complex pharmacokinetic/pharmacodynamic (PK/PD) simulations are usually developed in a modular manner. Each component or subsystem of the overall simulation is developed one-by-one and then each component is linked to run in a continuous manner (see Figure 33.2). Simulation of clinical trials consists of a covariate model and input-output model coupled to a trial execution model (10). The covariate model defines patient-specific characteristics (e.g., age, weight, clearance, volume of distribution). The input-output model consists of all those elements that link the known inputs into the system (e.g., dose, dosing regimen, PK model, PK/PD model, covariate-PK/PD relationships, disease progression) to the outputs of the system (e.g., exposure, PD response, outcome, or survival). In a stochastic simulation, random error is introduced into the appropriate subsystems. For example, between-subject variability may be introduced among the PK parameters, like clearance. The outputs of the system are driven by the inputs... 

Then, proceeding backwards through the system, the unit cost of the input to subsystem i is njj times that of the output therefrom. 

The Matlab Simulink Model was designed to represent the model stmctuie and mass balance equations for SSF and is shown in Fig. 6. Shaded boxes represent the reaction rates, which have been lumped into subsystems. To solve the system of ordinary differential equations (ODEs) and to estimate unknown parameters in the reaction rate equations, the inter ce parameter estimation was used. This program allows the user to decide which parameters to estimate and which type of ODE solver and optimization technique to use. The user imports observed data as it relates to the input, output, or state data of the SimuUnk model. With the imported data as reference, the user can select options for the ODE solver (fixed step/variable step, stiff/non-stiff, tolerance, step size) as well options for the optimization technique (nonlinear least squares/simplex, maximum number of iterations, and tolerance). With the selected solver and optimization method, the unknown independent, dependent, and/or initial state parameters in the model are determined within set ranges. For this study, nonlinear least squares regression was used with Matlab ode45, which is a Rimge-Kutta [3, 4] formula for non-stiff systems. The steps of nonlinear least squares regression are as follows ... 

Hierarchical Approach is a simple but powerful methodology for the synthesis of process flowsheets. It consists of a top-down analysis organised as a clearly defined sequence of tasks grouped in levels. Each level solves a fundamental problem as, number of plants, input/output structure, reactor design and recycle structure, separation system, energy integration, environmental analysis, safety and hazard analysis, and plantwide control. At each level, systematic methods can be applied for the synthesis of subsystems, as chemical reaction, separations, or heat exchangers network. 

Each "input circuit" contains the electronics required to read one sensor input. The "input module" subsystem includes all the electronics common to all input channels on a module. The "main processor" encompasses all components common to any PLC function. The "output module" subsystem contains all components common to the output channels on one module. The "output circuit" consists of the components needed to interface to one final elements device. 

For example, for a information processing subsystems consisting of PLCs the fi factor was evaluated in the range of 0.5% < /S < 5%. For subsystems, which contain sensors and executive elements %input/output modules 1% < 8< 50% (Hok-stad 2005). Basic value of /1-factor is specified from a table of score estimations on the basis of lEC 61508 suggestions and expert opinions. 

Further authors make a difference between systems, systems of systems (which are built by components that are large-scale systems), mega systems and intelligence-based systems which are able to comprehend, understand and profit from experience in order to adapt to changes of their environment [8]. A system is made up by the complex networking of resources such as manpower, equipment, facility, material, software, hardware and so on. Resources are to be considered as subsystems which interact with each other within or beyond the surrounding system. A system is characterized by inputs, outputs, internal processes and mechanisms as well as constraints [9]. 

As illustrated in Figure 16.52, the audio subsystem comprises the audio encoding/decoding function and resides between the audio inputs/outputs and the transport subsystem. The audio encoder(s) is (are) responsible for generating the audio elementary stream (s), which are encoded representations of the baseband audio input signals. The flexibility of the transport system allows multiple audio elementary... 

The detailed design is characterized by increasing levels of detail and refinement to the preliminary design from the subsystem level to the subroutine level of detail. This implies describing in detail the user s inputs, system outputs, input/output files, and the interfaces at the module level. 

This section describes a proposed methodology to evaluate the environmental impact of a chemical industrial process chain in the most accurate way possible. It includes a procedure to compute the LCI based on the concept of eco-vectors [Sonneman et al., 2000], Each process stream (feed, product, intermediate or waste) has an associated eco-vector whose elements are expressed as Environmental Loads (EL, e.g. SO2, NOJ per functional unit (ton of main product). All input eco-vectors, corresponding to material or energy streams, have to be distributed among the output streams of the process (or subsystem). In this sense, a balance of each EL of the eco-vector can be stated similarly to the mass-balance (input = output + generation ). This is the reason why all output streams are labelled as products or emissions. The eco-vector has negative elements for the pollutants contained in streams that are emissions and/or waste. Figure 1 illustrates these ideas for an example of a chain of three processes that produces a unique product. The proposed procedure associates inventory data with specific environmental impacts and helps to understand the effect of those impacts in human health, natural resources and the ecosystem. 

For example, the subsystem might be a pump, which can be modelled with the help of bondgraphs and easily be introduced in the system as a whole, also modelled with bondgraphs. Subsystems, modelled by means of other computational techniques, can also be introduced by means of and adaptation of the subsystem s behaviour in terms of the input/output relations at the ports in the total system s bondgraph. 

Within one interdependent infrastructure system, its subsystems depend on each other by different types of interdependencies. These have different causes and modes of manifestations (Buldyrev et al. 2010, Dobson 2008) formally, these can be described in terms of dynamic models and input/ output constraints. 

Subsystem A system consists of a set of subsystems. A subsystem is composite hardware and software design element, which can be composed of further subsystems or components or modules. Examples for subsystems are power supply, input, output, logic unit, software,... 

Su(co) and (co) describe the amphtude of the signals as a function of the frequency. The frequency domain offers the possibility to eompose in an easy way the overall input-output relation of a complex system eonsisting of several interconnected subsystems, from the separate transfer functions. 

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