Single-Input-Output

Generally, the transmission resonances of individual microresonators connected to a single input/output MNF can overlap and their separation may not be simple. However, in the case of relatively small changes, the separation of individual... 

They are multivariable in nature, and there are interactions which exist among the various control and output variables, making a simplistic single input-output (SISO) strategy somewhat hazardous if not inefficient. 

A time-delay-neural-network in nonlinear autoregressive with exogenous input structure (narx) for single input/output (one layer) data is chosen for the calculation of an unknown input-output-relation... 

Realizations for controllers with multiple inputs and outputs may be generated by suitably concatenating realizations corresponding to the single input-output combinations. Let the realization corresponding to controller output i and input j be given by... 

Single-ended amplifier. An operational amplifier with a single input (or output). 

The z-transform is the prineipal analytieal tool for single-input-single-output dis-erete-time systems, and is analogous to the Laplaee transform for eontinuous systems. 

The human brain is comprised of many millions of interconnected units, known individually as biological neurons. Each neuron consists of a cell to which is attached several dendrites (inputs) and a single axon (output). The axon connects to many other neurons via connection points called synapses. A synapse produces a chemical reaction in response to an input. The biological neuron fires if the sum of the synaptic reactions is sufficiently large. The brain is a complex network of sensory and motor neurons that provide a human being with the capacity to remember, think, learn and reason. 

It has been estimated that of the total U.S. increase in farm output between 1940 and 1955, 43 percent is attributable to increased crop yields per hectare, 27 percent to increases in value added by livestock production, 23 percent to reduction in farm-produced power, and 7 percent to changes in the amount of capital used. While it is not possible to isolate the effect of a single input, it is estimated that increased use of fertilizer accounted for more... 

In this case, each site can have many identical outputs but receives only a single input. There are four possible Boolean functions with one input two yield fixed values of 0 or 1, independent of input (these two static functions, and Fi are always among the 2 possible Boolean functions), the third inverts the input T = —) and the fourth is the identity = +). We will discuss behavior arising only ft om the latter two active functions. Exact results for the analytically tractable case of allowing a distribution of all four Boolean functions have been derived by Flyvbjerg and Kjaer [flyvb88]. 

Seagall, N.L. Taylor, P.A. "Saturation of Single-Input Single-Output Controllers Written in Velocity Form Reset Windup Protection", lEC Process Des. Dev., 1986, 25., 495. 

OLS is also called multiple linear regression (MLR) and is a commonly used method to obtain a linear input-output model for a given data set. The model obtained by OLS for a single output is given by... 

Figure 1.2. A block diagram representation of a single-input single-output negative feedback system. Labels within the boxes are general. Labels outside the boxes apply to the simplified pH control discussion.

If you are working with only single-input single-output (SISO) problems, it would be more appropriate to replace the notation B by b and C by cT, and write d for D. 

We use a simple liquid level controller to illustrate the concept of a classic feedback control system.1 In this example (Fig. 5.1), we monitor the liquid level in a vessel and use the information to adjust the opening of an effluent valve to keep the liquid level at some user-specified value (the set point or reference). In this case, the liquid level is both the measured variable and the controlled variable—they are the same in a single-input single-output (SISO) system. In this respect, the controlled variable is also the output variable of the SISO system. A system refers to the process which we need to control plus the controller and accompanying accessories such as sensors and actuators.2... 

We now re-introduce the change in reference, r(t). We will stay with analyzing a single-input single-output system. By a proper choice in the indexing of the state variables, we select x, = y. 

The next task is to seek a model for the observer. We stay with a single-input single-output system, but the concept can be extended to multiple outputs. The estimate should embody the dynamics of the plant (process). Thus one probable model, as shown in Fig. 9.4, is to assume that the state estimator has the same structure as the plant model, as in Eqs. (9-13) and (9-14), or Fig. 9.1. The estimator also has the identical plant matrices A and B. However, one major difference is the addition of the estimation error, y - y, in the computation of the estimated state x. 

In principle, any type of process model can be used to predict future values of the controlled outputs. For example, one can use a physical model based on first principles (e.g., mass and energy balances), a linear model (e.g., transfer function, step response model, or state space-model), or a nonlinear model (e.g., neural nets). Because most industrial applications of MPC have relied on linear dynamic models, later on we derive the MPC equations for a single-input/single-output (SISO) model. The SISO model, however, can be easily generalized to the MIMO models that are used in industrial applications (Lee et al., 1994). One model that can be used in MPC is called the step response model, which relates a single controlled variable y with a single manipulated variable u (based on previous changes in u) as follows ... 

In the previous chapter we discussed the elements of a conventional single-input-single-output (SISO) feedback control loop. This configuration forms the backbone of almost all process control structures. 

Avoid control-loop interaction if possible, but if not, make sure the controllers are tuned to make the entire system stable. Up to this point we have discussed tuning only single-input-single-output (SISO) control loops. Many... 

This equation shows that closedloop dynamics depend on the process openloop transfer functions (G, Gv, and Gj) and on the feedback controller transfer function (fl). Equation (10.10) applies for simple single-input-single-output systems. We will derive closedloop characteristic equations for other systems in later chapters. 

One final comment should be made about model-based control before we leave the subject. These model-based controllers depend quite strongly on the validity of the model. If we have a poor model or if the plant parameters change, the performance of a model-based controller is usually seriously affected. Model-based controllers are less robust than the more conventional PI controllers. This lack of robustness can be a problem in the single-input-single-output (SISO) loops that we have been examining. It is an even more serious problem in multi-variable systems, as we will find out in Chaps. 16 and 17. 

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