right TIME is NOW, The

InTech, Jul 2004

The core of real-time performance is its use in control, signal processing, and event response.

Numerous measurement and control applications require real-time performance. To recognize these real-time applications, you must first understand the core of real-time performance and how it works in control, signal processing, and event response. With real-time control, you can continually monitor and stimulate a physical system. Real-time control applications repeatedly perform a user-defined task separated by a specified time interval.

Many real-time control systems exist in the world around you, such as the cruise control in your car or the thermostat controlling the temperature in your house. There are several ways to characterize a real-time control application-control-loop cycle time, determinism, and jitter.

Control-loop cycle time: Most real-time control systems interface with n physical system by comparing the current state with the desired state and then stimulating the physical system based on the comparison.

The time it takes to traverse this loop is considered the control-loop cycle time. This cycle time varies based on the needs of the system. For instance, the control-loop cycle time of an electronic thermostat in a conventional oven is relatively slow. It acquires a temperature, compares that to the desired temperature, and turns the heating coils on or off. In this case a one second loop rate would be suitable.

On the other hand, ovens used in industrial environments require extremely precise temperature for growing crystals and other processes. The control-loop cycle time here would have to be much faster to maintain the stringent temperature requirements.

Determinism: Determinism measures the consistency of the specified time interval between events. Many control algorithms, such as proportional, integral, derivative, require very deterministic behavior.

For example, an elevator gradually moves to the correct floor because of the deterministic behavior of the control algorithm. Without the determinism the elevator would still reach the correct floor, but without the stability.

Jitter: All real-time systems encounter an amount of error called j itter. Jittcr is another way of measuring the determinism of a realtime system. You can calculate it as the maximum difference between any individual time delay and the desired time delay in a system.

Hard and soft real time

You can map real-time control performance onto a spectrum of performance.

On one side, hard real-time systems are very deterministic and never miss an event. An example of a hard real-time system is an engine dynamometer. If there is a missed event, the data collected or the road conditions simulated would be incorrect.

On the other side of the spectrum, soft real-time systems do not require the same degree of determinism and occasionally miss events without malfunctioning. An example of a soft real-time system is a temperature monitoring system where missing one data point does not affect the overall trend of the system, because the general trend of temperature is relatively slow to change.

Real-time signal processing

Real-time signal processing has many of the same characteristics as real-time control. It requires deterministic time intervals between repetitive events. But instead of calculating a response, it performs signal processing on the acquired data.

An example of such an application is calculating the frequency of a signal. The application deterministically acquires a collection of values that represents a waveform and then performs a power spectrum on that data in a loop. Although this example analyzes a waveform in blocks of data, it could also have analyzed each data value as you logged it in with a point-by-point analysis routine.

Point-by-point analysis routines: In many applications, point-by-point analysis routines provide better performance. Instead of analyzing blocks of data, these analysis routines maintain a memory of historical data and calculate a new output based on this data and the current value. While these analysis routines take in single values, they generate both single values and waveforms.

For instance, a single-point digital filter acquires a point and outputs a filtered value. A power spectrum function would acquire a point and generate the frequency-domain waveform. Hard real-time performance is necessary in such situations, because missing input values or even acquiring these values after a small time delay destroys the integrity of the historical data for future calculations.

Inline performance: Point-by-point analysis routines reduce the time delay between acquiring the data and generating the processed waveform.

For example, a simple digital filter application acquires 1,000 data points in one second, filters the data, then generates the filtered waveform. Although the filtered waveform is accurate, it is generated an entire second after it is initially acquired, introducing a large time delay or phase difference.