15-02-2013, 03:52 PM
Typical Real-Time Applications
[attachment=51080]
INTRODUCTION
From its title, you can see that this book is about real-time (computing, communication, and
information) systems. Rather than pausing here to define the term precisely, which we will
do in Chapter 2, let us just say for now that a real-time system is required to complete its
work and deliver its services on a timely basis. Examples of real-time systems include digital
control, command and control, signal processing, and telecommunication systems. Every day
these systems provide us with important services. When we drive, they control the engine
and brakes of our car and regulate traffic lights. When we fly, they schedule and monitor the
takeoff and landing of our plane, make it fly, maintain its flight path, and keep it out of harm’s
way. When we are sick, they may monitor and regulate our blood pressure and heart beats.
When we are well, they can entertain us with electronic games and joy rides. Unlike PCs and
workstations that run nonreal-time applications such as our editor and network browser, the
computers and networks that run real-time applications are often hidden from our view. When
real-time systems work correctly and well, they make us forget their existence.
For the most part, this book is devoted to real-time operating systems and communication
protocols, in particular, how they should work so that applications running on them can
reliably deliver valuable services on time. From the examples above, you can see that malfunctions
of some real-time systems can have serious consequences. We not only want such
systems to work correctly and responsively but also want to be able to show that they indeed
do. For this reason, a major emphasis of the book is on techniques for validating real-time
systems. By validation, we mean a rigorous demonstration that the system has the intended
timing behavior.
DIGITAL CONTROL
Many real-time systems are embedded in sensors and actuators and function as digital controllers.
Figure 1–1 shows such a system. The term plant in the block diagram refers to a
controlled system, for example, an engine, a brake, an aircraft, a patient. The state of the plant
is monitored by sensors and can be changed by actuators. The real-time (computing) system
estimates from the sensor readings the current state of the plant and computes a control output
based on the difference between the current state and the desired state (called reference input
in the figure). We call this computation the control-law computation of the controller. The
output thus generated activates the actuators, which bring the plant closer to the desired state.
Sampled Data Systems
Long before digital computers became cost-effective and widely used, analog (i.e., continuoustime
and continuous-state) controllers were in use, and their principles were well established.
Consequently, a common approach to designing a digital controller is to start with an analog
controller that has the desired behavior. The analog version is then transformed into a digital
(i.e., discrete-time and discrete-state) version. The resultant controller is a sampled data
system. It typically samples (i.e., reads) and digitizes the analog sensor readings periodically
and carries out its control-law computation every period. The sequence of digital outputs thus
produced is then converted back to an analog form needed to activate the actuators.
Timing Characteristics.
To generalize from the above example, we can see that the
workload generated by each multivariate, multirate digital controller consists of a few periodic
control-law computations. Their periods range from a few milliseconds to a few seconds.
A control system may contain numerous digital controllers, each of which deals with some
attribute of the plant. Together they demand tens or hundreds of control laws be computed
periodically, some of them continuously and others only when requested by the operator or
in reaction to some events. The control laws of each multirate controller may have harmonic
periods. They typically use the data produced by each other as inputs and are said to be a rate
group. On the other hand, there is no control theoretical reason to make sampling periods of
different rate groups related in a harmonic way.
More Complex Control-Law Computations
The simplicity of a PID or similar digital controller follows from three assumptions. First, sensor
data give accurate estimates of the state-variable values being monitored and controlled.
This assumption is not valid when noise and disturbances inside or outside the plant prevent
accurate observations of its state. Second, the sensor data give the state of the plant. In general,
sensors monitor some observable attributes of the plant. The values of the state variables
must be computed from the measured values (i.e., digitized sensor readings). Third, all the
parameters representing the dynamics of the plant are known. This assumption is not valid for
some plants. (An example is a flexible robot arm. Even the parameters of typical manipulators
used in automated factories are not known accurately.)
HIGH-LEVEL CONTROLS
Controllers in a complex monitor and control system are typically organized hierarchically.
One or more digital controllers at the lowest level directly control the physical plant. Each
output of a higher-level controller is a reference input of one or more lower-level controllers.
With few exceptions, one or more of the higher-level controllers interfaces with the operator(
s).
Examples of Control Hierarchy
For example, a patient care system may consist of microprocessor-based controllers that monitor
and control the patient’s blood pressure, respiration, glucose, and so forth. There may be
a higher-level controller (e.g., an expert system) which interacts with the operator (a nurse
or doctor) and chooses the desired values of these health indicators. While the computation
done by each digital controller is simple and nearly deterministic, the computation of a highlevel
controller is likely to be far more complex and variable. While the period of a lowlevel
control-law computation ranges from milliseconds to seconds, the periods of high-level
control-law computations may be minutes, even hours.
[attachment=51080]
INTRODUCTION
From its title, you can see that this book is about real-time (computing, communication, and
information) systems. Rather than pausing here to define the term precisely, which we will
do in Chapter 2, let us just say for now that a real-time system is required to complete its
work and deliver its services on a timely basis. Examples of real-time systems include digital
control, command and control, signal processing, and telecommunication systems. Every day
these systems provide us with important services. When we drive, they control the engine
and brakes of our car and regulate traffic lights. When we fly, they schedule and monitor the
takeoff and landing of our plane, make it fly, maintain its flight path, and keep it out of harm’s
way. When we are sick, they may monitor and regulate our blood pressure and heart beats.
When we are well, they can entertain us with electronic games and joy rides. Unlike PCs and
workstations that run nonreal-time applications such as our editor and network browser, the
computers and networks that run real-time applications are often hidden from our view. When
real-time systems work correctly and well, they make us forget their existence.
For the most part, this book is devoted to real-time operating systems and communication
protocols, in particular, how they should work so that applications running on them can
reliably deliver valuable services on time. From the examples above, you can see that malfunctions
of some real-time systems can have serious consequences. We not only want such
systems to work correctly and responsively but also want to be able to show that they indeed
do. For this reason, a major emphasis of the book is on techniques for validating real-time
systems. By validation, we mean a rigorous demonstration that the system has the intended
timing behavior.
DIGITAL CONTROL
Many real-time systems are embedded in sensors and actuators and function as digital controllers.
Figure 1–1 shows such a system. The term plant in the block diagram refers to a
controlled system, for example, an engine, a brake, an aircraft, a patient. The state of the plant
is monitored by sensors and can be changed by actuators. The real-time (computing) system
estimates from the sensor readings the current state of the plant and computes a control output
based on the difference between the current state and the desired state (called reference input
in the figure). We call this computation the control-law computation of the controller. The
output thus generated activates the actuators, which bring the plant closer to the desired state.
Sampled Data Systems
Long before digital computers became cost-effective and widely used, analog (i.e., continuoustime
and continuous-state) controllers were in use, and their principles were well established.
Consequently, a common approach to designing a digital controller is to start with an analog
controller that has the desired behavior. The analog version is then transformed into a digital
(i.e., discrete-time and discrete-state) version. The resultant controller is a sampled data
system. It typically samples (i.e., reads) and digitizes the analog sensor readings periodically
and carries out its control-law computation every period. The sequence of digital outputs thus
produced is then converted back to an analog form needed to activate the actuators.
Timing Characteristics.
To generalize from the above example, we can see that the
workload generated by each multivariate, multirate digital controller consists of a few periodic
control-law computations. Their periods range from a few milliseconds to a few seconds.
A control system may contain numerous digital controllers, each of which deals with some
attribute of the plant. Together they demand tens or hundreds of control laws be computed
periodically, some of them continuously and others only when requested by the operator or
in reaction to some events. The control laws of each multirate controller may have harmonic
periods. They typically use the data produced by each other as inputs and are said to be a rate
group. On the other hand, there is no control theoretical reason to make sampling periods of
different rate groups related in a harmonic way.
More Complex Control-Law Computations
The simplicity of a PID or similar digital controller follows from three assumptions. First, sensor
data give accurate estimates of the state-variable values being monitored and controlled.
This assumption is not valid when noise and disturbances inside or outside the plant prevent
accurate observations of its state. Second, the sensor data give the state of the plant. In general,
sensors monitor some observable attributes of the plant. The values of the state variables
must be computed from the measured values (i.e., digitized sensor readings). Third, all the
parameters representing the dynamics of the plant are known. This assumption is not valid for
some plants. (An example is a flexible robot arm. Even the parameters of typical manipulators
used in automated factories are not known accurately.)
HIGH-LEVEL CONTROLS
Controllers in a complex monitor and control system are typically organized hierarchically.
One or more digital controllers at the lowest level directly control the physical plant. Each
output of a higher-level controller is a reference input of one or more lower-level controllers.
With few exceptions, one or more of the higher-level controllers interfaces with the operator(
s).
Examples of Control Hierarchy
For example, a patient care system may consist of microprocessor-based controllers that monitor
and control the patient’s blood pressure, respiration, glucose, and so forth. There may be
a higher-level controller (e.g., an expert system) which interacts with the operator (a nurse
or doctor) and chooses the desired values of these health indicators. While the computation
done by each digital controller is simple and nearly deterministic, the computation of a highlevel
controller is likely to be far more complex and variable. While the period of a lowlevel
control-law computation ranges from milliseconds to seconds, the periods of high-level
control-law computations may be minutes, even hours.