Abstract System: Adaptive Control System

Name: Adaptive Control System

Based on:  System (Abstract)

Abstract System: This system has been identified as an abstract system that cannot be implemented directly. The abstract system establishes a shared pattern of characteristics that any system can use to describe its unique characteristics when referenced in the 'based on' list above. These references are described using a generalization association in UML.

An Adaptive Control System provides a way to manage a set of system properties within a target control range when the environment is changing. The system makes use of feedback elements to sense and respond to changes in the outputs or results and take appropriate corrective action to maintain the desired state of the outputs. Typical control systems are:

  • Performance Management.
  • Automatic Pilot Landing Systems in an Aircraft

The control system is a type of regulatory system. These concepts are used in the Viable System Model (VSM).

System properties of the system are generally regulated as part of a control system.

Systemic Measurable Variables

The emergent properties created or used through the interaction of the elements. This includes both desired and undesired.

The following are typical variables for a control system:

  • Reference Input: Command for specific action or output setting
  • Feedback Signal: representation of the output at a given time
  • Controlled output: the actual output value from the System.
  • Actuating Signal: difference between the reference and the feedback signal

NOTE: the names vary depending upon the control system model used.

Systemic Capabilities or Functions

The capabilities of the control system are to provide a regulation capability of the Controlled Output variable. These functions are generally embodied in a combination of control elements and plant.

System States

The various defined states that the system-of-interest can be in.

  • Architectural states: Generally defined in the enabling system
  • Transformational States Generally defined in an enabling or adaptive system associated with the control system.
  • Operational States: These are typically initialising, Reference input change, stable, shutting down.

Identify the key stakeholders and their concerns for this system. Each stakeholder is identified and their concerns and interests are identified. The list below is an example. Each system will have a specific set of stakeholders and concerns.

  • Owner / manager: Is this a sustainable / stable system? will our customers be satisfied?
  • System Architect: Are the system concepts understood? Are the system properties sufficient to deliver the objectives? Is the feedback mechanism sufficient to maintain / track outputs / outcomes?
  • People in the environment Will the people confirm or use the benefits of the system?
  • Change Agents Do we have the ability to change the system in a planned way?
  • People who are part of the system Will I understand my contribution to the system?

The environment and the potential impacts on the system-of-interest.

this section includes

  • Transactional: Ensure the delivery of the controlled output or respond to problems
  • External Possible disruptions due to external factors: temperature, environment (e.g. flood, etc.).
  • Regulator : Extra requirements or unexpected (magnitude or frequency) of changes to the reference inputs.

The system-of-interest consists of a number of identified system elements. .These are typically shown in a 'system breakdown structure'.

System Element identification for Adaptive Control System

Note: The adaptive control system builds on the basic control system model.

Note: some of the system elements may be systems their own right. These systems may become a system-of-interest and may be described using a Link to the System Description Template.

The relationships or interactions are defined in this section. The picture included in this section shows the way the system elements interact.

System Element Relationships for an Adaptive Control System

In this picture, the lines between the system elements are defined. These may represent formal interfaces, such as, communication interactions, protocols, information flows, Contracts, etc. In this section, the relationships may be defined.

The following approaches also have a similar pattern to the adaptive control system:

  • The Viable System based upon the Viable System Model
  • The Adaptation and Learning Cycle, Russell Ackoff.

Configuration / Scenario:

Describes any configuration / scenario attributes for a specific system-of-interest. This may not be appropriate for all system descriptions (e.g. patterns or abstract systems).

Cyclical (Repeating / Regular) Processes

The processes to translate requirements and architecture into an operational system. An example of a set of life cycle processes can be found in ISO 15288.

NOTE: The Shannon Sampling Theorem applies to the dynamic behavior of the control system. If the sampling rate is too slow, the control system may become unstable or unable to control or regulate the process. The sampling rate is generally at least twice the underlying base frequency of the system being controlled.

Development Life Cycle Processes

This area describes the life cycle for creating, using or releasing a system. The Adaptive Control System is created through a normal life cycle model such as ISO 15288:2015. There are various models that can be used to shape the adaptive control systems for the enterprise. These are shown in the

Viable System system description

References

The following references support this type of system-of-interest.