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The development of Automation Control
Release time:2019-05-01      clicks:1264

The history of automation control dates back to ancient China's early automated timers and the South-Pointing Chariot, with the widespread application of automation control technology beginning during the European Industrial Revolution. Here is a comprehensive overview of the development of automation control technology:

 

Early Automation Control


Ancient China

Automated Timers

Ancient China developed early forms of automated control with devices like water clocks.

South-Pointing Chariot

An ancient Chinese invention, it used differential gears to maintain a constant direction.

 

Industrial Revolution

 

James Watt's Steam Engine

In 1788, James Watt invented the centrifugal governor. This device used feedback principles to automatically adjust the intake valve's opening based on load or steam supply changes, thereby controlling the steam engine's speed.

 

Evolution of Process Control Systems


1.      First Generation - Pneumatic Control System (PCS)

Timeline

Over 150 years ago.

Technology

Based on 5-13 psi pneumatic signals.

Characteristics

Simple local operation mode with early control theory. No concept of a control room yet.

 

2. Second Generation - Analog Control System (ACS)

Timeline

Developed over the next 25 years.

Technology

Based on 0-10 mA or 4-20 mA current analog signals.

Characteristics

Marked the era of electrical automation control. Significant advancements in control theory established the foundations of modern control, with the introduction of control rooms and separated control functions.

 

3. Third Generation - Computer Control System (CCS)**:

Timeline

Began in the 1970s.

Technology

Introduction of digital computers initially used in measurement, analog, and logic control fields.

Characteristics

Revolutionized automation control, with centralized control computer systems. However, reliability issues led to the development of Distributed Control Systems (DCS) to mitigate the risk of system-wide failures.

 

4. Fourth Generation - Distributed Control System (DCS)**:

Timeline

Developed with advancements in semiconductor manufacturing and microprocessor technology.

Technology

Utilizes multiple computers and intelligent instruments for decentralized control.

Characteristics

Shift from 4-20 mA analog signals to digital signals for communication, enhancing reliability and control.

 

5. Fifth Generation - Fieldbus Control System (FCS)

Technology

Evolution from DCS, using digital, bidirectional communication links with multi-node branching structures.

Characteristics

Moves from centralized to field control with data transmission via buses. Examples include Profibus and LonWorks. Offers greater development potential than traditional DCS, reducing costs, increasing efficiency, and enabling comprehensive monitoring and management of field devices.

 

Development Phases of Automation

 

1. 1940s to Early 1960s

Drivers

Market competition, resource utilization, reducing labor intensity, improving product quality, and accommodating mass production.

Features

Single-machine automation with numerical control (NC) systems.


2.      Mid-1960s to Early 1970s

Drivers

Increasing market competition, faster product updates, higher quality demands, and medium to large batch production needs.

Features

Automated production lines with the introduction of software numerical control (NC) systems, CAD, and CAM software.

Examples

Automatic production lines for drilling, boring, and milling.

 

3. Mid-1970s to Present

Drivers

Diverse market demands and the need for highly integrated automation technologies.

Features

Emergence of Computer-Integrated Manufacturing (CIM) systems, flexible manufacturing systems (FMS), and concurrent engineering methodologies.

 

Modern Control Theory and Systems

 

Modern Control Theory

Development

With the advent of new mathematical results and the application of electronic computers, modern control theory emerged, focusing on high-performance, high-precision multi-variable optimal control problems using state-space methods.

 

Intelligent Control Theory

Integration

Combines control theory, information theory, and bionics, leading to advanced intelligent control systems.

 

Feedback Control Systems

 

Feedback Principle

In a feedback control system, the control device's action is derived from the feedback information of the controlled variable. This feedback is used to continuously correct the deviation between the controlled variable and the set point, achieving the control objective.

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