#pid control

Case Details

The ARM Edge Gateway is the core of data acquisition and control in industrial settings, integrating the open-source OpenPLC control platform. It supports multiple programming methods such as Ladder Diagram (LD), Function Block Diagram (FBD), and Structured Text (ST), with built-in PID control algorithms. The gateway enables local closed-loop control and seamless communication with upper-level systems or cloud platforms via Ethernet, 4G, or WiFi, balancing real-time performance and flexibility.

System Architecture and Functions

Hardware Layer

Sensors: Collect signals such as temperature, pressure, liquid level, flow, and speed (supporting analog/digital inputs).

Actuators: Control devices like motors, valves, heaters, and pumps (supporting analog/relay outputs).

ARM Edge Gateway ARMxy series:

CPU: Cortex-A7/A53/A55, delivering robust performance.

Interfaces: optional RS485/RS121, Ethernet, IO, 4G/WiFi.

Functions: Real-time data acquisition from the field, supporting multiple industrial protocols.

Control Layer

OpenPLC Platform (Running on ARM Gateway):

Complies with IEC 61131-3 standards, supporting multiple programming languages.

Built-in PID function blocks, supporting proportional (Kp), integral (Ki), and derivative (Kd) parameter tuning, with flexible sampling cycle settings.

Supports multi-loop PID control, suitable for complex industrial scenarios.

Application Logic

Typical Control Loops:

Temperature Control: Sensor collects temperature → OpenPLC processes → Adjusts heater.

Pressure Control: Pressure sensor collects data → OpenPLC processes → Controls regulating valve.

Speed Control: Encoder feeds back speed → OpenPLC processes → Adjusts variable frequency drive.

Upper-Level Management

Local Management: Communicates with HMI/SCADA systems via Modbus TCP or MQTT protocols for real-time data monitoring.

Cloud Platform Integration: Supports historical data storage, remote parameter tuning, and trend analysis.

Alarm Mechanism: Automatically triggers alarms when control errors exceed set thresholds.

Typical Application Scenarios

Building HVAC: Precisely regulates room temperature.

Water Treatment Systems: Maintains constant water level or flow control.

Boilers/Kilns: Achieves closed-loop regulation of combustion temperature.

Motor Speed Regulation: Ensures constant speed or pressure operation.

Food & Beverage/Fermentation Industry: Accurately controls temperature and humidity to enhance production quality.

Solution Advantages

Open-Source and Customization: OpenPLC’s open-source nature provides high flexibility and low development costs.

Edge Computing Capability: The ARM gateway supports local computation, reducing dependency on cloud systems and minimizing network latency.

Strong Real-Time Performance: Local PID closed-loop control ensures fast response and high reliability.

High Scalability: Supports multiple industrial protocols (Modbus, OPC UA, MQTT), facilitating integration with cloud platforms or other systems.

Summary

This solution, centered on the ARM Edge Gateway and integrated with the OpenPLC open-source platform, builds an efficient, flexible, and cost-effective industrial control and data acquisition system. It achieves real-time performance through local PID closed-loop control and scalability through multi-protocol support and cloud integration, making it suitable for various industrial scenarios. Leveraging open-source features and edge computing capabilities, this solution offers robust customization and real-time control while reducing costs, making it an ideal choice for industrial automation.

Modeling of DC Motor and Choosing the Best Gains for PID Controller

by Ye Htet Aung | Tin Tin Hla ""Modeling of DC Motor and Choosing the Best Gains for PID Controller""

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd26636.pdf  

Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/26636/modeling-of-dc-motor-and-choosing-the-best-gains-for-pid-controller/ye-htet-aung

call for paper health science, ugc approved engineering journal, social science journal

I just realized today that proportional derivative control is basically the same as a perceptron algorithm in the application I’m using.  Using the PD controller basically allows you to control the relationship of your weights and inputs more, since the perceptron has an associated function that is a pure linear relation between the vector of input vectors and the output vector using the vector of weights.

I made a controller for my water rocket!

See  Ziegler–Nichols tuning method

 http://en.wikipedia.org/wiki/Ziegler%E2%80%93Nichols_method

The other day I was trying to tune a PID controller for a simple boost converter. After spending a lot of time trying to get all the parameters right to get a good feedback response, I went to the internet and discovered this method.