Implementing High Precision Motor Control Algorithms with Industrial PCs

In the field of industrial automation, high precision motor control has always been a challenging topic. As a technical expert with over ten years of experience in the industrial PC control domain, today I will explain in detail how to implement high precision motor control algorithms.

Overview of Motor Control Algorithm Library

In industrial PC motor control, we mainly use the TwinCAT Motion Control library to achieve high precision control. This library provides a complete set of motion control functions, including position control, speed control, torque control, and other core functionalities. Its most significant feature is the support for real-time operating systems, enabling microsecond-level control precision.

The core advantages of the TwinCAT Motion Control library include:

• • Support for various motor types (stepper, servo, DC, etc.)
• • Provides a rich set of motion control functions
• • Has real-time control capabilities
• • Supports multi-axis coordinated control
• • Integrates advanced diagnostic tools

System Configuration Requirements

To achieve high precision motor control, system configuration is crucial:

1. 1. Hardware Requirements:

• • Intel i5 or higher CPU
• • 8GB or more RAM
• • EtherCAT bus interface card
• • Industrial PC that supports real-time systems

1. 2. Software Environment:

• • Windows 10 Professional
• • TwinCAT 3.1 or higher version
• • Visual Studio 2017/2019
• • TC1200 Motion Control license

Basic Control Implementation

Let’s start with a basic position control example:

PROGRAM MAIN
VAR
    fbAxis1  : AXIS_REF;
    bEnable  : BOOL;
    bExecute : BOOL;
    fPosition: LREAL;
    fVelocity: LREAL;
END_VAR

// Motor Enable
MC_Power(
    Axis    := fbAxis1,
    Enable  := bEnable,
    Status  => );

// Position Control
MC_MoveAbsolute(
    Axis    := fbAxis1,
    Execute := bExecute,
    Position:= fPosition,
    Velocity:= fVelocity);

This code demonstrates the basic position control process: first enabling the motor, then using the MC_MoveAbsolute function block to achieve absolute position movement. In practical applications, we also need to add:

1. 1. Initialization parameter settings
2. 2. Motion status monitoring
3. 3. Error handling mechanism
4. 4. Smooth acceleration and deceleration control

Advanced Control Algorithm Implementation

In actual industrial applications, we often need more complex control strategies. Below is a complete implementation of high precision position control:

FUNCTION_BLOCK FB_HighPrecisionControl
VAR_INPUT
    fTargetPosition : LREAL;
    fMaxVelocity   : LREAL;
    fAcceleration  : LREAL;
    fDeceleration  : LREAL;
    bStartMove     : BOOL;
END_VAR

VAR
    fbAxis         : AXIS_REF;
    fbMC_Power     : MC_Power;
    fbMC_Move      : MC_MoveAbsolute;
    stAxisStatus   : ST_AxisStatus;
    tPID           : ST_PIDParameters;
END_VAR

// PID Parameter Optimization
tPID.fKp := 100.0;
tPID.fKi := 0.01;
tPID.fKd := 10.0;

// Real-time position compensation
IF ABS(stAxisStatus.fActualPosition - fTargetPosition) < 0.001 THEN
    // Fine-tuning compensation algorithm
END_IF

This control algorithm includes the following key elements:

1. 1. Adaptive PID control
2. 2. Feedforward compensation
3. 3. Real-time position error correction
4. 4. Disturbance rejection control

Deep Thoughts and Outlook

High precision motor control is the foundation of industrial automation. With the development of Industry 4.0, the demand for control precision will continue to rise. By reasonably utilizing the TwinCAT Motion Control library and combining it with advanced control algorithms, we can achieve nanometer-level control precision. In the future, artificial intelligence and deep learning will bring new breakthroughs to motor control.