What Is PID Control?
PID control respectively stands for proportional, integral and derivative control, and is the most commonly used control technique in industry. The following video explains how PID control works and discusses the effect of the proportional, integral and derivative terms of the controller on the closed-loop system response. To learn how to design and implement PID controllers, check out the resources below the video.
PID control involves several tasks that include:
- Selecting an appropriate PID algorithm (P, PI, or PID)
- Tuning controller gains
- Simulating the controller against a plant model
- Implementing the controller on a target processor
While simple in theory, design and implementation of PID controllers can be difficult and time consuming in practice.
MATLAB and add-on products bring efficiency to these design tasks by enabling you to:
- Configure your Simulink PID Controller block for PID algorithm (P,PI, or PID), controller form (parallel or standard), anti-windup protection (on or off), and controller output saturation (on or off)
- Automatically tune controller gains against a plant model and fine-tune your design interactively
- Autotune controller gains in real time against a physical plant
- Tune multiple controllers in batch mode
- Run closed-loop system simulation by connecting your PID Controller block to the plant model
- Automatically generate C code for targeting a microcontroller
- Automatically generate IEC 61131 structured text for targeting a PLC or PAC
- Automatically scale controller gains to implement your controller on a processor with fixed-point arithmetic
Exemples et démonstrations
Workflow
Modeling
PID Tuning Against a Plant Model
Power Conversion
Robotics
Chemical Processes
Mechanical
Real-Time PID Autotuning
FAQ
Tutorials
Références
See also: control systems, system design and simulation, physical modeling, linearization, parameter estimation, PID tuning, control design software, Bode plot, root locus, PID control videos, field-oriented control, BLDC motor control, motor simulation for motor control design, power factor correction, small signal analysis, Optimal Control