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The difference between pi regulator and PID control _ Matlab pi regulator parameter selection _MATLAB inside PI control problem
The PI controller is a linear control mechanism that generates a control deviation based on a preset value and the actual output value. It combines the proportional and integral components of the deviation in a linear fashion to produce a control signal, which is then used to manage the target system. The PID controller, on the other hand, adjusts the overall control system's deviation according to the principles of PID control, ensuring that the actual value of the controlled variable aligns with the desired process value. Different control strategies are suited to varying production processes, and selecting the appropriate control law is crucial for achieving the desired results. Otherwise, the PID controller may fail to deliver the expected performance.
Today, the level of industrial automation has become a significant indicator of modernization across industries. Control theory has evolved through three main phases: classical control theory, modern control theory, and intelligent control theory. An excellent example of intelligent control is the fuzzy fully automatic washing machine. Control systems can be classified into open-loop and closed-loop systems. A control system consists of a controller, sensors, transmitters, actuators, and input/output interfaces. The controller's output is fed into the controlled system via the output interface and actuator, while the controlled variable is sent back to the controller through the input interface using sensors and transmitters. Different systems require different sensors, transmitters, and actuators. For instance, pressure control systems use pressure sensors, whereas electric heating control systems employ temperature sensors. Many PID controllers and their associated devices or intelligent PID controllers (meters) are available today, extensively utilized in practical engineering applications. These controllers come in various forms, and major companies have developed numerous PID solutions. Intelligent regulators with parameter self-tuning capabilities use intelligent adjustments or self-correction, adaptive algorithms to automatically tune the PID controller parameters. Pressure, temperature, flow, and level controllers that use PID control, programmable logic controllers (PLCs), and PC systems capable of implementing PID control are all common examples.
The difference between PI and PID control lies in the additional inclusion of the derivative component in PID control. PID control is referred to as proportional, integral, and derivative control. Its principle involves adjusting the output signal to match the setpoint by using proportional, integral, and derivative actions (referring to the input and output deviation).
Mathematically expressed as: c(t) = ke(t) + t/Tdde(t)/dt + TI/Ts ∫e(t)dt (S: represents the integral symbol).
Here:
- k is the proportional gain, determining the system's responsiveness.
- Td is the derivative time. A smaller value enhances the derivative effect but may impact accuracy.
- TI is the integral time. A larger value amplifies the integral effect but slows down the response.
Proportional control governs the system's responsiveness, the derivative action anticipates errors, and the integral action eliminates steady-state errors but with a slower response.
PID control is the foundational algorithm in industrial production and electronics design, providing effectiveness. However, in scenarios requiring high precision over speed, PI control (proportional and integral control) is often employed.
Its mathematical representation is: c(t) = ke(t) + TI/Ts ∫e(t)dt (S: represents the integral symbol).
In MATLAB, selecting PI controller parameters follows these steps:
1. **Determine the Proportional Gain (Kp):** Start with pure proportional control by setting the integral and derivative terms to zero (TI=0, Td=0). Input should be set to 60%-70% of the system’s maximum allowable output. Gradually increase Kp from zero until oscillations occur, then decrease Kp until oscillations cease. Record this Kp value and set the PID controller's Kp to 60%-70% of this value.
2. **Determine the Integral Time Constant (Ti):** With Kp fixed, start with a large Ti, then decrease it gradually until oscillations occur. Increase Ti again until oscillations stop. Record this Ti value and set the PID controller's Ti to 150%-180% of this value.
3. **Determine the Derivative Time Constant (Td):** Typically, Td is not set and kept at zero. This converts PID control to PI control. If needed, follow the same method as for Kp, setting Td to 30% of its value when no oscillations occur.
4. **System No-Load and On-Load Joint Adjustment:** Fine-tune the PID parameters to meet performance requirements.
For using the PI controller in MATLAB, select the PID block in Simulink and set the D parameter to zero.
Understanding these principles allows users to effectively apply PID control in MATLAB, whether for academic purposes or practical engineering applications.