PIDTune vs PID Controller Simulation Utilisation & Stats

PID Tuner uses the IMC (Internal Model Control) method to calculate PID tuning parameters. I’ve tried a lot of tuning methods over the years and have found this one to be the best. The app is written for the iPad to show all the information on one page. The program calculates: PID Parameters: Controller Gain (Kc) Integral Time (Ti) Derivative Time (Td) For process types First Order with Dead Time (FO) Second Order with Dead Time (SO) Integrating or Long Time Constant with Dead Time (I) For controller types Parallel (non-interacting) c(s) = Kc (1 + 1/(Ti s) + Td s) Series (interacting) c(s) = Kc (Ti s + 1)/(Ti s)(Td s + 1) For controller modes PID PI You can either enter the process gain (Kp) directly or enter the changes in the controlled virable (CV) and manipulated variable (MV). Tuning aggression is adjusted using the slider to set the closed loop time constant to the process time constant ratio (λ/Ƭ). The closed loop time constant (λ) is the time the controller is expected to reach set point (plus the dead time (ϴ)). Setting the closed loop time constant to process time constant ratio (λ/Ƭ) to 1.0 will make the MV change to its final value and allow the process to settle out to the setpoint. Setting (λ/Ƭ) greater than 1.0 will give a slower responce. Setting (λ/Ƭ) less than 1.0 will cause the MV to make a larger change and then reduce to its final value. Tight tuning would be to set the close loop time constant to the dead time. Use the Integrating Process type (Ƭ = ∞) for both integrating processes or processes with long time constants. These processes use the maximum slope as the process gain. Tuning aggression for these processes is determined by setting the closed loop time constant to the dead time ratio (λ/ϴ). Once again, setting the closed loop time constat to the dead time gives tight control. References: “Probably the test simple PID tuning rules in the World,” Sigurd Skogestad, Jounal of Process Control, July 3, 2001 “Consider the generalized IMC-PID method for PID controller tuning of time-delay processes,” Y. Lee, S. Park, M. Lee, Hydrocarbon Processing, January 2006

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PID Controller Simulation

PID Controller Assistant - Master the Core of Automatic Control This app is your powerful ally in learning and applying PID control! Whether you're an engineering student, automation enthusiast, or professional engineer, you'll benefit from this tool. Key Features: Clear and concise explanations of core PID control concepts Interactive demonstrations to help you understand PID parameter effects Practical PID tuning guides and tips Simulation support for single-loop systems Learning Content Includes: Relationships between controlled variable, setpoint, and control output Functions and adjustment methods of P, I, and D terms Differences between direct and reverse acting control Concepts of dynamic and static errors Basic methods for PID parameter tuning Special Functions: Visualization of PID response curves Parameter sensitivity analysis tools Case library of common PID application scenarios This project supports the following PID control algorithms: The Positional PID Control Algorithm The Incremental PID Control Algorithm The Integral Separate PID Control Algorithm The Integral Saturation PID Control Algorithm The Gearshift Integral PID Control Algorithm The PID Control Algorithm with Filter The Incomplete Differential PID Control Algorithm The Derivative Ahead PID Control Algorithm The PID Control Algorithm with Dead Zone Whether you want to improve work efficiency or prepare for exams, this app will help you easily master the essentials of PID control.