PID Explained with simple example скачать в хорошем качестве

PID Explained with simple example

Inspired from Brain Douglas's videos. Thanks to him. The following is a demonstration for how a PID control works. For this illustration I have used a DC motor as the actuator and a Hall Effect sensor for the feedback system. PID control: This is the most stable control system which is employed nowadays is the PID controller. This is used in most of the automated driving simulations. The control system's purpose is to make the vehicle follow the required velocity profile. Here the DC motor simulated the traction motor in the automobile. The control system is fed with a constant set speed for the dc motor. The Hall Effect sensor acts as a switch here. There is a small magnet which is mounted eccentrically on the motor's shaft. The Hall Effect sensor switches on and off, with respect to the magnetic proximity. This switching on and off occurs at a certain frequency which is proportional to the motor's RPM. This frequency is compared with the desired frequency (Set RPM of the motor) and the difference gives the error signal. This error signal is fed into the PID control which tries to eliminate the same. The PID controller adopts three mathematical computations to eliminate the error: 1. Proportional gain (P): This will multiply the error with a constant term. So this is responsible to reduce the rise-time of the actual signal with respect to the desired signal. But this cannot ensure that the actual signal gets closer to the steady state value. 2. Derivative gain (D): This parameter differentiates the error value. This increases the stability of the system and this also improves the transient response. This means that the actual signal will reach the desired value at a faster rate. 3. Integral gain (I): This integrates the error. This eliminates the steady state error, but it integrates the noise and error inside the circuit. So stability of the system is greatly compromised.