PID Controller Design | Tuning the Gains with MATLAB

Develop a mathematical model of a DC motor linking voltage, current, and torque through transfer functions, then simulate in MATLAB to analyze speed control with feedback.

Understand the mathematical model of the PID controller for MATLAB simulations. Develop a custom PID using KP, Ki, and Kd to tune performance.

Identify dc motor parameters and inertia to design a P.A. controller in MATLAB for a speed control system, achieving at most 1% steady-state error and settling time under two seconds.

Develop a simple dc motor simulation model using a transfer function in a continuous block and study its response to a step input, focusing on settling time and steady-state error.

Develop a simulation model of a pid controller with kp, ki, and kd gains, using summation, integrator, derivative, and saturation blocks for a dc motor.

Connect the DC motor model with the velocity controller to form a closed-loop speed control system, reuse and tune the predeveloped controller, observe how gain and limit settings affect response.

Tune kp, ki, and kd gains of a pd controller in MATLAB to achieve a desired speed response, reducing steady-state error and settling time while managing saturation and voltage limits.

Vary Kp and Ki to observe effects on steady-state error, settling time, and peak overshoot; increasing the gap reduces state error and settling time but raises overshoot.

Explore live tuning of pid gains using an interactive slider to adjust kp and ki, observe effects on steady-state error and overshoot in a simulated response.

Observe the live tuning of pid gains with a pulse and step input to see how kp and ki influence initial performance, overshoot, and settling time.

The lecture shows how load torque alters PID controller performance, with higher load lengthening settling time and necessitating retuning of the PID gains.

Design and tune a closed-loop dc motor speed controller in MATLAB, modeling inductance, resistance, inertia, and friction, with a 40 V limit to achieve fast settling and minimal overshoot.

Demonstrates a 12 v dc-dc step-down converter for ev applications with a closed-loop controller regulating output from a 72–90 v battery to 12 v, using pwm and mosfet switching.

Explore cruise control for a vehicle using a simple mass–friction model and a MATLAB feedback controller to maintain set speed amid disturbances, with saturation and open- and closed-loop tuning.

Explores modeling a first-order system in MATLAB, formulating a transfer function, solving differential equations, and simulating open-loop step responses, then incorporating the KPK to study its effects.

Analyze how a proportional controller is implemented in MATLAB to derive closed-loop transfer functions, compare with open-loop, and study step responses as the gain kp varies.

Design and tune pid controllers in MATLAB by analyzing the transfer function of a second-order closed-loop system, exploring step responses, oscillations, and tuning kp and ki gains.

Apply MATLAB's autotune function to design and tune a PID controller, adjusting Kp, Ki, Kd and filter settings to achieve desired settling time and response in cruise control.

Explore the applications of PID controllers for single-input single-output and multi-input multi-output systems, including water flow, temperature, pressure, and magnetic levitation, with emphasis on gain tuning and state-based modeling.

Explore how proportional, integral, and derivative gains shape the closed-loop response in PID tuning with MATLAB, balancing steady-state error and transient performance.