Tuning Control Systems

Control System Toolbox lets you systematically tune control system parameters using SISO and MIMO design techniques.

Tuning PID Controllers

Control System Toolbox provides tools for manipulating and tuning PID controllers through the PID Tuner GUI or command-line functions. You can:

•     Use PID objects to represent continuous-time or discrete-time PID controllers in standard or parallel form
•     Automatically tune PID gains to balance performance and robustness
•     Specify tuning parameters, such as desired response time and phase margin

Tuning SISO Controllers

The SISO Design Tool in Control System Toolbox lets you the design and analyze SISO control systems. You can:

•     Design common control components, such as PIDs, lead/lag networks, and notch filters
•     Graphically tune SISO loops using classical tools, such as root locus, Bode diagrams, and Nichols charts
•     Monitor closed-loop responses and performance requirements in real time while tuning your controller
•     Evaluate design factors, such as choice of sample time and controller complexity

In addition to standard model representations, such as transfer function and frequency-response data, the SISO Design Tool supports systems with time delays. You can also work with several plant models simultaneously to evaluate your control design for different operating conditions.

Simulink Control Design extends Control System Toolbox by enabling you to tune controllers in Simulink that consist of several SISO loops. You can close SISO loops sequentially, visualize loop interactions, and iteratively tune each loop for best overall performance. Simulink Control Design lets you export the tuned parameters directly to Simulink for further design validation through nonlinear simulation.

When used with Simulink Design Optimization™, the SISO Design Tool lets you optimize the control system parameters to enforce time and frequency-based performance requirements. When used with Robust Control Toolbox, it lets you automatically shape open-loop responses using H-infinity algorithms.

Tuning MIMO Controllers

Control System Toolbox supports established methods for MIMO design, including LQR/LQG and pole-placement algorithms. It also provides tools for designing observers, including Kalman filters.

PID Control with MATLAB and Simulink

Design and implement PID controllers

PID tuning and implementation involve 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

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 and fine-tune your design interactively
•     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