The Twin Rotor System demonstrates the principles of a non-linear MIMO system, with significant cross-coupling. Its behaviour resembles a helicopter but the angle of attack of the rotors is fixed and the aerodynamic forces are controlled by varying the speeds of the motors.
Significant cross-coupling is observed between the actions of the rotors, with each rotor influencing both angle positions. Using MATLAB™ together with the detailed training manuals supplied by Feedback and an Advantech PCI card [which creates an impressive digital control system development environment] the user is guided through the design process using Phenomenological process models, Dynamics analysis, Discrete models identification, Controller design, Controller tests on the model, Controller implementation in real-time applications, Implementation of various control strategies, Data visualisation,
The Phenomenological process models are designed in SIMULINK™ to provide initial models for the user to test. Model linearization is then discussed and the use of simple dynamics analysis – like bode diagrams poles and zeros maps are introduced.
To obtain accurate models Identification procedures incorporating MATLAB™ functions are described. The user has a chance to go step-by-step through the discrete models identification. One of the ‘obtained models’ is used for the Controllers design and PID control is explained. A guide is given for PID controller design, testing, tuning and implementation on the model. Root locus technique is used to illustrate the changes that PID controller tuning inflicts on the control system performance. The designed controllers are prepared in SIMULINK™.
- Classic multivariable system
- Non-linear processes
- Closed loop identification
- High resolution with optical
- 1-Degree of Freedom (DOF)
- PID Stabilising and Tracking
- Horizontal Controller
- 1-DOF PID Stabilising and Tracking Vertical Controller with Gravity Compensation
- 2-DOF PID Stabilising and Tracking Controller
- Parameter Tuning
- Coupled Dynamics Analysis
- Dynamics Decoupling
- Phenomenology Analysis
- Model Identification