This experimental unit forms part of a series of teaching systems developed in collaboration with the Department of Automation and Information Technology at the Harz University of Applied Studies and Research.

  A vehicle with an inverted rod pendulum acts as a mechanical multivariable system. A fuzzy control moves the rod pendulum to the centre position, where it is held in position, and at the same time controls the position of the vehicle.

  A rotary encoder determines the position of the vehicle from the rotation of its wheels. A rotary potentiometer detects the inclination of the pendulum. These sensors supply crisp signals to the fuzzy controller, where the signals are transformed into fuzzy input values and inferenced before being transformed back into a crisp output value. This in turn activates an actuator, the drive motor on the vehicle. The control process is made more difficult by the fact that the vehicle can only move to a limited extent from its original position.

  The RT 124 completes the learning contents from the RT 121 - RT 123 series. This experimental unit is very complex, as the controller has to

activate an actuator using two input variables. The overall solution also has to be fine tuned properly.

  The control algorithms are initially written and simulated in the user-friendly development software FSH-Shell and then compiled to generate microcontroller code. The control strategy can be optimised at a later date.

  A joystick can be used to control the system manually. This allows the degree of difficulty of the control process to be estimated very accurately.

  The well-structured instructional material sets out the fundamentals and provides a step-by-step guide through the experiments.

- Design of an demanding fuzzy control for an

  unstable, coupled multivariable system

  (fundamentals from the experiments with the

  units RT 121 - RT 123 are required)

- Superposition of pendulum stabilisation and

  position control of the vehicle 

- Comparison of different controller structures

- Optimisation of rule base

- Development of a strategy to decide what to do in

  case of conflicting requirements

- Demanding optimisation of control response