Many forced systems are prone to undesirable levels of oscillation if lightly damped modes are present with their frequency range of operation. Rotary systems, for example, can experience these problems during the speed up or speed down stage of operation. Resonant motion can damage or effect the accuracy of operation of such systems and is, therefore, highly undesirable. Many closed-loop controllers avoid this by suppressing the mode itself such that at resonance the modal vibration amplitude is small (i.e. highly damped). The current work presents an alternative novel switching controller, which suppresses the system not by applying a high amount of damping but rather by moving the resonant mode such that it is never excited. From the basis of an accurate plant model, two pole-placement controllers are designed and implemented both in simulation and experiment on a cantilever smart structure. These controllers are shown to successfully change the natural frequency value, while retaining the same damping ratio value. A novel switching system is employed that calculates the optimal switching position by running a simulation of the desired systems in parallel to the controlled open-loop system. Moreover, the system minimises transients occurred by switching back and forth between controllers, thus increasing the efficiency of the system. By comparing the experimental results to a conventional high damping pole-placement controller that applies a similar amount of control effort, a lower overall level of amplitude suppression can be seen.
The ability to model, investigate and control the behavior of dynamic systems in a simulation environment is highly desirable due to time and cost benefits. A new technique has been developed allowing finite element models to be integrated with Simulink for dynamic simulation and control. The technique is presented by the modeling of a fixed-free cantilever beam with bonded piezoelectric patches. A description of the modeling technique is presented detailing the process of model creation, including input and output variable determination, and exportation to Simulink as a state-space model. A comparison of simulated and experimental open-loop behavior is provided. Furthermore the free and forced system behavior both observed, and simulated with velocity feedback controllers (VFB) is presented. Conclusions are drawn regarding the capabilities and restrictions of the developed technique in comparison to modeling using a system identification technique. The author's views on the techniques application to non-linear system modeling and potential for optimizing sensor and actuator locations are presented.