In the machining industry, there is a constant need to improve productivity while maintaining required dimensional tolerances and surface quality. The self-excited vibration called chatter is one of the main factors limiting machining productivity. Chatter produces unstable cutting conditions during machining and unstable forces will damage and shorten the life of the machine tool. It can also damage the cutting tool, machining components as well as produce a poor surface finish on the workpiece. Researchers have developed various chatter suppression techniques such as changing process parameters, spindle speeds, and using passive dampers. However, many of these methods are not very robust to changing dynamics in the machine tool due to changing machine positioning, cutting setups, etc. Active vibration damping with a force actuator is a robust method of adding damping by due to its bandwidth and variable controller gains. However, the commissioning of the controller design for the actuators is not trivial and requires significant manual tuning to reach optimal productivity. The research presented in this thesis aims to simplify and automate the controller design process for force actuators.

A frequency domain, sensitivity based automatic controller tuning method for force actuators has been developed. This method uses the measured actuator dynamics and open-loop system dynamics to develop a prediction tool for closed-loop responses without needing to have the complete system model (model free). By monitoring the predicted closed-loop response of various virtually designed controllers, an optimal controller is found amongst the candidate parameter values. The stability of the system and actuator is monitored during the search to ensure that the system is stable throughout its bandwidth that the actuator does not become saturated. The controller is then experimentally tested to ensure that the predicted output is the same as the real output.

In cases where the system has several vibration modes that are in counter-phase and close in frequency, the model-free approach does not perform well. A more complex model-based control law has also been developed and implemented. The method automatically identifies a transfer function model for the measured open-loop system dynamics and synthesizes mixed-sensitivity optimization based controller to damp out the modes in counter-phase.

In order to verify that the model-based controllers can reduce vibration modes in counter-phase, a small-scale experimental setup was developed to mimic machine tools with vibration modes in counter-phase. A flexure was designed and fabricated. A shaker from Modal Shop is used as an active damping actuator to reduce the flexure’s vibration modes. It was concluded that while the model-based controller synthesis techniques were able to damp the vibration modes in counter phase, the flexure was too simplistic and the model-free controller was able to achieve similar results.