Data-Driven Iterative Trajectory Shaping for Precision Control of Flexible Feed Drives

With recent advances on material processing technologies, design requirements on modern manufacturing equipment are shifting toward achieving higher speed and accuracy rather than stiffness and load capacity. Motion systems used in additive or ultraprecision manufacturing equipment need to be designed to achieve greater dynamic positioning accuracy. As a result, feedforward (FF) control becomes an effective tool. This article presents a novel and practical FF controller design methodology to widen tracking bandwidth of precision motion systems suffering from structural dynamics and friction-induced disturbances. The proposed feedforward controller is designed to, first, compensate for the closed-loop servo dynamics to widen the command tracking bandwidth, second, mitigate unwanted vibrations, and third, compensate friction disturbance-induced positioning errors. The FF controller is structured in a trajectory prefilter form where the FF compensation signal is injected into the reference trajectory rather than torque command. This facilitates the FF controller to be applied conveniently without intervention with the servo controller. FF controller parameters are identified (tuned) automatically through machine in-the-loop-iterations. Parameter identification is posed as a convex optimization problem to realize safe and reliable auto-tuning. The proposed FF controller and its parameter tuning methodology are tested experimentally on an industrial scale multiaxis machine tool and its performance is validated.