Vibration suppression is important for high-precision motion control because positioning accuracy is an essential figure of merit for a servosystem. The paper presents a vibration-suppression method based on improved adaptive optimal arbitrary-time-delay (IAOAT) input shaping. First, analyzing a conventional optimal-arbitrary-time-delay (OAT) input shaper yields an OAT input shaper with five pulses that completely suppresses two-mode vibrations when the natural frequency and damping ratio are exactly known. Next, embedding an adaptive algorithm in the shaper gives a conventional adaptive optimal arbitrary-time-delay (AOAT) input shaper that handles unknown natural frequencies and damping ratios. Note that the conventional AOAT input shaper contains five pulses that have to be updated, but the delay times of the pulses are prescribed. Then, the IAOAT method extends the symmetry of pulse amplitudes for zero damping ratio to a nonzero case and reduces the number of pulses to three. A recursive-least-squares (RLS) algorithm is devised to update these parameters. This shaper features the smallest number of parameters and high robust performance. Finally, comparisons with other input-shaping methods show the effectiveness and superiority of the developed method over others.

This paper presents a vibration suppression method for two-inertia mechanical transmission systems, combining adaptive horizon model predictive control (AHMPC) with the equivalent-input-disturbance (EID) approach. First, conventional model predictive control (MPC) is extended to an adaptive horizon formulation to reduce computational cost while effectively attenuating vibrations. Second, a quadratic-programming-based method is designed to efficiently solve the AHMPC optimization problem. Third, the EID approach is integrated to compensate for external disturbances. Finally, simulation studies on a two-inertia system demonstrate the effectiveness of the proposed method in achieving significant vibration suppression.

This paper presents a torque oscillation attenuation method for permanent magnet synchronous motors (PMSMs) based on the combination of sliding-mode control (SMC) and the equivalent input disturbance (EID) approach. To deal with the changes in PMSM parameters, we explored a continuous-domain ant colony optimization (CDACO) method to design a control system for such a plant. This is the first application of SMC-EID to uncertain PMSM plants, with CDACO enabling robust parameter tuning in continuous spaces. First, we designed an EID estimator to estimate the disturbance caused by torque oscillation. Next, we added the estimated disturbance to the sliding-mode controller to improve disturbance attenuation performance. Then, we extended an ant colony optimization (ACO) algorithm to the continuous domain to optimize controller parameters for an uncertain plant. Finally, a speed control experiment was carried out on a two-mass experimental system for PMSMs to demonstrate the validity of the method. The experimental results show that our method yields better control performance than the SMC.