This paper proposes a new modeling scheme to describe the hysteresis and the preload characteristics of piezoelectric stack actuators in the inchworm. From the analysis of piezoelectric stack actuator behavior, the hysteresis can be described by the functions of a maximum input voltage and the preload characteristics are identified by the preload weight. The dynamic characteristics are also identified by the frequency domain modeling technique based on the experimental data. For the motion control, the hysteresis is compensated by the inverse hysteresis model. Since the dynamic stiffness of an inchworm is generally low compared to its driving condition, the mechanical vibration may degrade accuracy of the inchworm. Therefore, the SMC (Sliding Mode Control) and the Kalman filter are developed for the precision motion control of the inchworm. The feasibility of the proposed modeling scheme and the control algorithm is tested and verified experimentally.
This paper presents a theoretical development and an experimental validation of a hybrid control algorithm for the active noise control in the rectangular enclosure with lightly damped boundaries. The hybrid control composes of the adaptive feedforward with feedback loop in which the adaptive feedforward control uses the well-known filtered-x LMS(least mean square) algorithm and the feedback loop consists of the sliding mode controller and observer. The hybrid control has its robustness for both transient and persistent external disturbances and increases the convergence speed due to the reduced variance of the filtered-x signal by adding the feedback loop. The sliding mode control (SMC) is used to incorporate modeling errors, disturbances and uncertainties in the controller deign. This paper also investigates the potential of noise control using a smart foam actuator, which is designed to minimize noise passively using an absorption-foam and actively using an embedded PVDF film driven by an electrical input. The error path dynamics is experimentally identified in the form of the auto-regressive and moving-average using the frequency domain identification technique. Experiment results demonstrate the effectiveness of the hybrid control and the feasibility of the smart foam actuator.
This paper presents a methodology to suppress the vibration of thin rectangular plate clamped all edges. Intelligent materials such as the piezoelectric ceramic are used as actuators and sensors. The experimental modeling technique, i.e., the state-space frequency domain identification, is introduced to model the complex shaped structures bonded with noncollocated actuators/sensors. This method is much free from the Multi-Input Multi-Output (MIMO) model order problem caused at the digital implementation and also reduces distortion of the signal. In control scheme, the adaptive feedforward with feedback control algorithm is adopted since it is robust for both the transient and persistent external disturbances. The adaptive feedforward control uses the well known Multiple filtered-x LMS (least mean square) algorithm. The MIMO error path dynamics is controlled by the feedback loop which is constructed by multivariable digital LQG (Linear Quadratic Gaussian) controller composed of the regulator and Kalman filter. Experiment results demonstrate the effective reduction of the vibration label and the robustness for both the transient and persistent external disturbances.
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