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A Deformable Model With Cellular Neural Network, Yongmin Zhong, Bijan Shirinzadeh, Gursel Alici, Julian Smith
A Deformable Model With Cellular Neural Network, Yongmin Zhong, Bijan Shirinzadeh, Gursel Alici, Julian Smith
Gursel Alici
This paper presents a new methodology for deformable models by drawing an analogy between cellular neural network (CNN) and elastic deformation. The potential energy stored in an elastic body as a result of a deformation caused by an external force is propagated among mass points by the local connectivity of cells and the CNN dynamics. An improved CNN model is developed for propagating the energy generated by the external force on the object surface. A method is presented to derive the internal forces from the potential energy distribution established by the CNN. The methodology proposed in this paper can not …
Model-Based Adaptive Control Of Piezoelectric Actuation Systems, Hwee Choo Liaw, Denny Oetomo, Bijan Shirinzadeh, Gursel Alici
Model-Based Adaptive Control Of Piezoelectric Actuation Systems, Hwee Choo Liaw, Denny Oetomo, Bijan Shirinzadeh, Gursel Alici
Gursel Alici
This paper proposes a model-based adaptive control methodology for piezoelectric actuation systems to follow specified motion trajectories. This is motivated by a search for an effective control strategy to deal with the problem of parametric uncertainties such as disturbance and hysteresis effects. The proposed adaptive law is formulated by combining a parameter compensator and a conventional PD feedback control for a system to drive its position tracking error converging to zero. The fundamental concept lies in the properties of a quasinatural potential function, which allows a saturated position error function in the control formulation. Implementation of the control law requires …