A Control-Oriented Dynamical Model of Deposited Droplet Volume in Electrohydrodynamic Jet Printing

Electrohydrodynamic jet printing (e-jet printing) is a nascent additive manufacturing process most notable for extremely high resolution printing and having a vast portfolio of printable materials. These capabilities make e-jet printing promising for applications such as custom electronics and biotechnology fabrication. However, reliably fulfilling e-jet printing’s potential for high resolution requires delicate control of the volume deposited by each jet. Such control is made difficult by a lack of models that both capture the dynamics of volume deposition and are compatible with the control schemes relevant to e-jet printing. This work delivers such a model. Specifically, this work introduces a definition of “droplet volume” as a dynamically evolving variable rather than a static variable, and uses this definition along with analysis of high speed microscope videos to develop a hybrid dynamical system model of droplet volume evolution. This model is validated with experimental data, which involves the contribution of a novel technique for extracting consistent droplet volume measurements from videos.

Quasi-static analysis of planar sliding using friction patches

Flat objects lying on a surface are hard to grasp, but could be manipulated by sliding along the surface in a non-prehensile manner. This strategy is commonly employed by humans as pre-manipulation, for example to bring a cell phone to the edge of a table to pick it up. To endow robots with a similar capability, we introduce a mathematical model of planar sliding by means of a soft finger. The model reveals various aspects of interaction through frictional contacts, which can be used for planning and control. Specifically, using a quasi-static analysis we are able to derive a hybrid dynamical system to predict the motion of the object and the interaction forces. The conditions for which the object sticks to the friction patch, pivots, or completely slides against it are obtained. It is possible to find fixed points of the system and the path taken by the object to reach such configurations. Theoretical as well as comprehensive experimental results are presented.

Torque Coordination Control of Hybrid Electric Vehicles Based on Hybrid Dynamical System Theory

In order to reduce the vibration caused by mode switching of hybrid electric vehicles (HEVs) and achieve smooth mode switching, the hybrid input and output automation (HIOA) model of power control system of a parallel HEV is established based on the theory of hybrid dynamical system (HDS). Taking the switching from electric drive mode to hybrid drive mode for example, the torque coordination control is considered, and the performance is compared with the method without the torque coordination by using a rule-based control strategy. The simulation results in AVL Cruise show that, on the premise of ensuring the fuel economy and the emission, the mode switching process becomes smoother with smaller torque fluctuation and better driving comfort by considering the torque coordination.

Maximum Power Tracking and Current Control for Solar Photovoltaic System Applications, Hybrid Dynamical System Approach

The problem of a DC-DC buck converter control to extract the maximum power from a photovoltaic (PV) system is considered in this paper. A controller is proposed based on the hybrid dynamical system approach dealing with both voltage and current control. This approach allows the system to track a desired voltage using the maximum power point tracking (MPPT) algorithm while keeping the output current at a moderate level. The stability of the closed loop of the full system is demonstrated by means of Lyapunov theory. The simulation utilizes realistic PV array parameters obtained using particle swarm optimization (PSO) identification algorithm. Experimental results are also presented showing the good performance of the proposed controller.