AUTOMATION 21XX

• Batch fabrication and manufacturing processes to ensure cost effectiveness and miniaturization.
• Application and problem-oriented approaches to address needs in medical applications.
• Target the whole systems in solving medical issue and addressing patient’s needs and surgical/treatment procedures.
• System configurations include telemetry, micropumps, chemical sensors, physical sensors, electrodes, optical interrogation, magnetic interrogation, fiber optics, MEMS sensors and actuators, microrobotics and control mechanism.

Accomplishments:

• Demonstration of in vivo near infrared fiber optics scanning probes for brain tissue imaging, artery imaging, skin cancer early detection, active endoscopy and retinal detachment and retinoschisis diagnosis.
• Demonstration of miniature impedance and pH sensors for GERD (gastroesophageal reflux disease) monitoring.
• Demonstration of sensors on flexible substrates for implants.
• Micropackaging and demonstration of safe implantable drug delivery systems.
• Demonstration of wireless chemical and physical sensors. Applications include prevention of sudden infant death syndrome (SIDS) and for senior/patient homecare.
• Demonstration of integrated pain management by neurostimulation.
• Design and demonstration of integrated bandages for wound healing

Approach:

• Metal – ceramic composite actuators.
• Low – profile ceramic fiber composites.
• Piezoelectric motors.

Accomplishments:

• “Piezo-Bow” actuator which exhibits high displacement and high blocking force at low frequencies was designed, analyzed and fabricated. The structure consist of a piezoelectric bar poled along the length with metal caps attached to the two major faces of the bar bounded by steel blocks.
• In frequency ranges below 2 kHz, a linear displacement of 8 mm at an applied field of 3.3 V/mm was obtained. The actuator size was 7x7x30 mm³ and exhibited stresses of the order of 30 MPa.
• Experiments are in progress to design and fabricate PZT fiber based composites which can provide high blocking force. Such actuators will find immediate

• Piezoelectric transformers with drive circuit/charger systems have enormous potential to reduce bulky electromagnetic transformers, increase energy efficiency and reduce the dollar cost per unit.
• Exhibit huge power densities, in the order of 40 W/cm³.
• 96%-98% efficiency range require no heat sinks.
• Provide true power isolation and eliminate stray magnetics.

Accomplishments:

• A multi-layer piezoelectric voltage and power transformer which has one direction poling, operates in a wide-frequency range and delivers both step-up and step-down voltages by inverting the electrical connections has been developed, characterized and implemented.
• A complete equivalent circuit model and FEM model for the above design has been developed and used to verify the experimental results.

Approach:

• Inter-digitated electrode to detect capacitance changes.
• Deposited organic polymer films, highly selective to the target gas.
• Packaging with embedded electronics to improve sensitivity and SN ratio.

Accomplishments:

• Microfabricated electrode array and wirebonded package.
• Completed gas sensor testing infrastructure with PPB-levels gas mixing and flow control system.

Approach:
Various structures are being experimented to analyze the magnetoelastic coupling in the ferromagnetic – ferroelectric composites.

Approach:

• Deployment of large numbers of sensors using heterogeneous robotic platforms including inexpensive ARRI-Bots.
• Use of a Potential Fields (PF) approach to achieve mobility subject to communication bandwidth, energy and navigation/collision.
• Use of Extended Kalman Filter (EKF) for information gathering, localization and navigation.
• Use of a Discrete Event Controller (DEC) for resource allocation and mission planning.
• Data logging and supervisory control using Labview for managing and visualization of sensor networks.
• Platform independent algorithms: Land, Aerial, Underwater.
• Adaptive Sampling (AS): Efficient, information-driven sensor deployment.

Types of Deployment Algorithms:

• Communication-Aware deployment consisting of dynamic sensor repositioning in the presence of network communication constraints.
• Information-Aware deployment consisting of optimal placement of mobile sensors to gather the most information.
• Mission-Aware deployment consisting of resource coordination to accomplish a common mission.
• Energy-Aware deployment consisting of conservation and harvesting of energy for sensor network sustainability.

Approach:

• High strain elastomer materials are selected as polymeric substrates.
• Piezoelectric fiber composite actuators are embedded in the elastomer.
• Micro sensors and fluidics are arrayed in the elastomer matrix.
• Integration with microelectronics, digital signal processors and wireless communications.

Accomplishments:
Pictures below shows the porous structure of the silicone based elastomer and the same material after embedding the sensors and actuators. Flexibility of the elastomer matrix is not affected by the micro piezoelectric actuators.

• A meso-micro-nano assembly platform for MEMS millimeter to micron part sizes and nanometer tolerances. This platform uses microrobots built on a wafer.
• A micro-nano assembly system built using these microrobots.

MEMS grippers and fasteners made from various materials are used to assemble cm-size complex MEMS such as the micro-spectrometer die shown above.
 

Accomplishments:

• Microgripper, passive and active micro snap-fastener technology for MOEMS assembly.
• Successful assembly of heterogeneous MEMS and MOEMS: interferometer, spectrometer, safe & arm devices, fiber arrays, fiber interconnects, PIN diodes, and many others.
• Reliable automated handling of parts with dimensions as low as tens of microns, and sub-micron feature sizes.
• Modeling and motion control for electrostatic and thermal MEMS.
• Significant performance improvement of MEMS devices via open or closed loop control. Input shaping and closed-loop control of MEMS with applications in VOA, MEMS switching and other optical and RF-MEMS.

Approach:

• Wafer and die-level stacking and interconnects of electronics, MEMS, optics, and fluidics.
• Vertical interconnects between stacks including electrical, fluidic and optical connectivity.
• Multifunctional integration of components enables modular architectures.

Simultaneous BCB wafer bonding and 3D interconnect formation.

Accomplishments:

• Wafer bonding using BCB for microfluidic packaging.
• Die stacking using fluxless soldering.
• Simultaneous bonding and interconnects using BCB and SnAu microbumps.
• Packaging of microdevices such as implantable drug delivery systems and S&A devices.

• Analysis of Lead-free solders for Electronic devices.
• Shear/tensile/vibration testing of MOEMS and microfluidic devices.
• Reliability of fluxless soldering for hermetic packaging.

Approach:

• Low cost flexible substrates using polymer molding.
• Embedded microvalves to measure fluid volume, direct flow and sequence discrete flow control.
• Reconfigurable circuit construction by assembly of modular components on a platform substrate.

Accomplishments:

• Fluidic interconnection using PDMS molded adapters.
• Pneumatic pressure controlled microvalves.
• Manipulation of discrete volume fluid using fluidic gates.
• Modular microfluidic platform design, fabrication, and integration.

• Develop piezoelectric devices using MEMS technology and targeting applications to sensors, actuators, and power generators.
• Develop piezoelectric materials and deposition processes compatible with flexible substrates.
• ARRI MEMS software design and simulation tools include Intellisuite's Piezo MEMS library.

• Sol-gel process for deposition of BaTiO3 and Pb(Zr,Ti)O3 thin films.
• Novel lithography and etching techniques to realize complex structures.
• Combination of heterogeneous materials on the same substrate.

• Develop improved methods for intelligent automated Diagnostics and Prognostics for engineered machinery, aerospace, and vehicle systems
• Provide a unified and rigorous framework for computer-aided Condition-Based Maintenance (CBM) and Prognostics & Health Management (PHM) based on wireless sensor networks

• Use biologically inspired control system structures based on neural networks, decision-making, and linguistic fuzzy logic to avoid the need for exact system descriptions, to avoid full internal state measurements, and to deal with incomplete knowledge of disturbances.
• Formal derivation of digital control system structures with learning features for implementation on computer microcontroller systems.
• Feedback Linearization that allows the control of systems with high-frequency flexible modes such as vehicle suspension vibration, fuel slosh, tank gun barrel vibration, aircraft flutter, computer disk drive oscillations and windage. Neural networks allow learning of unknown effects.
• Dynamic Inversion with a neural network learning feature for effective compensation of actuator deadzones, uncertainties, and disturbances.
• Nonlinear Lyapunov proof extension methods to determine control system structure and neural network learning schemes that guarantee closed-loop performance of intelligent controllers in the presence of uncertainties and disturbances.
• High-level performance critic methods for updating control system parameters through real-time learning techniques.
• Backstepping methods using Neural Networks to learn unknown dynamics. This allows effective control of coupled systems with more degrees of freedom than control inputs by using the system structure properties.
• Adaptive Fuzzy Logic methods to allow dynamic focusing of controller awareness on regions where more performance activity is needed.
• Actuator feedforward compensation controllers that incorporate neural network or fuzzy logic components to offset the effects of unknown backlash, deadzone, and friction.
• Nearly optimal control design using solution of nonlinear controller design equations using neural network approximators.
• Development of robust output-feedback learning controllers that operate effectively with reduced measurement information about the system state.
  Accomplishments:
• New learning control systems have been developed, simulated on computers, and implemented on DoD, vehicle, and industry platforms. These systems significantly improve the performance and control of modern high-performance systems.
• Development of high performance nonlinear control system for MEMS optical switch.

• Develop improved supervisory control systems for event-based systems including manufacturing workcells, wireless sensor networks, battlefield command and communication, and dynamic resource assignment.
• Provide a rigorous and streamlined framework for mission planning, task sequencing, and real-time resource assignment that allows analysis of performance, computer simulation & verification, and fast implementation of effective supervisory controllers on actual task/resource systems.

Approach:

• Discrete event controller based on matrices for efficient design, computer simulation, and implementation.
• Matrix Graphical User Interface for ease of mission programming and resource assignment.
• Incorporation of the Steward Task Sequencing matrix and the Resource Requirements matrix into a rigorous mathematical framework to calculate the next jobs to perform and assign the required resources dynamically.
• Measurement of events, sensor readings, available resources, and tasks accomplished in the discrete event system, and formal computation of the next activities needed using a simplified feedback controller structure.
• Analysis to determine the onset of blocking phenomena such as deadlock and throughput delay, and computation of blocking avoidance tactics.
• Relation of our Matrix Feedback Controller with standard tools such as Petri Nets and Max-Plus Algebra, which are more difficult to implement on actual systems but have a good theoretical foundation.
• Implementation of Graphical User Interfaces in LabVIEW for easy design for discrete event systems, including mission planning, task sequencing, and resource pool assignment.
• A higher-level outer loop for priority task assignment, Quality of Service, and User Selected dispatching.
• Programming of manufacturing workcells and wireless sensor networks remotely over the internet.

Accomplishments:

• A new Matrix Framework has been developed for discrete event supervisory control, including task assignment and dynamic resource assignment.
• The matrix framework allowed development of a new supervisory controller that allows fast design, mission planning, computer simulation, and actual implementation.
• A US patent has been received.
• Publication of a book on Discrete Event Control and numerous scientific papers.
• NSF grant received for work with Mexico universities to program robot workcells over the internet using the new controller.
• Two Army Research Office contracts received, one for research in discrete event control, and one DURIP to buy equipment for a Wireless Sensor Networks Lab at ARRI.
• With our method, it is now as easy to deploy and program a wireless sensor network as it is to program a PC.
• A wireless sensor network has been developed for Condition-Based Maintenance of a machinery room, including equipment monitoring, fault diagnosis, and health prognosis using advanced decision schemes.
• Implementation of our DE controller on a robotic manufacturing workcell at ARRI.
• Implementation of our DE controller on a wireless sensor network for environmental monitoring and area security at ARRI.
• International collaboration with leading researchers and institutes in Europe and China
• Development of an ARRI Outreach program including local high school Teacher Development, and summer programs for top local students
• Founded local Dallas/Fort Worth IEEE Control systems Society Chapter in 1994