A general modeling scheme is proposed for precision positioning of piezoelectrically-driven flexural systems. To
describe the nonlinear behavior of the structure while also considering the system dynamics, a second order linear
dynamic model subjected to nonlinear hysteretic input is first adopted. Using the memory-dependent properties of
hysteresis nonlinearity, a new mathematical framework is then proposed for describing this phenomenon. More
specifically, a nonlinear mapping strategy is proposed for the approximation of each of the ascending and descending
multiple-loop hysteresis curves based on the shape of hysteresis reference curves. The trace of internal hysteresis
trajectory is, however, obtained based on the locations of the past turning points, corresponding to the input extrema.
Experimental tests are carried out on a dual-axis piezoelectrically-driven flexural stage to demonstrate the contribution
of dynamic and hysteresis models, individually and combined together, on the improvement of the model response.
Results indicate that the proposed hysteresis model can effectively predict the nonlinear response of the system, while
the influence of dynamic model is more apparent for high rate inputs.
The dynamic equations of piezoelectric benders are studied in this paper, considering nonlinear behavior of
piezoceramics. A second order approximation of constitutive equations of piezoceramics is used to account for
reversible nonlinearities. Transversal and longitudinal deflections at the tip of the beam and the blocking force as well
as sensor equations (output charge as a function of external loads) are obtained under static conditions. The static
equations are then used to construct a linear dynamic model for actuation. A Bouc-Wen type hysteresis model is
employed in order to account for the irreversible nonlinearities. The final equation of motion is in the form of well-known
Hill's equation.
Unlike widely-used carbon nanotubes, boron nitride nanotubes (BNNTs) have shown to possess stable semiconducting
behavior and strong piezoelectricity. Such properties along with their outstanding mechanical properties and thermal
conductivity, make BNNTs promising candidate reinforcement materials for a verity of applications especially
nanoelectronic and nanophotonic devices. Motivated by these abilities, we aim to study the buckling behavior of BNNT-reinforced
piezoelectric polymeric composites when subjected to combined electro-thermo-mechanical loadings. For
this, the multi-walled structure of BNNT is considered as elastic media and a set of concentric cylindrical shell with van
der Waals interaction between them. Using three-dimensional equilibrium equations, Donnell shell theory is utilized to
show that the axially compressive resistance of BNNT varies with applying thermal and electrical loads. The effect of
BNNT piezoelectric property on the buckling behavior of the composites is demonstrated. More specifically, it is shown
that applying direct and reverse voltages to BNNT changes the buckling loads for any axial and circumferential
wavenumbers. Such capability could be uniquely utilized when designing BNNT-reinforced composites.
A new actuation mechanism utilizing piezoelectric properties of boron-nitride nanotube (BNNT) for microcantilever
beams is proposed here and modeled using a multiple-scale, multi-physic approach. Using the developed model, specific
attention is placed on thermal effects on the microbeams made of aluminum and titanium and the results are compared
with each other. Different studies are conducted on the microbeams response characteristics such as frequency response,
resonance frequency and heat transition effects while the microbeam tip temperature varies. It is found that Titanium
microbeam possesses smaller peak frequency response that occurs at lower frequency. Also, it is demonstrated that
increasing the temperature will lower resonance frequency in both beams. Finally, the temperature gradient through the
beams with respect to time is studied and it is found that Titanium beam can be stabilized in a longer time period.
KEYWORDS: Actuators, Nanomanipulation, Kinematics, Adaptive control, Process control, Numerical simulations, Scanning tunneling microscopy, Nanoparticles, Systems modeling, Control systems
This paper presents the modeling and memory-based robust adaptive control of a variable length stepping
nanomanipulator. A three degree of freedom (3DOF) nanomanipulator with revolute revolute prismatic (RRP) actuator
structure, namely here MM3A, is utilized for a variety of nanomanipulation tasks. Unlike widely used Cartesian-structure
nanomanipulators, the MM3A is equipped with revolute-piezoelectric actuators which result in outstanding
performance for controlling the nanomanipulator's tip alignment during the nanomanipulation process. However, the
RRP structure of the nanomanipulator introduces complicity in kinematic and dynamic equations of the system which
needs to be addressed in order to control the nanomanipulation process. Dissimilar to the ordinary piezoelectric actuators
which provide only a couple of micrometers working range, the piezoelectric actuators utilized in MM3A, namely
Nanomotors, provide wide range of action (120° in revolute actuators and 12mm in prismatic actuator) with sub-nano
scale precision (0.1 μrad in revolute actuators and 0.25 nm in prismatic actuator). This wide range of action combined
with sub-nano scale precision is achieved using a special stick/slip moving principle of the Nanomotors. However,
such stick/slip motion results in stepping movement of the MM3A. Hence, due to the RRP structure and stepping
movement principle of the MM3A nanomanipulator, controller design for the nanomanipulation process is not a trivial
task. In this paper, a novel memory-based robust adaptive controller is proposed to overcome these shortfalls. Following
the development of the memory-based robust adaptive controller, numerical simulations of the proposed controller are
preformed to demonstrate the positioning performance capability of the controller in nanomanipulation tasks.
In this paper the problem of coupled flexural-torsional nonlinear vibrations of a piezoelectrically-actuated
microcantilever beam is investigated considering beam's simultaneous flexural, torsional and longitudinal vibrations.
Application of such problem is utilized in several nanotechnological instruments such as atomic force microscopy,
nanomechanical cantilever sensors and friction force microscopy. The actuation and sensing are both facilitated through
bonding a piezoelectric layer (here, ZnO) on the microcantilever surface. The piezoelectric properties combined with
nonlinear geometry of the beam introduce both linear and nonlinear coupling between flexural vibration as well as
longitudinal and torsional vibrations. The governing equations of motion are obtained with piezoelectric nonlinearity
appearing in quadratic form while inertia and stiffness nonlinearities as cubic. An experimental setup consisting of a
commercial piezoelectric microcantilever installed on the stand of an ultramodern laser-based microsystem analyzer is
designed and utilized to verify the theoretical developments. First and second flexural natural frequencies are both
experimentally and numerically obtained and are shown to be in good agreement. Both linear and nonlinear simulation
results are compared with experimental results and it is observed that nonlinear modeling response matches the
experimental findings very closely.
The dynamics of a self-sensing microcantilever beam for mass sensing applications are presented. The microcantilever is assumed to be uniform and obeying the Euler-Bernoulli beam theory assumptions. The beam possesses an unknown tip mass to be measured and a piezoelectric patch actuator deposited on the cantilever surface. The actuator is operated in a self-sensing mode, in the sense that the same piezoelectric patch is used to simultaneously actuate the beam and
sense the voltage induced due to beam vibrations. A balanced impedance bridge is used to supply voltage to the piezoelectric actuator and to read the induced voltage. Mathematical models for this mechatronic system actuated through a pure capacitive and a resistive-capacitive bridge network are derived. Equations of motion are obtained using the Hamilton's principle by considering the microcantilever as a distributed-parameters system. A technique to estimate the unknown tip mass, based on the inverse solution to the characteristic equation problem is presented along with sensitivity analysis of the unknown mass with respect to the characteristic equation parameters. A closed-form solution for the determination of unknown tip mass is obtained which has many advantages over numerical estimation methods in a widespread mass sensing application.
Complex structural nonlinearities of piezoelectric materials drastically degrade their performance in variety of micro-
and nano-positioning applications. From the precision positioning and control perspective, the multi-path time-history dependent hysteresis phenomenon is the most concerned nonlinearity in piezoelectric actuators to be analyzed. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligent properties of hysteresis with the effects of non-local memories are discussed. Through performing a set of experiments on a piezoelectrically-driven nanostager with high resolution capacitive position sensor, it is shown that for the precise prediction of hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the system everpresent nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect if memory units are sufficiently chosen for the inverse model.
Nanocrystals and nanostructures will be the building blocks for future materials that will exhibit enhanced or entirely new combinations of properties with tremendous opportunity for novel technologies that can have far-reaching impact on our society. It is, however, realized that a major challenge for the near future is the design, synthesis and integration of nanostructures to develop functional nanosystems. In view of this, this exploratory research seeks to facilitate the development of a controlled and deterministic framework for nanomanufacturing of nanotubes as the most suitable choice among nanostructures for a plethora of potential applications in areas such as nanoelectronic devices, biological probes, fuel cell electrodes, supercapacitors and filed emission devices. Specifically, this paper proposes to control and maintain the most common nanotube growth parameters (i.e., reaction temperature and gas flow rate) through both software and hardware modifications. The influence of such growth parameters in a CVD process on some of the most vital and crucial aspects of nanotubes (e.g., length, diameter, yield, growth rate and structure) can be utilized to arrive at some unique and remarkable properties for the nanotubes. The objective here is, therefore, to control the process parameters to pinpoint accuracy, which would enable us to fabricate nanotubes having the desired properties and thereby maximize their ability to function at its fullest potential. To achieve this and in order to provide for experimental validation of the proposed research program, an experimental test-bed using the nanotube processing test chamber and a mechatronics workstation are being constructed.
Electro-active polymers reinforced with carbon nanotubes have attracted many researchers in the recent years. Recent activities in this area show that conducting polymers with carbon nanotubes in an electrolytic medium possess actuation and sensing properties due to the change in bond length in the carbon atoms. However, their applications are limited due to their operation in a wet medium. In this paper, we explore the feasibility of electro-active polymers with dispersed carbon nanotubes that can be used for actuation and sensing in a dry medium like air to make them viable. Different polymer composites are considered for mixing with single-walled and multi-walled carbon nanotubes manufactured by chemical vapor deposition technique. Various dispersing techniques for aligning the carbon nanotubes like smart blending and chaotic mixing are also explored. The feasibility of actuation and sensing of these composites are verified by experimentation on several macrosystems comprised of these functional nanostructures.
In many structural vibration control applications, strain sensors play a key role in the design and implementation of the vibration controller. Different types of sensors are commercially available, among which is the poled polyvinylidene difluoride (PVDF), an attractive sensor for large bandwidths and low costs. Despite such attractive features, PVDF-based sensors have limited use due to their low efficiency (mechanical energy to electrical energy conversion factor). To remedy this, nanocrystals and nanostructures have been recently cited as candidate materials that can be engineered to exhibit enhanced or entirely new properties for use in different applications. Particularly, carbon nanotubes (CNTs) have raised considerable interest in the scientific community due to their size and wide range of outstanding material properties. Given the moduli and strength values of CNTs, they are ideal filler materials for high performance (polymer) composite materials with unbeatable modulus-to-weight and strength-to-weight ratios -- the attributes that are essential for structural vibration control of a wide variety of industrial equipment and systems. Along this line of reasoning, this paper undertakes the development and implementation of a novel sensor paradigm based on proper fusion of CNTs with PVDF materials.
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