2,544 research outputs found
Design of ternary signals for MIMO identification in the presence of noise and nonlinear distortion
A new approach to designing sets of ternary periodic signals with different periods for multi-input multi-output system identification is described. The signals are pseudo-random signals with uniform nonzero harmonics, generated from Galois field GF(q), where q is a prime or a power of a prime. The signals are designed to be uncorrelated, so that effects of different inputs can be easily decoupled. However, correlated harmonics can be included if necessary, for applications in the identification of ill-conditioned processes. A design table is given for q les 31. An example is presented for the design of five uncorrelated signals with a common period N = 168 . Three of these signals are applied to identify the transfer function matrix as well as the singular values of a simulated distillation column. Results obtained are compared with those achieved using two alternative methods
Time-Domain Analysis of Sensor-to-Sensor Transmissibility Operators with Application to Fault Detection.
In some applications, multiple measurements are available, but the driving input that gives rise to those outputs may be unknown. This raises the question as to whether it is possible to model the response of a subset of sensors based on the response of the remaining sensors without knowledge of the driving input. To address this issue, we develop time-domain sensor-to-sensor models that account for nonzero initial conditions. The sensor-to-sensor model is in the form of a transmissibility operator, that is, a rational function of the differentiation operator. What is essential in defining the transmissibility operator is that it must be independent of both the initial condition and inputs of the underlying system, which is assumed to be time-invariant. The development is carried out for both single-input, single-output and multi-input, multi-output transmissibility operators. These time-domain sensor-to-sensor models can be used for diagnostics and output prediction.
We show that transmissibility operators may be unstable, noncausal, and of unknown order. Therefore, to facilitate system identification, we consider a class of models that can approximate transmissibility operators with these properties. This class of models consists of noncausal finite impulse response models based on a truncated Laurent expansion. These models are shown to approximate the Laurent expansion inside the annulus between the asymptotically stable pole of largest modulus and the unstable pole of smallest modulus. By delaying the measured pseudo output relative to the measured pseudo input, the identified finite impulse response model is a noncausal approximation of the transmissibility operator. The causal (backward-shift) part of the Laurent expansion is asymptotically stable since all of its poles are zero, while the noncausal (forward-shift) part of the Laurent expansion captures the unstable and noncausal components of the transmissibility operator.
This dissertation also develops a time-domain framework for both single-input, single-output and multi-input, multi-output transmissibilities that account for nonzero initial conditions for both force-driven and displacement-driven structures. We show that motion transmissibilities in force-driven and displacement-driven structures are equal when the locations of the forces and prescribed displacements are identical.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113623/1/khaledfj_1.pd
Improving the Accuracy and Scope of Control-Oriented Vapor Compression Cycle System Models
The benefits of applying advanced control techniques to vapor compression cycle systems are well know.
The main advantages are improved performance and efficiency, the achievement of which brings both economic and
environmental gains. One of the most significant hurdles to the practical application of advanced control techniques
is the development of a dynamic system level model that is both accurate and mathematically tractable. Previous
efforts in control-oriented modeling have produced a class of heat exchanger models known as moving-boundary
models. When combined with mass flow device models, these moving-boundary models provide an excellent
framework for both dynamic analysis and control design. This thesis contains the results of research carried out to
increase both the accuracy and scope of these system level models.
The improvements to the existing vapor compression cycle models are carried out through the application
of various modeling techniques, some static and some dynamic, some data-based and some physics-based. Semiempirical
static modeling techniques are used to increase the accuracy of both heat exchangers and mass flow
devices over a wide range of operating conditions. Dynamic modeling techniques are used both to derive new
component models that are essential to the simulation of very common vapor compression cycle systems and to
improve the accuracy of the existing compressor model. A new heat exchanger model that accounts for the effects
of moisture in the air is presented. All of these model improvements and additions are unified to create a simple but
accurate system level model with a wide range of application. Extensive model validation results are presented,
providing both qualitative and quantitative evaluation of the new models and model improvements.Air Conditioning and Refrigeration Project 17
A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends
This paper examines the security vulnerabilities and threats imposed by the
inherent open nature of wireless communications and to devise efficient defense
mechanisms for improving the wireless network security. We first summarize the
security requirements of wireless networks, including their authenticity,
confidentiality, integrity and availability issues. Next, a comprehensive
overview of security attacks encountered in wireless networks is presented in
view of the network protocol architecture, where the potential security threats
are discussed at each protocol layer. We also provide a survey of the existing
security protocols and algorithms that are adopted in the existing wireless
network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term
evolution (LTE) systems. Then, we discuss the state-of-the-art in
physical-layer security, which is an emerging technique of securing the open
communications environment against eavesdropping attacks at the physical layer.
We also introduce the family of various jamming attacks and their
counter-measures, including the constant jammer, intermittent jammer, reactive
jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the
integration of physical-layer security into existing authentication and
cryptography mechanisms for further securing wireless networks. Finally, some
technical challenges which remain unresolved at the time of writing are
summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201
State-space model identification and feedback control of unsteady aerodynamic forces
Unsteady aerodynamic models are necessary to accurately simulate forces and
develop feedback controllers for wings in agile motion; however, these models
are often high dimensional or incompatible with modern control techniques.
Recently, reduced-order unsteady aerodynamic models have been developed for a
pitching and plunging airfoil by linearizing the discretized Navier-Stokes
equation with lift-force output. In this work, we extend these reduced-order
models to include multiple inputs (pitch, plunge, and surge) and explicit
parameterization by the pitch-axis location, inspired by Theodorsen's model.
Next, we investigate the na\"{\i}ve application of system identification
techniques to input--output data and the resulting pitfalls, such as unstable
or inaccurate models. Finally, robust feedback controllers are constructed
based on these low-dimensional state-space models for simulations of a rigid
flat plate at Reynolds number 100. Various controllers are implemented for
models linearized at base angles of attack , and . The resulting control laws are
able to track an aggressive reference lift trajectory while attenuating sensor
noise and compensating for strong nonlinearities.Comment: 20 pages, 13 figure
Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers
PID control architectures are widely used in industrial applications. Despite
their low number of open parameters, tuning multiple, coupled PID controllers
can become tedious in practice. In this paper, we extend PILCO, a model-based
policy search framework, to automatically tune multivariate PID controllers
purely based on data observed on an otherwise unknown system. The system's
state is extended appropriately to frame the PID policy as a static state
feedback policy. This renders PID tuning possible as the solution of a finite
horizon optimal control problem without further a priori knowledge. The
framework is applied to the task of balancing an inverted pendulum on a seven
degree-of-freedom robotic arm, thereby demonstrating its capabilities of fast
and data-efficient policy learning, even on complex real world problems.Comment: Accepted final version to appear in 2017 IEEE International
Conference on Robotics and Automation (ICRA
Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation
New techniques in cross-layer wireless networks are building demand for
ubiquitous channel sounding, that is, the capability to measure channel impulse
response (CIR) with any standard wireless network and node. Towards that goal,
we present a software-defined IEEE 802.11b receiver and CIR estimation system
with little additional computational complexity compared to 802.11b reception
alone. The system implementation, using the universal software radio peripheral
(USRP) and GNU Radio, is described and compared to previous work. By overcoming
computational limitations and performing direct-sequence spread-spectrum
(DS-SS) matched filtering on the USRP, we enable high-quality yet inexpensive
CIR estimation. We validate the channel sounder and present a drive test
campaign which measures hundreds of channels between WiFi access points and an
in-vehicle receiver in urban and suburban areas
Providing structural modules with self-integrity monitoring
With the advent of complex space structures (i.e., U.S. Space Station), the need for methods for remotely detecting structural damage will become greater. Some of these structures will have hundreds of individual structural elements (i.e., strut members). Should some of them become damaged, it could be virtually impossible to detect it using visual or similar inspection techniques. The damage of only a few individual members may or may not be a serious problem. However, should a significant number of the members be damaged, a significant problem could be created. The implementation of an appropriate remote damage detection scheme would greatly reduce the likelihood of a serious problem related to structural damage ever occurring. This report presents the results of the research conducted on remote structural damage detection approaches and the related mathematical algorithms. The research was conducted for the Small Business Innovation and Research (SBIR) Phase 2 National Aeronautics and Space Administration (NASA) Contract NAS7-961
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