Input Design for Systems Under Identification Using Indirect and Direct Methods

The motivation for system identification can be manifold. In this work, the provocation to identify unknown system characteristics is derived from the control engineering point of view. That is, one intends to design a control strategy based on the identified system properties. The used system identification methods are the Open-Loop Kalman filter System Identification method (OKID) and the Closed-Loop System Identification method (CLID). It is shown that the quantitative largest error of the system identification is given by its model representation, that is the attempt to describe a system with model parameters which poses a linear relationship with the input/output data. Parameter identifiability is reduced to the problem of consistent estimation. The identifiability is largely determined by the way the system is excited, and in addition by the output of the system for the indirect system identification. A quantitative comparison between the indirect and direct system identification method is given, where indirect system identification showed to be slightly superior in accuracy if a suitable controller is selected. The example models used in the comparison are a heat-mass transfer model, a macro economical model, a structural model, NASA\u27s Large-Angle Magnetic Suspension Test Facility (LAMSTF), and a human respiratory system. The problem of defining the input data such that accuracy and identifiability are increased is addressed and controller design criteria can be developed from it. The excitation input is calculated from input/output data and substituted into the current input. Simulations indicate that only a few substitutions are necessary to successfully identify the system. The new input design results in very accurate identification with reduced noise influence and data length requirement. Controller design criteria can be formed based on the input design, such that identification leads to more accurate and more reliable results

Diabetic Patients Foot Care Using Smart Materials to Prevent Ulcerations/Amputations

A major cause of illness and disability in diabetic patients is complications affecting the lower limbs, particularly the feet where loss of feeling may result in ulcerations, and ultimately to partial or total amputation. Traditional remedies for this problem still remains in measuring the foot pressures and then designing a passive shoe insert that absorbs the high pressures. This process may then be repeated multiple times during the lifetime of the patient. This paper describes the conceptual design of an automatic system that monitors and controls the pressure levels in diabetic patients’ feet in real time. The scheme is based on the constant measurement of pressure levels and then actively changing the shape of the shoe insert so as to decrease the high pressure levels. The sensing and the actuation is done by the use of smart materials powered by a battery pack in the insert. The sensing is done by using piezoceramic patches while the actuation is done by use of electroactive polymer (EAP) actuators. All the circuitry is envisioned to be on a single VLSI chip embedded in the shoe insert, hence making the shoe insert completely autonomous. The greatest strength of the system is that it is an active real time system that will adapt to changes in the locations of high stress points, and, hence, is far superior to currently used passive shoe inserts and other forms of diabetic foot care

The role of string-like, supramolecular assemblies in reentrant supernematic liquid crystals

Using a combination of isothermal-isobaric Monte Carlo and microcanonical molecular dynamics we investigate the relation between structure and self-diffusion in various phases of a model liquid crystal using the Gay-Berne-Kihara potential. These molecules are confined to a mesoscopic slit-pore with atomically smooth substrate surfaces. As reported recently [see M. G. Mazza {\em et al.}, Phys. Rev. Lett. {\bf 105}, 227802 (2010)], a reentrant nematic (RN) phase may form at sufficiently high pressures/densities. This phase is characterized by a high degree of nematic order and a substantially enhanced self-diffusivity in the direction of the director $\hat{\bm{n}}$ which exceeds that of the lower-density nematic and an intermittent smectic A phase by about an order of magnitude. Here we demonstrate that the unique transport behavior in the RN phase may be linked to a confinement-induced packing effect which causes the formation of supramolecular, string-like conformations. The strings consist of several individual molecules that are capable of travelling in the direction of $\hat{\bm{n}}$ as individual "trains" consisting of chains of molecular "cars". Individual trains run in parallel and may pass each other at sufficiently high pressures.Comment: 24 page

A Genetic Algorithm Approach for Model Reference Adaptive Control of Ionic Polymer Metal Composites

Electroactive polymers undergo physical deformation to external voltage stimuli. These electrically activated polymers possess extraordinary features making them capable as lightweight sensors and actuators in manifold applications. The characteristics of applied voltage and environmental conditions, especially the moisture content surrounding the polymer, have a combined influence on the dynamical behavior of these polymers. In order to characterize these polymers under varying environmental conditions, this paper discusses the experimental procedure and modeling techniques used to derive a representative model. Ionic polymer metal composite polymers are used for this humidity relative electrodynamical study. Insight on the numerous applications of electroactive polymers as actuators and the built model enabled a controller is designed for a typical tracking problem. The control architecture includes a model reference adaptive scheme along with pole-placement control strategies to achieve the goal of tracking. A genetic algorithm approach is implemented to carryout an optimized control action. Tracking control of ionic polymer metal composites as actuator resembling that of a real-world scenario is simulated and reveals promising results

Application of System Identification for Modeling the Dynamic Behavior of Axial Flow Compressor Dynamics

Identification of a one-stage axial compressor system is addressed. In particular, we investigate the underlying dynamics of tip air injection and throttle activation to the overall compressor dynamics and the dynamics around the tip of the compressor blades. A proposed subspace system identification algorithm is used to extract three mathematical models: relating the tip air injection to the overall dynamics of the compressor and to the flow dynamics at the tip of the compressor blade and relating the movement of the throttle to the overall compressor dynamics. As the system identification relays on experimental data, concerns about the noise level and unmodeled system dynamics are addressed by experimenting with two model structures. The identification algorithm entails a heuristic optimization that allows for inspection of the results with respect to unmodeled system dynamics. The results of the proposed system identification algorithm show that the assumed model structure for the system identification algorithm takes on an important role in defining the coupling characteristics. A new measure for the flow state in the blade passage is proposed and used in characterizing the dynamics at the tip of the compressor blade, which allows for the inspection of the limits for the utilized actuation

A hybrid adaptive control strategy for a smart prosthetic hand

This paper presents a hybrid of a soft computing technique of adaptive neuro-fuzzy inference system (ANFIS) and a hard computing technique of adaptive control for a two- dimensional movement of a prosthetic hand with a thumb and index finger. In articular, ANFIS is used for inverse kinematics, and the adaptive control is used for linearized dynamics to minimize tracking error. The simulations of this hybrid controller, when compared with the proportional-integral-derivative (PID) controller showed enhanced performance. Work is in progress to extend this methodology to a five-fingered, three-dimensional prosthetic hand.Peer ReviewedPostprint (published version

Kinematic synthesis for smart hand prosthetics

The dream of a bionic replacement appendage is becoming reality through the use of mechatronic prostheses that utilize the body’s myoelectric signals. This paper presents a process to accurately capture the motion of the human hand joints; the obtained information is to be used in conjunction with myoelectric signal identification for motion control. In this work, the human hand is modeled as a set of links connected by joints, which are approximated to standard revolute joints. Using the methods of robotics, the motion of each finger is described as a serial robot, and expressed as Clifford algebra exponentials. This representation allows us to use the model to perform kinematic synthesis, that is, to adapt the model to the dimensions of real hands and to obtain the angles at each joint, using visual data from real motion captured with several cameras. The goal is to obtain an adaptable motion tracking system that can follow as many different motions as possible with sufficient accuracy, in order to relate the individual motions to myoelectric signals in future work.Postprint (author’s final draft

Instability of the R^3\times S^1 vacuum in low-energy effective string theory

We present and discuss an euclidean solution of the low-energy effective string action that can be interpreded as a semiclassical decay process of the ground state of the theory.Comment: 9 pages, plain-tex file, 2 figures available upon reques

A hybrid optimal control strategy for a smart prosthetic hand

ABSTRACT This paper presents a hybrid of a soft computing or control technique of adaptive neuro-fuzzy inference system (AN-FIS) and a hard computing or control technique of the hybrid finite-time linear quadratic optimal control for a two-fingered (thumb and index) prosthetic hand. In particular, the ANFIS is used for inverse kinematics, and the optimal control is used to minimize tracking error utilizing feedback linearized dynamics. The simulations of this hybrid controller, when compared with the proportional-integral-derivative (PID) controller showed enhanced performance. Work is underway to extend this methodology to a five-fingered, three-dimensional prosthetic hand

In depth characterisation of the biomolecular coronas of polymer coated inorganic nanoparticles with differential centrifugal sedimentation

Advances in nanofabrication methods have enabled the tailoring of new strategies towards the controlled production of nanoparticles with attractive applications in healthcare. In many cases, their characterisation remains a big challenge, particularly for small-sized functional nanoparticles of 5 nm diameter or smaller, where current particle sizing techniques struggle to provide the required sensitivity and accuracy. There is a clear need for the development of new reliable characterisation approaches for the physico-chemical characterisation of nanoparticles with significant accuracy, particularly for the analysis of the particles in the presence of complex biological fluids. Herein, we show that the Differential Centrifugal Sedimentation can be utilised as a high-precision tool for the reliable characterisation of functional nanoparticles of different materials. We report a method to correlate the sedimentation shift with the polymer and biomolecule adsorption on the nanoparticle surface, validating the developed core–shell model. We also highlight its limit when measuring nanoparticles of smaller size and the need to use several complementary methods when characterising nanoparticle corona complexes