Métodos de identificação e redução de modelos para atenuação de vibrações em estruturas inteligentes

Pós-graduação em Engenharia Mecânica - FEIS

Nonlinear constrained and saturated control of power electronics and electromechanical systems

Power electronic converters are extensively adopted for the solution of timely issues, such as power quality improvement in industrial plants, energy management in hybrid electrical systems, and control of electrical generators for renewables. Beside nonlinearity, this systems are typically characterized by hard constraints on the control inputs, and sometimes the state variables. In this respect, control laws able to handle input saturation are crucial to formally characterize the systems stability and performance properties. From a practical viewpoint, a proper saturation management allows to extend the systems transient and steady-state operating ranges, improving their reliability and availability. The main topic of this thesis concern saturated control methodologies, based on modern approaches, applied to power electronics and electromechanical systems. The pursued objective is to provide formal results under any saturation scenario, overcoming the drawbacks of the classic solution commonly applied to cope with saturation of power converters, and enhancing performance. For this purpose two main approaches are exploited and extended to deal with power electronic applications: modern anti-windup strategies, providing formal results and systematic design rules for the anti-windup compensator, devoted to handle control saturation, and “one step” saturated feedback design techniques, relying on a suitable characterization of the saturation nonlinearity and less conservative extensions of standard absolute stability theory results. The first part of the thesis is devoted to present and develop a novel general anti-windup scheme, which is then specifically applied to a class of power converters adopted for power quality enhancement in industrial plants. In the second part a polytopic differential inclusion representation of saturation nonlinearity is presented and extended to deal with a class of multiple input power converters, used to manage hybrid electrical energy sources. The third part regards adaptive observers design for robust estimation of the parameters required for high performance control of power systems.

Control of muscle relaxation during anesthesia: a novel approach for clinical routine

During general anesthesia drugs are administered to provide hypnosis, ensure analgesia, and skeletal muscle relaxation. In this paper, the main components of a newly developed controller for skeletal muscle relaxation are described. Muscle relaxation is controlled by administration of neuromuscular blocking agents. The degree of relaxation is assessed by supramaximal train-of-four stimulation of the ulnar nerve and measuring the electromyogram response of the adductor pollicis muscle. For closed-loop control purposes, a physiologically based pharmacokinetic and pharmacodynamic model of the neuromuscular blocking agent mivacurium is derived. The model is used to design an observer-based state feedback controller. Contrary to similar automatic systems described in the literature this controller makes use of two different measures obtained in the train-of-four measurement to maintain the desired level of relaxation. The controller is validated in a clinical study comparing the performance of the controller to the performance of the anesthesiologist. As presented, the controller was able to maintain a preselected degree of muscle relaxation with excellent precision while minimizing drug administration. The controller performed at least equally well as the anesthesiologist.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Autonomous formation flying: unified control and collision avoidance methods for close manoeuvring spacecraft

The idea of spacecraft formations, flying in tight configurations with maximum baselines of a few hundred meters in low-Earth orbits, has generated widespread interest over the last several years. Nevertheless, controlling the movement of spacecraft in formation poses difficulties, such as in-orbit high-computing demand and collision avoidance capabilities, which escalate as the number of units in the formation is increased and complicated nonlinear effects are imposed to the dynamics, together with uncertainty which may arise from the lack of knowledge of system parameters. These requirements have led to the need of reliable linear and nonlinear controllers in terms of relative and absolute dynamics. The objective of this thesis is, therefore, to introduce new control methods to allow spacecraft in formation, with circular/elliptical reference orbits, to efficiently execute safe autonomous manoeuvres. These controllers distinguish from the bulk of literature in that they merge guidance laws never applied before to spacecraft formation flying and collision avoidance capacities into a single control strategy. For this purpose, three control schemes are presented: linear optimal regulation, linear optimal estimation and adaptive nonlinear control. In general terms, the proposed control approaches command the dynamical performance of one or several followers with respect to a leader to asymptotically track a time-varying nominal trajectory (TVNT), while the threat of collision between the followers is reduced by repelling accelerations obtained from the collision avoidance scheme during the periods of closest proximity. Linear optimal regulation is achieved through a Riccati-based tracking controller. Within this control strategy, the controller provides guidance and tracking toward a desired TVNT, optimizing fuel consumption by Riccati procedure using a non-infinite cost function defined in terms of the desired TVNT, while repelling accelerations generated from the CAS will ensure evasive actions between the elements of the formation. The relative dynamics model, suitable for circular and eccentric low-Earth reference orbits, is based on the Tschauner and Hempel equations, and includes a control input and a nonlinear term corresponding to the CAS repelling accelerations. Linear optimal estimation is built on the forward-in-time separation principle. This controller encompasses two stages: regulation and estimation. The first stage requires the design of a full state feedback controller using the state vector reconstructed by means of the estimator. The second stage requires the design of an additional dynamical system, the estimator, to obtain the states which cannot be measured in order to approximately reconstruct the full state vector. Then, the separation principle states that an observer built for a known input can also be used to estimate the state of the system and to generate the control input. This allows the design of the observer and the feedback independently, by exploiting the advantages of linear quadratic regulator theory, in order to estimate the states of a dynamical system with model and sensor uncertainty. The relative dynamics is described with the linear system used in the previous controller, with a control input and nonlinearities entering via the repelling accelerations from the CAS during collision avoidance events. Moreover, sensor uncertainty is added to the control process by considering carrier-phase differential GPS (CDGPS) velocity measurement error. An adaptive control law capable of delivering superior closed-loop performance when compared to the certainty-equivalence (CE) adaptive controllers is finally presented. A novel noncertainty-equivalence controller based on the Immersion and Invariance paradigm for close-manoeuvring spacecraft formation flying in both circular and elliptical low-Earth reference orbits is introduced. The proposed control scheme achieves stabilization by immersing the plant dynamics into a target dynamical system (or manifold) that captures the desired dynamical behaviour. They key feature of this methodology is the addition of a new term to the classical certainty-equivalence control approach that, in conjunction with the parameter update law, is designed to achieve adaptive stabilization. This parameter has the ultimate task of shaping the manifold into which the adaptive system is immersed. The performance of the controller is proven stable via a Lyapunov-based analysis and Barbalat’s lemma. In order to evaluate the design of the controllers, test cases based on the physical and orbital features of the Prototype Research Instruments and Space Mission Technology Advancement (PRISMA) are implemented, extending the number of elements in the formation into scenarios with reconfigurations and on-orbit position switching in elliptical low-Earth reference orbits. An extensive analysis and comparison of the performance of the controllers in terms of total Δv and fuel consumption, with and without the effects of the CAS, is presented. These results show that the three proposed controllers allow the followers to asymptotically track the desired nominal trajectory and, additionally, those simulations including CAS show an effective decrease of collision risk during the performance of the manoeuvre.

Low-Level Laser Irradiation (InGaAlP-660 nm) Increases Fibroblast Cell Proliferation and Reduces Cell Death in a Dose-Dependent Manner

Background and Objective: Impaired cell metabolism and increased cell death in fibroblast cells are physiological features of chronic tendinopathy. Although several studies have shown that low-level laser therapy (LLLT) at certain parameters has a biostimulatory effect on fibroblast cells, it remains uncertain if LLLT effects depend on the physiological state. Study Design/Material and Methods: High-metabolic immortal cell culture and primary human keloid fibroblast cell culture were used in this study. Trypan blue exclusion and the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test were used to determine cell viability and proliferation. Propidium iodide stain was used for cell-cycle analysis by flow cytometry. Laser irradiation was performed daily on three consecutive days with a GaAlAs 660-nm laser (mean output: 50 mW, spot size 2 mm(2), power density = 2.5 W/cm(2)) and a typical LLLT dose and a high LLLT dose (irradiation times: 60 or 420 s; fluences: 150 or 1050 J/cm(2); energy delivered: 3 or 21 J). Results: Primary fibroblast cell culture from human keloids irradiated with 3 J showed significant proliferation by the trypan blue exclusion test (p < 0.05), whereas the 3T3 cell culture showed no difference using this method. Propidium iodide staining flow cytometry data showed a significant decrease in the percentage of cells being in proliferative phases of the cell cycle (S/g(2)/M) when irradiated with 21 J in both cell types (hypodiploid cells increased). Conclusions: Our data support the hypothesis that the physiological state of the cells affects the LLLT results, and that high-metabolic rate and short-cell-cycle 3T3 cells are not responsive to LLLT. In conclusion, LLLT with a dose of 3 J reduced cell death significantly, but did not stimulate cell cycle. A LLLT dose of 21 J had negative effects on the cells, as it increased cell death and inhibited cell proliferation.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

MVD Quarterly Report on Building Project, 2nd Quarter, FY06

A quarterly report from the Iowa Department of Transportation regarding building project status.

MVD Quarterly Report on Building Project, 4th Quarter, FY06

A quarterly report from the Iowa Department of Transportation regarding building project status.

Lineaarisen hammashihnaservokäytön tilasäätö

Tuotantotehokkuus näyttelee yhä suurempaa roolia teollisuudessa, minkä vuoksi myös pakkauslinjas­toille joudutaan asettamaan suuria vaatimuksia. Usein leik­kaus- ja kappaleensiirtosovelluksissa käyte­tään lineaarisia ruuvikäyttöjä, jotka voitaisiin tietyin edellytyksin korvata halvemmilla ja osittain suori­tuskykyisimmillä hammashihnavetoisilla johteilla. Yleensä paikkasäädetty työsolu muodostuu kahden tai kolmen eri koordinaatisto­akselin suuntaan asen­netuista johteista. Tällaisen työsolun paikoitustarkkuuteen vaikuttavat muun muassa käytetty säätöra­kenne, moottorisäätöketjun viiveet, sekä laitteiston eri epälineaarisuudet, kuten kitka. Tässä työssä esitetään lineaarisen hammashihnaservokäytön dynaamista käytöstä kuvaava matemaatti­nen malli ja laaditaan mallin pohjalta laitteen simulointimalli. Mallin toimivuus varmistetaan käytän­nön identifiointitesteillä. Lisäksi työssä tut­kitaan, kuinka hyvään suorituskykyyn lineaarinen hammas­hihnaservokäyttö kyke­nee, jos teollisuudessa paikoitussäätörakenteena tyypillisesti käytetty kaskadira­kenne tai PID-rakenne korvataan kehittyneemmällä mallipohjaisella tilasäädinra­kenteella. Säädön toi­mintaa arvioidaan simulointien ja koelaitteistolla suoritetta­vien mittaus­ten perusteella.

Tuotealustapohjaisen suunnittelun vaikutukset risteilijän suunnitteluaikatauluihin

Tuotealustapohjaisella suunnittelulla pyritään hyödyntämään jo kertaalleen hyväksi todettuja kokonaisuuksia ja moduuleja, joiden avulla voidaan nopeasti suunnitella uusia tuotteita. Tarkoituksena on suunnitella asiakkaan näkökulmasta monia erilaisia tuotteita jopa sarjatuotannon kustannustehokkuudella. Tutkimuksessa esitetään risteilijän tuotealustapohjainen suunnitteluprosessi. Lisäksi työn tavoitteena on tutkia uuden suunnitteluprosessin vaikutukset risteilijän suunnitteluaikatauluihin. Tutkimuksessa haastateltiin Turun telakan suunnitteluosaston ja kehitysosaston johtajia. Haastatteluilla selvitettiin nykyisen suunnitteluprosessin haasteita, joiden nähtiin erityisesti viivästyttävät suunnitteluaikatauluja. Keskeisiä haasteita ovat suunnitteluresurssien ylikuormitus ja suunnittelulaadun huonontuminen. Lisäksi kartoitettiin tavoitteet risteilijän tuotealustaratkaisulle ja suunnitteluaikataululle. Haastattelukierroksen pohjalta ja teoriaa soveltaen analysoitiin risteilijän modulaariseen tuotealustaan perustuva suunnitteluprosessi. Tätä suunnitteluprosessia tutkittiin edelleen case-tutkimuksessa jääasemien osalta, jossa haastateltiin kyseisten alueiden suunnittelijoita. Lisäksi case-tutkimuksessa verrattiin jääaseman ja baaripentterin perussuunnittelun vaiheita toisiinsa. Näistä saatuja tutkimustuloksia verrattiin hyttialueen vakioidun perussuunnitteluohjeen vaikutuksiin suunnitteluprosessissa. Onnistunut tuotealustapohjainen suunnittelu vaatii sitoutumista jokaisella organisaation tasolla, jotta tuotealustassa olevien vakioituja moduuleja myös käytettäisiin. Modulaarisesta toiminnasta siirtyminen tuotealustapohjaiseen suunnitteluun vaatii vakioituja moduuleja ja vakioituja rajapintoja risteilijässä. Case-tutkimuksessa ja johtopäätöksissä on todettu uuden suunnitteluprosessin lyhentävän ja tuovan kustannussäästöjä tuotteen valmistusprosessissa.

Control of Structures with Cubic and Quadratic Non-Linearities with Time Delay Consideration

This paper studies the effect of time delay on the active non-linear control of dynamically loaded flexible structures. The behavior of non-linear systems under state feedback control, considering a fixed time delay for the control force, is investigated. A control method based on non-linear optimal control, using a tensorial formulation and state feedback control is used. The state equations and the control forces are expressed in polynomial form and a performance index, quadratic in both state vector and control forces, is used. General polynomial representations of the non-linear control law are obtained and implemented for control algorithms up to the fifth order. This methodology is applied to systems with quadratic and cubic non-linearities. Strongly non-linear systems are tested and the effectiveness of the control system including a delay for the application of control forces is discussed. Numerical results indicate that the adopted control algorithm can be efficient for non-linear systems, chiefly in the presence of strong non-linearities but increasing time delay reduces the efficiency of the control system. Numerical results emphasize the importance of considering time delay in the project of active structural control systems.

Results of applying sensor fusion to a control system using optic flow

The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

Dynamic recurrent neural network for system identification and control

A dynamic recurrent neural network (DRNN) that can be viewed as a generalisation of the Hopfield neural network is proposed to identify and control a class of control affine systems. In this approach, the identified network is used in the context of the differential geometric control to synthesise a state feedback that cancels the nonlinear terms of the plant yielding a linear plant which can then be controlled using a standard PID controller.

Stable linearization using multilayer neural networks

The main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedback coefficients that linearize a nonlinear control affine plant. The stability of the linearizing closed loop can be guaranteed if the autonomous plant is asymptotically stable and the state feedback is bounded.