Exponential stabilization for state and input delay systems via output feedback

This paper considers the exponential stabilization problem via static and dynamic output feedback controllers of linear systems with a time delay in both the state and input. By using a change of the state variable and combining with the Lyapunov-Krasovskii method, new sufficient conditions for exponential stabilization via static and dynamic output feedback controllers are proposed. The conditions are expressed in terms of matrix inequalities but with only one parameter needs to be tuned and therefore can be efficiently solved by incorporating an one-dimensional search method into the Matlab’s LMI toolbox. Two numerical examples are provided to illustrate the obtained results.

Partial state estimation for linear systems with output and input time delays.

This paper deals with the problem of partial state observer design for linear systems that are subject to time delays in the measured output as well as the control input. By choosing a set of appropriate augmented Lyapunov-Krasovskii functionals with a triple-integral term and using the information of both the delayed output and input, a novel approach to design a minimal-order observer is proposed to guarantee that the observer error is ε-convergent with an exponential rate. Existence conditions of such an observer are derived in terms of matrix inequalities for the cases with time delays in both the output and input and with output delay only. Constructive design algorithms are introduced. Numerical examples are provided to illustrate the design procedure, practicality and effectiveness of the proposed observer.

Adaptive fuzzy multi-surface sliding control of multiple-input and multiple-output autonomous flight systems

In this study, we proposed an adaptive fuzzy multi-surface sliding control (AFMSSC) for trajectory tracking of 6 degrees of freedom inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an adaptive fuzzy logic-based function approximator can be used to estimate the system uncertainties and an iterative multi-surface sliding control design can be carried out to control flight. Using AFMSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. It is proved that the AFMSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the tracking error. Simulation results are presented to validate the analysis.

Minimal unknown-input functional observers for multi-input multi-output LTI systems

Designing minimum possible order (minimal) disturbance-decoupled proper functional observers for multi-input multi-output (MIMO) linear time-invariant (LTI) systems is studied. It is not necessary that a minimum-order unknown-input functional observer (UIFO) exists in our proposed design procedure. If the minimum-order observer cannot be attained, the observer's order is increased sequentially through a recursive algorithm, so that the minimal order UIFO can be obtained. To the best of our knowledge, this is the first time that this specific problem is addressed. It is assumed that the system is unknown-input functional detectable, which is the least requirement for the existence of a stable UIFO. This condition also is a certificate for the convergence of our observer's order-increase algorithm. Two methodologies are demonstrated to solve the observer design equations. The second presented scheme, is a new design method that based on our observations has a better numerical performance than the first conventional one. Numerical examples and simulation results in the MATLAB/Simulink environment describe the overall observer design procedure, and highlight the efficacy of our new methodology to solve the observer equations in comparison to the conventional one.

Controle adaptativo robusto para um modelo desacoplado de um robô móvel

This thesis presents a new structure of robust adaptive controller applied to mobile robots (surface mobile robot) with nonholonomic constraints. It acts in the dynamics and kinematics of the robot, and it is split in two distinct parts. The first part controls the robot dynamics, using variable structure model reference adaptive controllers. The second part controls the robot kinematics, using a position controller, whose objective is to make the robot to reach any point in the cartesian plan. The kinematic controller is based only on information about the robot configuration. A decoupling method is adopted to transform the linear model of the mobile robot, a multiple-input multiple-output system, into two decoupled single-input single-output systems, thus reducing the complexity of designing the controller for the mobile robot. After that, a variable structure model reference adaptive controller is applied to each one of the resulting systems. One of such controllers will be responsible for the robot position and the other for the leading angle, using reference signals generated by the position controller. To validate the proposed structure, some simulated and experimental results using differential drive mobile robots of a robot soccer kit are presented. The simulator uses the main characteristics of real physical system as noise and non-linearities such as deadzone and saturation. The experimental results were obtained through an C++ program applied to the robot soccer kit of Microrobot team at the LACI/UFRN. The simulated and experimental results are presented and discussed at the end of the text

Desacoplamento de um gerador síncrono através de um controle adaptativo por modelo de referência baseado em funções de Base radial

An alternative nonlinear technique for decoupling and control is presented. This technique is based on a RBF (Radial Basis Functions) neural network and it is applied to the synchronous generator model. The synchronous generator is a coupled system, in other words, a change at one input variable of the system, changes more than one output. The RBF network will perform the decoupling, separating the control of the following outputs variables: the load angle and flux linkage in the field winding. This technique does not require knowledge of the system parameters and, due the nature of radial basis functions, it shows itself stable to parametric uncertainties, disturbances and simpler when it is applied in control. The RBF decoupler is designed in this work for decouple a nonlinear MIMO system with two inputs and two outputs. The weights between hidden and output layer are modified online, using an adaptive law in real time. The adaptive law is developed by Lyapunov s Method. A decoupling adaptive controller uses the errors between system outputs and model outputs, and filtered outputs of the system to produce control signals. The RBF network forces each outputs of generator to behave like reference model. When the RBF approaches adequately control signals, the system decoupling is achieved. A mathematical proof and analysis are showed. Simulations are presented to show the performance and robustness of the RBF network

Identificação e comparação entre controle preditivo com modelo não linear e PI sintonizados com PSO em sistema de separação gravitacional de águia-óleo

The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances

Tri-state single-phase integrated inverters with input to output power decoupling control

Researches on control for power electronics have looked for original solutions in order to advance renewable resources feasibility, specially the photovoltaic (PV). In this context, for PV renewable energy source the usage of compact, high efficiency, low cost and reliable converters are very attractive. In this context, two improved simplified converters, namely Tri-state Boost and Tri-state Buck-Boost integrated single-phase inverters, are achieved with the presented Tri-state modulation and control schemes, which guarantees the input to output power decoupling control. This feature enhances the field of single-phase PV inverters once the energy storage is mainly inductive. The main features of the proposal are confirmed with some simulations and experimental results. © 2012 IEEE.

Modelo fuzzy estimando tempo de internação por doenças cardiovasculares

Abstract A fuzzy linguistic model based on the Mamdani method with input variables, particulate matter, sulfur dioxide, temperature and wind obtained from CETESB with two membership functions each was built to predict the average hospitalization time due to cardiovascular diseases related to exposure to air pollutants in São José dos Campos in the State of São Paulo in 2009. The output variable is the average length of hospitalization obtained from DATASUS with six membership functions. The average time given by the model was compared to actual data using lags of 0 to 4 days. This model was built using the Matlab v. 7.5 fuzzy toolbox. Its accuracy was assessed with the ROC curve. Hospitalizations with a mean time of 7.9 days (SD = 4.9) were recorded in 1119 cases. The data provided revealed a significant correlation with the actual data according to the lags of 0 to 4 days. The pollutant that showed the greatest accuracy was sulfur dioxide. This model can be used as the basis of a specialized system to assist the city health authority in assessing the risk of hospitalizations due to air pollutants.

Simulação sequencial na interpolação dos dados de entrada ou saída do modelo de lixiviação do software Araquá

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

Um Modelo para Análise do Balanço e Eficiência Energética na Logística de Transporte Dutoviário para Exportação do Etanol.

This paper analyzed the energy flow of a route currently designed to transport ethanol from the Midwest region of Brazil for exportation, more precisely from the city of Aparecida do Taboado (MS) to the port of São Sebastiao (SP). The route studied a single modal combined into two pieces, duct - duct. The direct and indirect energy, involved in the operations were used to account for the inputs and outputs of energy from and into the system. The energy input and output were the variables, diesel fuel, lubricants, greases, indirect energy consumption of machinery and equipment, power consumption of labor, the energy consumption and energy consumption in depreciation and maintenance of roads. We found that this route has specific energy consumption of 0,14 MJ km-1 m-3 . The Net Energy Gain (GEl), the Energy Efficiency global (EEg) and Renewable Energy Balance (BEr), which were the energy indicators adopted in this study were obtained respectively: 1.585.958.977,00 MJ; 200,72 and 1.593.900.000,00MJ.

Comparison of multiple-input single-output single-user ultra-wideband systems with pre-distortion

This paper presents a performance analysis of a baseband multiple-input single-output ultra-wideband system over scenarios CM1 and CM3 of the IEEE 802.15.3a channel model, incorporating four different schemes of pre-distortion: time reversal, zero-forcing pre-equaliser, constrained least squares pre-equaliser, and minimum mean square error pre-equaliser. For the third case, a simple solution based on the steepest-descent (gradient) algorithm is adopted and compared with theoretical results. The channel estimations at the transmitter are assumed to be truncated and noisy. Results show that the constrained least squares algorithm has a good trade-off between intersymbol interference reduction and signal-to-noise ratio preservation, providing a performance comparable to the minimum mean square error method but with lower computational complexity. Copyright (C) 2011 John Wiley & Sons, Ltd.

An Input-Process-Output Approach to Interorganizational Teams: The Influence of Work Group Diversity, Trust and Shared Leadership on Communication Network and Team Outputs.

The market’s challenges bring firms to collaborate with other organizations in order to create Joint Ventures, Alliances and Consortia that are defined as “Interorganizational Networks” (IONs) (Provan, Fish and Sydow; 2007). Some of these IONs are managed through a shared partecipant governance (Provan and Kenis, 2008): a team composed by entrepreneurs and/or directors of each firm of an ION. The research is focused on these kind of management teams and it is based on an input-process-output model: some input variables (work group’s diversity, intra-team's friendship network density) have a direct influence on the process (team identification, shared leadership, interorganizational trust, team trust and intra-team's communication network density), which influence some team outputs, individual innovation behaviors and team effectiveness (team performance, work group satisfaction and ION affective commitment). Data was collected on a sample of 101 entrepreneurs grouped in 28 ION’s government teams and the research hypotheses are tested trough the path analysis and the multilevel models. As expected trust in team and shared leadership are positively and directly related to team effectiveness while team identification and interorganizational trust are indirectly related to the team outputs. The friendship network density among the team’s members has got positive effects on the trust in team and on the communication network density, and also, through the communication network density it improves the level of the teammates ION affective commitment. The shared leadership and its effects on the team effectiveness are fostered from higher level of team identification and weakened from higher level of work group diversity, specifically gender diversity. Finally, the communication network density and shared leadership at the individual level are related to the frequency of individual innovative behaviors. The dissertation’s results give a wider and more precise indication about the management of interfirm network through “shared” form of governance.

Measuring Scale Efficiency from the Translog Multi-Input, Multi-Output Distance Function

Ray (1998) developed measures of input- and output-oriented scale efficiency that can be directly computed from an estimated Translog frontier production function. This note extends the earlier results from Ray (1998) to the multiple-output multiple input case.