10 resultados para Multivariable predictive control
em Reposit
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Recently, a generalized passivity concept for linear multivariable systems was obtained which allows circumventing the restrictiveness of the usual passivity concept. The latter is associated with the classical SPR (Strictly Positive Real) condition whereas the new concept of passivity is associated with the so called WSPR condition and its advantage in multivariable systems is that it does not require a restrictive symmetry condition of SPR systems. As a result, it allows the design of multivariable adaptive control that, unlike some existing factorization approaches, does not imply in additional overparameterization of the adaptive controller. In this paper, we complete a previously established WSPR sufficient condition and prove that it is also necessary. We also propose some methods of passification by either premultiplying the system output tracking error vector or the system input vector by an adequate passifying matrix multiplier, so that the resulting input/output transfer function becomes WSPR. The efficiency of our proposals are illustrated by simulation utilizing a well known robotics adaptive visual servoing problem. © 2011 IFAC.
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This paper presents a control method that is effective to reduce the degenerative effects of delay time caused by a treacherous network. In present application a controlled DC motor is part of an inverted pendulum and provides the equilibrium of this system. The control of DC motor is accomplished at the distance through a treacherous network, which causes delay time in the control signal. A predictive technique is used so that it turns the system free of delay. A robust digital sliding mode controller is proposed to control the free-delay system. Due to the random conditions of the network operation, a delay time detection and accommodation strategy is also proposed. A computer simulation is shown to illustrate the design procedures and the effectiveness of the proposed method. © 2011 IEEE.
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An optimal control framework to support the management and control of resources in a wide range of problems arising in agriculture is discussed. Lessons extracted from past research on the weed control problem and a survey of a vast body of pertinent literature led to the specification of key requirements to be met by a suitable optimization framework. The proposed layered control structure—including planning, coordination, and execution layers—relies on a set of nested optimization processes of which an “infinite horizon” Model Predictive Control scheme plays a key role in planning and coordination. Some challenges and recent results on the Pontryagin Maximum Principle for infinite horizon optimal control are also discussed.
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The good efficiency in a sewage treatment plant (WWTP) is a great importance to the environment. The management of electromechanical equipment installed in these stations is a major challenge due to the fact that they are installed on areas of difficult access and maintenance unhealthy and making the time for the correction of any faults is extended. This paper proposes the development of a Wireless Sensor Network (WSN), in order to monitor electromechanical equipment, allowing the Concessionaire a predictive control in real time. The design of a wireless sensors network for monitoring equipment requires not only the development and assembly of the sensor modules, but must also include the development of software for managing the data collected. Thus, this work includes a Zigbee WSN, small, adapted for monitoring of electromechanical equipment and environmental conditions of a WWTP, type stabilization pond, installed in an area of approximately 0.15 km 2 and the average flow of 320 liters of treatment per second. The experimental results show that this monitoring system can perform with the collection of parameters of performance and quality assessment at the station.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Feasibility of nonlinear and adaptive control methodologies in multivariable linear time-invariant systems with state-space realization (A, B, C) is apparently limited by the standard strictly positive realness conditions that imply that the product CB must be positive definite symmetric. This paper expands the applicability of the strictly positive realness conditions used for the proofs of stability of adaptive control or control with uncertainty by showing that the not necessarily symmetric CB is only required to have a diagonal Jordan form and positive eigenvalues. The paper also shows that under the new condition any minimum-phase systems can be made strictly positive real via constant output feedback. The paper illustrates the usefulness of these extended properties with an adaptive control example. (C) 2006 Elsevier Ltd. All rights reserved.
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Nasopharyngeal colonization with methicillin-resistant Staphylococcus aureus (MRSA) often precedes the development of nosocomial infections. In order to identify risk factors for MRSA colonization, we conducted a case-case-control study, enrolling 122 patients admitted to a medical-surgical intensive care unit (ICU). All patients had been screened for nasopharyngeal colonization with S. aureus upon admission and weekly thereafter. Two case-control studies were performed, using as cases patients who acquired colonization with MRSA and methicillin-susceptible S. aureus (MSSA), respectively. For both studies, patients in whom colonization was not detected during ICU stay were selected as control subjects. Several potential risk factors were assessed in univariate and multivariable (logistic regression) analysis. MRSA and MSSA were recovered from nasopharyngeal samples from 27 and 10 patients, respectively. Independent risk factors for MRSA colonization were: length-of-stay in the ICU (Odds Ratio [OR]=1.12, 95%Confidence Interval[CI]=1.06-1.19, p<0.001) and use of ciprofloxacin (OR=5.05, 95%CI=1.38-21.90, p=0.015). The use of levofloxacin had a protective effect (OR=0.08, 95%CI=0.01-0.55, p=0.01). Colonization with MSSA was positively associated with central nervous system disease (OR=7.45, 95%CI=1.33-41.74, p=0.02) and negatively associated with age (OR=0.94, 95%CI=0.90-0.99, p=0.01). In conclusion, our study suggests a role for both cross-transmission and selective pressure of antimicrobials in the spread of MRSA.
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In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.
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Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.
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Introduction Surgical site infections (SSIs) often manifest after patients are discharged and are missed by hospital-based surveillance. Methods We conducted a case-reference study nested in a prospective cohort of patients from six surgical specialties in a teaching hospital. The factors related to SSI were compared for cases identified during the hospital stay and after discharge. Results Among 3,427 patients, 222 (6.4%) acquired an SSI. In 138 of these patients, the onset of the SSI occurred after discharge. Neurological surgery and the use of steroids were independently associated with a greater likelihood of SSI diagnosis during the hospital stay. Conclusions Our results support the idea of a specialty-based strategy for post-discharge SSI surveillance.