Active sound quality control of engine induced cavity noise

Active control solutions appear to be a feasible approach to cope with the steadily increasing requirements for noise reduction in the transportation industry. Active controllers tend to be designed with a target on the sound pressure level reduction. However, the perceived control efficiency for the occupants can be more accurately assessed if psychoacoustic metrics can be taken into account. Therefore, this paper aims to evaluate, numerically and experimentally, the effect of a feedback controller on the sound quality of a vehicle mockup excited with engine noise. The proposed simulation scheme is described and experimentally validated. The engine excitation is provided by a sound quality equivalent engine simulator, running on a real-time platform that delivers harmonic excitation in function of the driving condition. The controller performance is evaluated in terms of specific loudness and roughness. It is shown that the use of a quite simple control strategy, such as a velocity feedback, can result in satisfactory loudness reduction with slightly spread roughness, improving the overall perception of the engine sound. (C) 2008 Elsevier Ltd. All rights reserved.

A state-space modeling approach for active structural acoustic control

The demands for improvement in sound quality and reduction of noise generated by vehicles are constantly increasing, as well as the penalties for space and weight of the control solutions. A promising approach to cope with this challenge is the use of active structural-acoustic control. Usually, the low frequency noise is transmitted into the vehicle`s cabin through structural paths, which raises the necessity of dealing with vibro-acoustic models. This kind of models should allow the inclusion of sensors and actuators models, if accurate performance indexes are to be accessed. The challenge thus resides in deriving reasonable sized models that integrate structural, acoustic, electrical components and the controller algorithm. The advantages of adequate active control simulation strategies relies on the cost and time reduction in the development phase. Therefore, the aim of this paper is to present a methodology for simulating vibro-acoustic systems including this coupled model in a closed loop control simulation framework that also takes into account the interaction between the system and the control sensors/actuators. It is shown that neglecting the sensor/actuator dynamics can lead to inaccurate performance predictions.

Experimental analysis of active-passive vibration control using viscoelastic materials and extension and shear piezoelectric actuators

Hybrid active-passive damping treatments combine the reliability, low cost and robustness of viscoelastic damping treatments and the high-performance, modal selective and adaptive piezoelectric active control. Numerous hybrid damping treatments have been reported in the literature. They differ mainly by the relative positions of viscoelastic treatments, sensors and piezoelectric actuators. In this work we present an experimental analysis of three active-passive damping design configurations applied to a cantilever beam. In particular, two design configurations based on the extension mode of piezoelectric actuators combined with viscoelastic constrained layer damping treatments and one design configuration with shear piezoelectric actuators embedded in a sandwich beam with viscoelastic core are analyzed. For comparison purposes, a purely active design configuration with an extension piezoelectric actuator bonded to an elastic beam is also analyzed. The active-passive damping performance of the four design configurations is compared. Results show that active-passive design configurations provide more reliable and wider-range damping performance than the purely active configuration.

AVERAGE CONTINUOUS CONTROL OF PIECEWISE DETERMINISTIC MARKOV PROCESSES

This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs) taking values in a general Borel space and with compact action space depending on the state variable. The control variable acts on the jump rate and transition measure of the PDMP, and the running and boundary costs are assumed to be positive but not necessarily bounded. Our first main result is to obtain an optimality equation for the long run average cost in terms of a discrete-time optimality equation related to the embedded Markov chain given by the postjump location of the PDMP. Our second main result guarantees the existence of a feedback measurable selector for the discrete-time optimality equation by establishing a connection between this equation and an integro-differential equation. Our final main result is to obtain some sufficient conditions for the existence of a solution for a discrete-time optimality inequality and an ordinary optimal feedback control for the long run average cost using the so-called vanishing discount approach. Two examples are presented illustrating the possible applications of the results developed in the paper.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

Lymphocytic prolactin does not contribute to systemic lupus erythematosus hyperprolactinemia

Introduction Lymphocytic prolactin (PRL) gene expression is detected in the majority of the immune cells and it is not known if this source contributes to hyperprolactinemia in systemic lupus erythematosus (SLE). We have therefore evaluated lymphocytic PRL secretion and gene expression in SLE and healthy controls. Methods Thirty SLE patients (ACR criteria) and 10 controls were selected for the study. Serum levels of PRL and macroprolactin were detected by immunofluorometric assay and gel filtration chromatography, respectively. The lymphocytic biological activity was determined by Nb2 cells bioassays. Lymphocytic PRL gene expression was evaluated by RT-PCR assay. Results The median serum PRL levels of the 30 SLE patients was higher than the control group (9.65 (1.9-38.9) vs. 6.40 (2.4-10.3) ng/mL, p=0.03). A significant difference was detected between median serum PRL levels of active SLE, inactive SLE and controls (10.85 (5-38.9) vs. 7.65 (1.9-15.5) vs. 6.40 (2.4-10.3) ng/mL), p=0.01). The higher frequency of mild hyperprolactinemia was detected among active SLE in comparison with inactive SLE and controls (7(38.9%) vs. 1 (8.3%) vs. 0(0%)), with statistical significance (p=0.02). Nb2 cells assay revealed uniformly low levels of lymphocytic PRL in active, inactive and control groups without statistical significance among them (24.2 (8-63) vs. 27 (13.6-82) vs. 29.5 (8-72) ng/mL), p=0.84). Furthermore, median lymphocytic PRL gene expression evaluated by RT-PCR assay was comparable in both active and inactive SLE groups (p=0.12). Conclusion This is the first study to exclude a lymphocytic source of PRL, pointing out a pituitary etiology for hyperprolactinemia in SLE. However, other sources from the immune system cannot be ruled out.

Outbreak of vancomycin-resistant enterococci in a tertiary hospital: The lack of effect of measures directed mainly by surveillance cultures and differences in response between Enterococcus faecium and Enterococcus faecalis

To describe the effect of active surveillance to control vancomycin-resistant enterococci (VRE) after an outbreak, 549 surveillance rectal cultures were performed in 308 patients (35% positive). An educational intervention to prevent transmission was implemented. Infection and colonization by VR-Enterococcus faecalis decreased, but Enterococcus faecium persisted despite control measures. Infections by VR-E faecalis fell to zero in 2008. We observed difficulties in controlling colonization with measures directed mainly by surveillance cultures and differences between responses of E faecium and E faecalis.

Analysis of patellar stabilizers muscles and patellar kinematics in anterior knee pain subjects

Patella stabilizer muscle response and patellar kinematics were evaluated in 19 women with anterior knee pain (AKP) and 20 healthy women during maximum voluntary isometric contraction (MVIC) with the knee positioned at 15 degrees, 30 degrees and 45 degrees flexion during open (OKC) and closed (CKC) kinetic chain exercises. Patellar kinematics was evaluated through patellar tilt and displacement, and the electrical activity of patellar stabilizers through the root mean square normalized during MVIC and OKC with the knee at 90 degrees flexion. Data revealed that the vastus medialis oblique muscle (VMO) was more active in the control group compared to the AKP group during OKC exercises with the knee at 45 degrees flexion. However, no difference in the patellar kinematics was observed between these groups; nevertheless, the correlation between these parameters also showed, with the knee at 45 degrees flexion, that lateral patellar tilt increase was associated with a reduction in the activity of lateral patellar stabilizers in the control group and with an increase in the VMO activity in the AKP group. In conclusion, electrical activity is an important factor in evaluating AKP and in AKP treatment evolution. (C) 2010 Elsevier Ltd. All rights reserved.

Galerkin Method and Weighting Functions Applied to Nonlinear H(infinity) Control with Output Feedback

This paper considers two aspects of the nonlinear H(infinity) control problem: the use of weighting functions for performance and robustness improvement, as in the linear case, and the development of a successive Galerkin approximation method for the solution of the Hamilton-Jacobi-Isaacs equation that arises in the output-feedback case. Design of nonlinear H(infinity) controllers obtained by the well-established Taylor approximation and by the proposed Galerkin approximation method applied to a magnetic levitation system are presented for comparison purposes.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

Control system design for flexible rotors supported by actively lubricated bearings

This article presents a methodology for calculating the gains of an output feedback controller for active vibration control of flexible rotors. The methodology is based on modal reduction. The proportional and derivative gains are obtained by adjusting the first two damping factors of the system and keeping the lengths of the two eigenvalues constant in the real-imaginary plane. The methodology is applied to an industrial gas compressor supported by active tilting-pad journal bearings. The unbalance response functions and mode shapes of the flexible rotor with and without active control are presented, showing significative improvement in damping reserve with the control. The importance of sensor location is emphasized, on the basis of the energy necessary to operate the active system over the entire frequency range studied. The best results are obtained by a decentralized controller, observing displacement and velocity of the shaft at the bearing positions.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

On the convergence of successive Galerkin approximation for nonlinear output feedback H(infinity) control

Although the formulation of the nonlinear theory of H(infinity) control has been well developed, solving the Hamilton-Jacobi-Isaacs equation remains a challenge and is the major bottleneck for practical application of the theory. Several numerical methods have been proposed for its solution. In this paper, results on convergence and stability for a successive Galerkin approximation approach for nonlinear H(infinity) control via output feedback are presented. An example is presented illustrating the application of the algorithm.