Adaptive optical elements are often used to compensate for disturbances in the beam to enhance the image quality. If the element is thin, the force profile for its motion may lead to a significant unevenness of the op...
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Adaptive optical elements are often used to compensate for disturbances in the beam to enhance the image quality. If the element is thin, the force profile for its motion may lead to a significant unevenness of the optical surface impairing the image quality. A remedy falls back on the overactuation with a larger number of actuators. However, the question arises of what the minimal number of actuators for a given optical requirement is. Thus, we investigate the case of a low-frequent reference acceleration in the spatial degrees of freedom of a rigid body, where the elastic modes of a thin plate experience quasi-static amplification. Considering the information on the elastic plate modes, an optimal mapping of the demanded reference acceleration on the actuators leading to a minimal surface deviation from ideally flat is derived analytically. Furthermore, this mapping and the information of the nonsquare relative gain array (RGA) are exploited to obtain an actuator placement to further reduce the elastic plate deformation. Numerical results show a major improvement in flattening the optical surface profile compared to the case of neglecting the information about the elastic plate modes and lead to a Pareto front that supports the choice of a minimal number of actuators.
This paper proposes a new approach for one-dimensional thermoacoustic combustor models. Our new model is a transfer function estimated from the frequency response of the linearised Euler equation to a spatially normal...
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This paper proposes a new approach for one-dimensional thermoacoustic combustor models. Our new model is a transfer function estimated from the frequency response of the linearised Euler equation to a spatially normalised and temporally impulsive input. The proposed approach can deal with combustors with varying cross-sectional areas under a non-zero mean flow, distributed heating/cooling, and outlet boundary conditions involving entropy waves, overcoming limitations of the popular network model. In addition our new approach can provide a more reliable thermoacoustic model for combustors with entropy-related boundary conditions, remedying the inaccurate entropy model of the network model. Numerical comparisons of our new model with a network model show apparent similarities between the two, validating the new model. It is also observed that, compared to our new model, the network model is more sensitive to mean flow and significantly overestimates the entropy wave effects on combustor acoustics.
Joint uncertainties and state estimation of a class of linearly coupled hyperbolic partial differential equation systems in the presence of unstructured and structured uncertainties are studied in this article. For un...
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Joint uncertainties and state estimation of a class of linearly coupled hyperbolic partial differential equation systems in the presence of unstructured and structured uncertainties are studied in this article. For unstructured uncertainties that are completely unknown, by employing Takagi-Sugeno fuzzy logic systems to approximate the unstructured uncertainties, a novel adaptive fuzzy boundary observer is developed to estimate both unknown system states as well as unknown weights in the fuzzy logic system, and the estimation errors are ultimately bounded. Therein, in the design of the proposed observer, a set of swapping filters and an infinite dimensional backstepping technique are combined. On the other hand, for structured uncertainties that can be described in a concrete parameterized form, the proposed method can easily achieve the exact estimation of weights and states to their true values. The rigorous proof is provided to show that the ultimately bounded estimation errors for the case of unstructured uncertainties and the exponential convergent estimation errors for the case of structured uncertainties can be realized. Finally, three illustrative simulations are carried out to show the feasibility and effectiveness of the developed methods in this article.
In this paper, the boundary feedback control problem for the Euler-Bernoulli beam with unknown time-varying distributed load and boundary disturbance is investigated. Based on the Lagrangian-Hamiltonian mechanics, the...
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In this paper, the boundary feedback control problem for the Euler-Bernoulli beam with unknown time-varying distributed load and boundary disturbance is investigated. Based on the Lagrangian-Hamiltonian mechanics, the model of the beam is derived as a partial differential equation. To suppress the external disturbance, two disturbance rejection control approaches are adopted in the control design. Firstly, a disturbance observer is designed to estimate the boundary disturbance online. Thus, the effect of the boundary disturbance can be canceled directly in the feedback loop. A time-varying function is applied in the disturbance observer to prevent an excessively large control input. Secondly, a new observer is developed to estimate the upper bound of the disturbance and a sign function is introduced to suppress the influence of the disturbance without demanding the boundedness of the derivative of the boundary disturbance. The well-posedness and the uniform boundedness of the closed-loop system are proved using the operator semigroup theory and the Lyapunov method. Numerical comparisons with existing results are made for demonstrating the advantages of the proposed approaches.
This article addresses the problem for vibration suppression of a multiple-sectioned marine riser system subject to time-varying external disturbances and asymmetric output constraint. Under the assumption that contin...
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This article addresses the problem for vibration suppression of a multiple-sectioned marine riser system subject to time-varying external disturbances and asymmetric output constraint. Under the assumption that continuity constraint, multiple-sectioned marine riser's dynamics are described by some continuously connected partial differential equations (PDEs) coupled with an ordinary differential equation (ODE). We only employ boundary control mechanism that suppresses system's vibration displacements and compensate the influence of external disturbances. A novel and improved disturbance observer is proposed to estimate unknown boundary disturbance and two different barrier Lyapunov functions are constructed to prevent the time-varying constraint violation. Based on the backstepping technology and Lyapunov-based control, a boundary controller is presented to accomplish the control objectives. Moreover, the uniform boundedness and stability of the closed-loop system are rigorously guaranteed. Finally, simulation results are provided to illustrate the effectiveness of the designed control scheme.
In this paper, we propose an adaptive fault-tolerant boundary vibration control approach for the flexible aerial refueling hose with variable length, variable speed, and multiple actuators. A distributedparameter sys...
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In this paper, we propose an adaptive fault-tolerant boundary vibration control approach for the flexible aerial refueling hose with variable length, variable speed, and multiple actuators. A distributed parameter system (DPS) is utilized to represent the dynamic behavior of the flexible refueling hose more precisely and accurately. Based on the established DPS model, we present a boundary vibration controller to suppress the vibration of the flexible refueling hose. In the controller, fault-tolerant control with multiple actuators is considered to tackle the failure issues, and both multiplicative and additive failures are discussed in the fault situation. Then, by the Lyapunov direct method, we prove that the stability of the closed-loop system is guaranteed under the proposed control approach. Numerical examples are presented to support the theoretical derivation.
This study investigates the finite-time anti-disturbance control problem of an autonomous helicopter flexible slung-load system (AHFSLS) by describing it as a distributed parameter system with matched disturbance, mis...
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This study investigates the finite-time anti-disturbance control problem of an autonomous helicopter flexible slung-load system (AHFSLS) by describing it as a distributed parameter system with matched disturbance, mismatched disturbance, and vibration information constraint. Here, initially, a novel compound disturbance observer is proposed to simultaneously compensate for matched and mismatched disturbances. Then, by executing a rigorous Lyapunov stability analysis, with the help of a barrier Lyapunov function, the vibration amplitude converges into a compact set for the AHFSLS. The simulation results demonstrated the efficiency of the developed control strategy in dealing with matched and mismatched disturbances, vibration information constraint, and vibration in the AHFSLS. & COPY;2023 Elsevier Masson SAS. All rights reserved.
Model reduction of a high-dimensional distributed parameter system (DPS) reduces the complexity of the system for various applications, from monitoring to model predictive control, while retaining its intrinsic proper...
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Model reduction of a high-dimensional distributed parameter system (DPS) reduces the complexity of the system for various applications, from monitoring to model predictive control, while retaining its intrinsic properties. Unfortunately, the assumption of time-space separability usually fails to hold for popular time-space separation model reduction methods because the space and time of the DPS are inherently coupled. In this study, a time-space coupled learning method for a data-driven model reduction of the DPS is presented. The proposed method has the advantage of preserving the time-space coupling characteristics and increasing the number of degrees of freedom during the model reduction learning process. A novel deep-learning architecture is presented by combining encoder-decoder networks with recurrent neural networks. Given a high-dimensional system without an exact partial differential equation description, the dimension-reduced model and its temporal dynamics are jointly learned using the collected input and output data. The learned model is then applied to predict the low-dimensional representations and reconstruct the high-dimensional outputs. The proposed method was demonstrated on the catalytic rod in a tubular reactor with recycle, the results of which indicate a better modeling accuracy and lower intrinsic dimensionality compared with classical time-space separation model reduction methods.
State estimation is an important problem in distributed parameter system especially with nonlinear dynamics in industrial process. An extended Luenberger observer based on the eigen-spectrum of the system operator is ...
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State estimation is an important problem in distributed parameter system especially with nonlinear dynamics in industrial process. An extended Luenberger observer based on the eigen-spectrum of the system operator is developed in this paper to handle this problem. The distributed parameter system is projected into a finite-dimensional subspace where a low-order ordinary differential equation describing the dominant dynamics of the system is derived. A Luenberger observer extended with a nonlinear part is developed based on that dominant dynamics. A sufficient condition is given in this paper for the convergence of the estimated error. Finally, by applying the developed design method to the temperature estimation of a catalytic rod, the achieved simulation results show the effectiveness of the proposed observer. (C) 2020 Elsevier Ltd. All rights reserved.
The synthesis problem of control of objects with distributedparameters with feedback is investigated on the example of the process of heating a rod in a furnace. To generate the values of control actions, we propose ...
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The synthesis problem of control of objects with distributedparameters with feedback is investigated on the example of the process of heating a rod in a furnace. To generate the values of control actions, we propose to use their linear de- pendence on the values of the state at the measurement points, both at the current and previous moments of time. The unknown coefficients involved in this dependence of control on the measured state values are feedback parameters. They are deter- mined by minimizing the objective functional using numerical methods of first-order optimization. Formulas for the gradient of the objective functional with respect to the feedback parameters are obtained. The results of numerical experiments are presented.
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