1,256 publications from this institution
This paper presents the issue of robust disturbance attenuation and robust asymptotic stability problem for finite-dimensional linear parameter-dependent state-delayed systems. The use of polynomial parameter-dependent quadratic Lyapunov functions and linear matrix inequalities (LMIs) formulations for robust H ∞ control are considered. It is shown that the state feedback control can be determined to guarantee the stability of the closed-loop system independently of the time-delay. We present an illustrative example to demonstrate the applicability of the proposed design approach. Acknowledgements This research project was partially financially supported under Research Grant 8101004-1-1 provided by University of Tehran and partially by the German Academic Exchange Service (DAAD).
This brief investigates the problem of passivity-based resilient sampled-data control for Markovian jump systems subject to actuator faults via an adaptive fault-tolerant mechanism. By constructing a proper Lyapunov function, a set of sufficient conditions is obtained in terms of linear matrix inequalities (LMIs), which ensures that the closed-loop system is stochastically passive. In order to reflect the imprecision in controller, the additive gain variations is considered. Then, the resilient sampled-data control parameters can be determined by solving the obtained LMIs. Finally, an illustrative example is presented to show the validity and applicability of the proposed design technique.
The prediction of key variables has great significance to monitor the running status of industrial systems. In this paper, a novel data-driven design of variable predictor is proposed. The basic idea is the realization of prediction observer, which is modified from the observer-based fault diagnose method. Different from the standard data-driven approaches, the proposed scheme is adopted for the dynamic systems due to the superior tracking ability of output observer. Additionally, by introducing an extra design freedom and the estimation of measured value, it can also be used for the case that the key variable is not on-line measurable. Finally, the proposed prediction scheme is applied to the Tennessee-Eastman plant to demonstrate the effectiveness.
In this note, the problem of robust fault detection filter (RFDF) design for a class of linear systems subjected to some nonlinear perturbations and mixed neutral and discrete time-varying delays is investigated based on an H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sub> performance condition. By introducing a descriptor technique, using Lyapunov-Krasovskii functional and a suitable change of variables, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities (LMIs) to synthesize the residual generation scheme. Based on Luenberger type observers, the explicit expression of the filters is derived for the fault such that both asymptotic stability and a prescribed level of disturbance attenuation are satisfied for all admissible nonlinear perturbations. A numerically example is provided to show performance of the proposed design approach.
We address the problem of downlink throughput improvement for IEEE 802.11a/g systems by using a modified access point (AP) equipped with multiple antennas. The main restriction is that the standard terminals should not be modified in any way. An alternating time-offset space division multiple access (SDMA) solution is considered for a conference room scenario. A simulation is based on channel models approved by the IEEE 802.11 Standard Group and takes into account the main features of the IEEE 802.11a/g standard. It is demonstrated that a near doubling of downlink capacity can be achieved in a conference room environment.
A vehicle stability control approach for four-wheel independently actuated (FWIA) electric vehicles is presented. The proposed control method consists of a higher-level controller and a lower-level controller. An adaptive control-based higher-level controller is designed to yield the vehicle virtual control efforts to track the desired vehicle motions due to the possible modeling inaccuracies and parametric uncertainties. The lower-level controller considering tire force saturation is given to allocate the required control efforts to the four in-wheel motors for providing the desired tire forces. An analytic method is given to distribute the high-level control efforts, without using the numerical-optimization-based control allocation algorithms. Simulations based on a high-fidelity, CarSim, and full-vehicle model show the effectiveness of the control approach.
The design of vibration control systems for the seismic protection of closely adjacent buildings is a complex and challenging problem. In this paper, we consider distributed multi-actuation schemes that combine interbuilding linking elements and interstory actuation devices. Using an advanced static output-feedback H ∞ approach, active and passive vibration control systems are designed for a multi-story two-building structure equipped with a selected set of linked and unlinked actuation schemes. To validate the effectiveness of the obtained controllers, the corresponding frequency responses are investigated and a proper set of numerical simulations is conducted using the full scale North–South El Centro 1940 seismic record as ground acceleration disturbance. The observed results indicate that using combined interstory-interbuilding multi-actuation schemes is an effective means of mitigating the vibrational response of the individual buildings and, simultaneously, reducing the risk of interbuilding pounding. These results also point out that passive control systems with high-performance characteristics can be designed using damping elements.
No abstract is provided for this article.
No abstract is provided for this article.
This paper presents a convex optimisation method for observer-based control design of LPV neutral systems. Utilising the polynomials parameter-dependent quadratic functions and a suitable change of variables, the required sufficient conditions with high precision for the design of a desired observer-based control are established in terms of delay-dependent parameter-independent linear matrix inequalities. An observer-based controller guaranteeing asymptotic stability of the closed-loop system and satisfying a prescribed level of performance to the LPV neutral system with constant delay parameters is developed. A Lyapunov-Krasovskii method underlies the observer-based H∞ control design. A numerical example with simulation results illustrates the effectiveness of the methodology.
This article focuses on the integral sliding mode control (SMC) issue for nonlinear singularly perturbed systems via T-S fuzzy models. A new sufficient criterion for the sliding surface design is attained by adopting convexification techniques, which also guarantees the asymptotic stability of the sliding motion. Then, a new dynamic SMC synthesis scheme is developed to ensure the finite-time reachability of the sliding surface. A simulation example is shown to illustrate the validity of the developed scheme.
This paper is dedicated to studying the stability of semi-Markov switching stochastic delay systems with unstable subsystems, where delay depends on another semi-Markovian process and transition rates are uncertain. Based on the stochastic analysis theory and the mode-dependent multi-Lyapunov function method, relevant sufficient conditions are established to ensure the asymptotic stability in mean square of the system. In addition, contrary to the existing works, the system under consider is more general and our works are not only applicable to the system with partial unstable subsystems, but also applicable to the system with all unstable subsystems. Finally, one numerical example is provided to illustrate the correctness of the method described in the paper.
Unsupervised image segmentation is greatly useful in many vision-based applications. In this paper, we aim at the unsupervised low-key image segmentation. In low-key images, dark tone dominates the background, and gray level distribution of the foreground is heterogeneous. They widely exist in the areas of space exploration, machine vision, medical imaging, etc. In our algorithm, a novel active contour model with the probability density function of gamma distribution is proposed. The flexible gamma distribution gives a better description for both of the foreground and background in low-key images. Besides, an unsupervised curve initialization method is designed, which helps to accelerate the convergence speed of curve evolution. The experimental results demonstrate the effectiveness of the proposed algorithm through comparison with the CV model. Also, one real-world application based on our approach is described in this paper.
