Author

# Mahmoud E. Sawan

Other affiliations: Texas Instruments, University of Illinois at Urbana–Champaign

Bio: Mahmoud E. Sawan is an academic researcher from Wichita State University. The author has contributed to research in topics: Full state feedback & Discrete time and continuous time. The author has an hindex of 11, co-authored 113 publications receiving 510 citations. Previous affiliations of Mahmoud E. Sawan include Texas Instruments & University of Illinois at Urbana–Champaign.

##### Papers published on a yearly basis

##### Papers

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TL;DR: In this article, the robust stability problem of linear time-invariant singularly perturbed systems is discussed, where the system matrix may have a parameter perturbation bounded by the Hα-norm.

Abstract: The robust stability problem of linear time-invariant singularly perturbed systems is discussed, where the system matrix may have a parameter perturbation bounded by the Hα-norm. A sufficient condition for the upper bound of e is given, such that the stability of the actual system (or the full-order model) can be inferred from the analysis of the reduced-order system (or the slow model) in separate time scales.

52 citations

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TL;DR: In this article, a design technique is formulated by which the stabilizing controller can be formed through the controllers of the slow and fast subsystems, and sufficient conditions for stability of the closed-loop system under this composite controller are given.

Abstract: A class of linear shift-invariant discrete-time singularly perturbed systems with inaccessible states is considered. A design technique is formulated by which the stabilizing controller can be formed through the controllers of the slow and fast subsystems. Sufficient conditions for stability of the closed-loop system under this composite controller are given.

44 citations

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TL;DR: In this article, the Hamilton-Jacobi-Bellman equation is employed to derive the optimality equations wherein this performance index is minimized, and an unstable wing rock model using nonlinear state feedback is asymptotically stable in the large.

Abstract: A procedure is presented for optimizing a state feedback control law for a nonlinear system with respect to a positive performance index. The Hamilton-Jacobi-Bellman equation is employed to derive the optimality equations wherein this performance index is minimized. The closed-loop Lyapunov function is assumed to have the same matrix form of state variables as the performance index. The constant interpolated terms of these matrix forms are easily determined so as to guarantee their positive definitenesses. The optimal nonlinear system is asymptotically stable in the large, as both the closed-loop Lyapunov function and performance index are positive definite. An unstable wing rock equation of motion is employed to illustrate this method. It is shown that the wing rock model using nonlinear state feedback is asymptotically stable in the large. Both optimal linear and nonlinear state feedback cases are evaluated.

39 citations

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14 Aug 1989TL;DR: In this article, a sequential procedure to relocate the optimal eigenvalues to desired positions by proper modification in performance criterion is developed, and the optimal solution of the resulting LQ problem determines the optimal gain.

Abstract: A procedure in which a state weighting matrix was modified by introducing a degree of relative stability to relocate the optimal closed-loop eigenvalues of continuous time system was recently presented. This procedure is adapted to relocate the optimal poles to any desired location of a discrete time system. A sequential procedure to relocate the optimal eigenvalues to desired positions by proper modification in performance criterion is developed. The optimal solution of the resulting LQ problem determines the optimal gain, and the closed-loop system attains the desired spectrum. Thus, the desired properties of the Linear Quadratic (LQ) solution are retained, while placing the closed-loop system poles. >

37 citations

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16 Jan 2006TL;DR: In this article, the robust stabilisation problem of a linear time-invariant singularly perturbed system with nonlinear uncertainties is studied, where the only information available for system uncertainties is their norm upper bounds, and no matching conditions are assumed.

Abstract: This note studies the robust stabilisation problem of a linear time–invariant singularly perturbed system with nonlinear uncertainties, where the only information available for system uncertainties is their norm upper bounds, and no matching conditions are assumed. A linear stabilising control law is presented which can be determined by the solutions of two independent Lyapunov equations. The system stability bound can then be obtained by using the existing methods. Finally, a numerical example is given to illustrate the applications of the proposed results, and future work on this subject is also discussed.

26 citations

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01 Jun 1979TL;DR: In this article, an augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems, with step-by-step explanations that show clearly how to make practical use of the material.

Abstract: This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material. The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the engineering properties of the regulator. Topics include degree of stability, phase and gain margin, tolerance of time delay, effect of nonlinearities, asymptotic properties, and various sensitivity problems. The third section explores state estimation and robust controller design using state-estimate feedback. Numerous examples emphasize the issues related to consistent and accurate system design. Key topics include loop-recovery techniques, frequency shaping, and controller reduction, for both scalar and multivariable systems. Self-contained appendixes cover matrix theory, linear systems, the Pontryagin minimum principle, Lyapunov stability, and the Riccati equation. Newly added to this Dover edition is a complete solutions manual for the problems appearing at the conclusion of each section.

3,254 citations

01 Jun 2002

TL;DR: This paper presents an overview of singular perturbations and time scales (SPaTS) in control theory and applications during the period 1984-2001 and is not intended to be an exhaustive survey on the topic.

Abstract: This paper presents an overview of singular perturbations and time scales (SPaTS) in control theory and applications during the period 1984-2001 (the last such overviews were provided by [231, 371]). Due to the limitations on space, this is in way intended to be an exhaustive survey on the topic.

305 citations

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TL;DR: In this article, an adaptive backstepping flight control law for the F-16/MATV (multi-axis thrust vectoring) aircraft is discussed, which tracks reference trajectories with the angle of attack a, the stability-axes roll rate p s, and the total velocity V T. Furthermore, the sideslip angle β has to be kept at zero.

Abstract: The design of an adaptive backstepping flight control law for the F-16/MATV (multi-axis thrust vectoring) aircraft is discussed. The control law tracks reference trajectories with the angle of attack a, the stability-axes roll rate p s , and the total velocity V T . Furthermore, the sideslip angle β has to be kept at zero. B-spline neural networks are used inside the parameter update laws of the backstepping control law to approximate the uncertain aerodynamic forces and moments. Command filters are used to implement the constraints on the control surfaces and the virtual control states. The stability of the parameter estimation process during periods of saturation is guaranteed by using a modified tracking error definition, in which the effect of the saturation has been filtered out. The controller and its performance are evaluated on a nonlinear, six-degrees-of-freedom dynamic model of an F-16/MATV aircraft in a number of simulation scenarios.

257 citations

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TL;DR: Simulation results demonstrate that the proposed design method can achieve favorable control performance for the wing rock system without the knowledge of system dynamic functions.

Abstract: Wing rock is a highly nonlinear phenomenon in which an aircraft undergoes limit cycle roll oscillations at high angles of attack. In this paper, a supervisory recurrent fuzzy neural network control (SRFNNC) system is developed to control the wing rock system. This SRFNNC system is comprised of a recurrent fuzzy neural network (RFNN) controller and a supervisory controller. The RFNN controller is investigated to mimic an ideal controller and the supervisory controller is designed to compensate for the approximation error between the RFNN controller and the ideal controller. The RFNN is inherently a recurrent multilayered neural network for realizing fuzzy inference using dynamic fuzzy rules. Moreover, an on-line parameter training methodology, using the gradient descent method and the Lyapunov stability theorem, is proposed to increase the learning capability. Finally, a comparison between the sliding-mode control, the fuzzy sliding control and the proposed SRFNNC of a wing rock system is presented to illustrate the effectiveness of the SRFNNC system. Simulation results demonstrate that the proposed design method can achieve favorable control performance for the wing rock system without the knowledge of system dynamic functions.

154 citations

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TL;DR: In this paper, a kinetic energy optimization technique (EOT) has been derived, and numerical issues are addressed and applied to real experimental data obtained from a model of an asymmetric long span bridge.

Abstract: In experimental modal testing, the measurement locations and the number of measurements have a major influence on the quality of the results. In general, there are several alternative schemes for sensor placement, and the accuracy of the data increases as the number of sensors utilized increases. However, the number of transducers that can be attached to a real structure is limited by economic constraints. Therefore, algorithms that address the issue of limited instrumentation and its effects on resolution and accuracy are important from the standpoint of experimental modal analysis. The authors are particularly interested in structural dynamics based damage evaluation of large structures, and the development and implementation of suitable sensor location algorithms are critical for such a problem. A kinetic energy optimization technique (EOT) has been derived, and numerical issues are addressed and applied to real experimental data obtained from a model of an asymmetric long span bridge. Using experimental data from the bridge model, the algorithm proposed in this paper is compared to Kammer's EIM algorithm, which optimizes the transducer placement for identification and control purposes.

148 citations