Partial Quadratic Eigenvalue Assignment Problem Research Articles

Partial quadratic eigenvalue assignment for vibration systems using receptances and system matrices

In this paper, we consider the partial quadratic eigenvalue assignment problem (PQEAP) for vibration system by active feedback control, such that some “troublesome” eigenpairs are replaced by some suitable chosen or newly measured ones, while the remaining unknown eigenpairs are kept unchanged. With the assumptions that the mass and stiffness matrices are nonsingular, we give a new proof of the spectral decomposition of quadratic symmetric pencil. And then we provide some necessary and sufficient conditions of the feedback matrices so that the closed-loop can preserve the no spill-over property. With these conditions, we characterize a set of parametric solutions to the PQEAP using receptances, system matrices and a few open-loop eigenpairs. Finally, we propose a gradient-based optimization method for solving the minimum norm solution to the PQEAP. Numerical experiments illustrate the effectiveness and robustness of the proposed algorithm.

A Method for Robust Partial Quadratic Eigenvalue Assignment with Repeated Eigenvalues

Abstract A new method is proposed for robust partial quadratic eigenvalue assignment problem (RPQEAP) with repeated prescribed eigenvalues. We first derive a result on the solution of partial quadratic eigenvalue assignment problem, which leads to the partial Schur form of the close-loop system. Then by minimizing the normality departure of the partial Schur form of the close-loop system, we assign the prescribed eigenvalues step by step such that the close-loop system is as robust as possible. Our method allows the prescribed eigenvalues are repeated. Moreover, the proposed method does not use the unchanged eigenpairs of the open-loop system and avoids transforming the second-order control system to the first-order system. Numerical experiments show that the proposed method is efficient for solving the RPQEAP with repeated eigenvalues.

Robust partial quadratic eigenvalue assignment for the damped vibroacoustic system

In this paper, we consider the robust partial quadratic eigenvalue assignment problem for the damped vibroacoustic system by active feedback control. Based on the special structures of the mass and stiffness matrices of the damped vibroacoustic system, we provide a new orthogonality relation and give solution to partial quadratic eigenvalue assignment problem which only needs a few unwanted eigenvalues of the open-loop pencil and associated eigenvectors. With the QR decomposition of the control matrix, we propose a new method to characterize the solution to the quadratic eigenvalue assignment problem, which does not need to solve the Sylvester equation. Finally, we propose two different gradient-based methods for the robust and minimum norm partial quadratic eigenvalue assignment problems, in which the closed-loop eigenvalue sensitivity and the feedback norms can be minimized simultaneously. Numerical experiments demonstrate the effectiveness of our methods.

A receptance method for robust and minimum norm partial quadratic eigenvalue assignment

This paper considers the partial quadratic eigenvalue assignment problem (PQEAP) in active vibration control using state feedback. A receptance method is proposed for PQEAP such that the norms of feedback matrices and the condition number of close-loop system are simultaneously minimized. The real form of the proposed method is developed. The proposed method only uses receptance matrices and the unwanted eigenpairs of open-loop system. The system matrices and the unchanged eigenpairs of open-loop system are not required. The efficiency of the proposed method is illustrated by some numerical examples.

A modified optimization method for robust partial quadratic eigenvalue assignment using receptances and system matrices

In this paper, we focus on the robust partial quadratic eigenvalue assignment problem for vibrating structures by active feedback control. This problem is reformulated as an minimization problem, where the cost function can measure both the sensitivity of the closed-loop eigenvalues and the feedback norms. This can be seen as a modified version of the minimization problem proposed by Bai et al. (2016) [5], where there exist additional equality constraints involving determinants of linear functions of the parameter matrix. By using the receptance measurements, the system matrices and a few undesired open-loop eigenvalues and associated eigenvectors, we propose a modified gradient-based optimization method for solving the minimization problem, where the explicit gradient formula of the cost function is derived. To implement our method in real operation, the real form of our method is also presented. Finally, some numerical examples are given to illustrate the validity of the proposed method.

Minimum norm partial quadratic eigenvalue assignment for vibrating structures using receptance method

Abstract In this paper, we consider the minimum norm partial quadratic eigenvalue assignment problem (MNPQEAP) for multi-input vibration control systems. Our work is based on the recent paper proposed by Bai et al. (2018) who solve this problem by using receptances and system matrices. By using receptance method, we transform this problem into finding the minimum norm solutions of the matrix equations and propose a modified conjugate gradient (MCG) method for solving this problem. Our method can solve the MNPQEAP with finite iteration steps in the absence of roundoff errors. The numerical examples show the efficiency of our method.

Minimum norm partial quadratic eigenvalue assignment for vibrating structures using receptances and system matrices

Abstract This paper is concerned with the minimum norm partial quadratic eigenvalue assignment problem (MNPQEAP) for vibrating structures via active feedback control. We propose a gradient-based optimization method for solving the MNPQEAP using the receptance measurements, system matrices and a few undesired open-loop eigenvalues with associated eigenvectors. The real form of our method is also derived. Numerical tests show that the proposed methods are effective for solving the MNPQEAP with multiple-input vibration controls.

Robustness of the quadratic partial eigenvalue assignment using spectrum sensitivities for state and derivative feedback designs

Based on the notions of spectrum sensitivities, proposed by us earlier, we develop a novel optimization approach to deal with robustness in the closed-loop eigenvalues for partial quadratic eigenvalue assignment problem arising in active vibration control. A distinguished feature of this new approach is that the objective function is composed of only the system and the closed-loop feedback matrices. It does not need an explicit knowledge of the eigenvalues and eigenvectors. Furthermore, the approach is applicable to both the state-feedback and derivative feedback designs. These features make the approach viable to design an active vibration controller for practical applications to large real-life structures. A comparative study with existing algorithms and a study on the transient response of a real-life system demonstrate the effectiveness, superiority, and competitiveness of the proposed approach.

Partial quadratic eigenvalue assignment in vibrating structures using receptances and system matrices

In this paper, we consider the partial quadratic eigenvalue assignment problem (PQEAP) in vibration by active feedback control. Based on the receptance measurements and system matrices, we propose a constructive method for solving PQEAP, where we only need to solve a small linear system and only a few undesired open-loop eigenvalues with associated eigenvectors are needed. Our method is designed for both single-input and multiple-input vibration controls of vibrating structures. The real form of our method is also presented. Numerical tests show that our method is effective for constructing a solution to PQEAP with both single-input and multiple-input vibration controls.

Robust partial quadratic eigenvalue assignment with time delay using the receptance and the system matrices

In this paper, we consider the robust partial quadratic eigenvalue assignment problem in vibration by active feedback control. Based on the receptance measurements and the system matrices, we propose an optimization method for the robust and minimum norm partial quadratic eigenvalue assignment problem. We provide a new cost function and the closed-loop eigenvalue sensitivity and the feedback norms can be minimized simultaneously. Our method is also extended to the case of time delay between measurements of state and actuation of control. Numerical tests demonstrate the effectiveness of our method.

Multi-input partial eigenvalue assignment for high order control systems with time delay

In this paper, we consider the partial eigenvalue assignment problem for high order control systems with time delay. Ram et al. (2011) [1] have shown that a hybrid method can be used to solve partial quadratic eigenvalue assignment problem of single-input vibratory system. Based on this theory, a rather simple algorithm for solving multi-input partial eigenvalue assignment for high order control systems with time delay is proposed. Our method can assign the expected eigenvalues and keep the no spillover property. The solution can be implemented with only partial information of the eigenvalues and the corresponding eigenvectors of the matrix polynomial. Numerical examples are given to illustrate the efficiency of our approach.

Partial quadratic eigenvalue assignment in vibrating systems using acceleration and velocity feedback

The partial quadratic eigenvalue assignment problem (PQEVAP) is to shift a few undesired eigenvalues of a damped vibrating system to suitably chosen locations, while leaving the remaining eigenvalues and corresponding eigenvectors unchanged. In this paper, an algorithm for solving PQEVAPs and the minimum norm PQEVAP (MNPQEVAP) using acceleration and velocity feedback is proposed. It is shown that solving the PQEVAP here is transformed into solving an eigenvalue assignment of a linear system of a much lower order. Furthermore, the MNPQEVAP here can be efficiently solved by a gradient-based unconstrained optimization method with the derived gradient formula. This algorithm works directly on the second-order system model, and requires the knowledge of only the open-loop eigenvalues to be replaced and their corresponding eigenvectors. Lastly, through two numerical examples, the results of solving the MNPQEVAP under two different combined feedback signals, velocity and displacement signals, and acceleration and velocity signals, are compared from two points of view, i.e. the F-norms of their feedback matrices and the active control energy required from the actuators.

Minimum norm partial quadratic eigenvalue assignment with time delay in vibrating structures using the receptance and the system matrices

The partial quadratic eigenvalue assignment problem (PQEAP) is to compute a pair of feedback matrices such that a small number of unwanted eigenvalues in a structure are reassigned to suitable locations while keeping the remaining large number of eigenvalues and the associated eigenvectors unchanged. The problem arises in active vibration control of structures. For real-life applications, it is not enough just to compute the feedback matrices. They should be computed in such a way that both closed-loop eigenvalue sensitivity and feedback norms are as small as possible. Also, for practical effectiveness, the time-delay between the measurement of the state and implementation of the feedback controller should be considered while solving the PQEAP. These problems are usually solved using only system matrices and do not necessarily take advantage of the receptances which are available by measurements.In this paper, we propose hybrid methods, combining the system matrices and measured receptances, for solutions of the multi-input PQEAP and the minimum-norm PQEAP, both for systems with and without time-delay. These hybrid methods are more efficient than the standard methods which only use the system matrices and not the receptances. These hybrid methods also offer several other computational advantages over the standard methods. Our results generalize the recent work by Ram et al. [Partial pole placement with time delay in structures using the receptance and the system matrices, Linear Algebra and its Applications 434 (2011) 1689–1696]. The results of numerical experiments demonstrate the effectiveness of the proposed methods.

A multi-step hybrid method for multi-input partial quadratic eigenvalue assignment with time delay

A hybrid method was given by Ram et al. (2011) [15] for solving the partial quadratic eigenvalue assignment problem of single-input vibratory systems. In this paper, we consider the partial quadratic eigenvalue assignment problem of multi-input vibratory systems. We solve the multi-input partial quadratic eigenvalue assignment problem by a multi-step hybrid method using both the system matrices and the receptance measurements. Our method can assign the partial expected eigenvalues and keep the no spillover property. We also extend our method to the case when there exists time delay between measurements of state and actuation of control. Numerical tests show the effectiveness of our method.

Robust and minimum norm partial quadratic eigenvalue assignment in vibrating systems: A new optimization approach

Abstract The partial quadratic eigenvalue assignment problem (PQEVAP) concerns reassigning a few undesired eigenvalues of a quadratic matrix pencil to suitably chosen locations and keeping the other large number of eigenvalues and eigenvectors unchanged (no spill-over). The problem naturally arises in controlling dangerous vibrations in structures by means of active feedback control design. For practical viability, the design must be robust, which requires that the norms of the feedback matrices and the condition number of the closed-loop eigenvectors are as small as possible. The problem of computing feedback matrices that satisfy the above two practical requirements is known as the Robust Partial Quadratic Eigenvalue Assignment Problem (RPQEVAP). In this paper, we formulate the RPQEVAP as an unconstrained minimization problem with the cost function involving the condition number of the closed-loop eigenvector matrix and two feedback norms. Since only a small number of eigenvalues of the open-loop quadratic pencil are computable using the state-of-the-art matrix computational techniques and/or measurable in a vibration laboratory, it is imperative that the problem is solved using these small number of eigenvalues and the corresponding eigenvectors. To this end, a class of the feedback matrices are obtained in parametric form, parameterized by a single parametric matrix, and the cost function and the required gradient formulas for the optimization problem are developed in terms of the small number of eigenvalues that are reassigned and their corresponding eigenvectors. The problem is solved directly in quadratic setting without transforming it to a standard first-order control problem and most importantly, the significant “no spill-over property” of the closed-loop eigenvalues and eigenvectors is established by means of a mathematical result. These features make the proposed method practically applicable even for very large structures. Results on numerical experiments show that the proposed method considerably reduces both feedback norms and the sensitivity of the closed-loop eigenvalues. A study on robustness of the system responses of the method under small perturbations show that the responses of the perturbed closed-loop system are compatible with perturbations.

An optimization approach for minimum norm and robust partial quadratic eigenvalue assignment problems for vibrating structures

The partial quadratic eigenvalue assignment problem (PQEVAP) concerns the reassignment of a small number of undesirable eigenvalues of a quadratic matrix pencil, while leaving the remaining large number of eigenvalues and the corresponding eigenvectors unchanged. The problem arises in controlling undesirable resonance in vibrating structures and in stabilizing control systems. The solution of this problem requires computations of a pair of feedback matrices. For practical effectiveness, these feedback matrices must be computed in such a way that their norms and the condition number of the closed-loop eigenvector matrix are as small as possible. These considerations give rise to the minimum norm partial quadratic eigenvalue assignment problem (MNPQEVAP) and the robust partial quadratic eigenvalue assignment problem (RPQEVAP), respectively. In this paper we propose new optimization based algorithms for solving these problems. The problems are solved directly in a second-order setting without resorting to a standard first-order formulation so as to avoid the inversion of a possibly ill-conditioned matrix and the loss of exploitable structures of the original model. The algorithms require the knowledge of only the open-loop eigenvalues to be replaced and their corresponding eigenvectors. The remaining open-loop eigenvalues and their corresponding eigenvectors are kept unchanged. The invariance of the large number of eigenvalues and eigenvectors under feedback is guaranteed by a proven mathematical result. Furthermore, the gradient formulas needed to solve the problems by using the quasi-Newton optimization technique employed are computed in terms of the known quantities only. Above all, the proposed methods do not require the reduction of the model order or the order of the controller, even when the underlying finite element model has a very large degree of freedom. These attractive features, coupled with minimal computational requirements, such as solutions of small diagonal Sylvester equations make the proposed algorithms ideally suited for application to large real-life structures. Numerical results show significant improvement in feedback norms and in the condition number of the closed-loop system. Also, the closed-loop eigenvalues have acceptable accuracy.