QFT Parameter-Scheduling control design for linear Time-Varying systems based on RBF networks

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.     

IDENTIFICATION OF TIME-VARYING MODAL PARAMETERS USING LINEAR TIME-FREQUENCY REPRESENTATION

A new method of parameter identification based on linear time-frequency representation andHilbert transform is proposed to identify modal parameters of linear time-varying systems frommeasured vibration responses. Using Gabor expansion and synthesis theory measured responses arerepresented in the time-frequency domain and modal components are reconstructed by time-frequencyfiltering. The Hilbert transform is applied to obtain time histories of the amplitude and phase angle ofeach modal component, from which time-varying frequencies and damping ratios are identified. The     

Identification of modal parameters of a time invariant linear system by continuous wavelet transformation

The applications of wavelet transforms have received significant attentions in many fields. This work proposes a procedure for identifying modal parameters of a linear system using the continuous wavelet transform. The merits of the proposed procedure over the exiting schemes of applying the wavelet transform to system identification for a linear system are in use of the time invariance property and filtering ability of the transform to enhance the efficiency of identifying the modal parameters of a structure from its earthquake responses or free vibration responses. The effectiveness and accuracy of the proposed procedure are validated via numerical simulations. The effects of noise and wavelet function on identifying the modal parameters of the structure are also explored in processing the numerically simulated acceleration responses of a six-story shear building subjected to base excitation. The dynamic characteristics of close modes are accurately determined. Finally, the proposed procedure is adopted to obtain the modal parameters of a three-story non-symmetric steel frame from its measured acceleration responses in a shaking table test. A total of nine modes are identified, including modes with high frequencies and very small amplitude.     

Time-frequency characterization of nonlinear normal modes and challenges in nonlinearity identification of dynamical systems

Presented here is a new time-frequency signal processing methodology based on Hilbert-Huang transform (HHT) and a new conjugate-pair decomposition (CPD) method for characterization of nonlinear normal modes and parametric identification of nonlinear multiple-degree-of-freedom dynamical systems. Different from short-time Fourier transform and wavelet transform, HHT uses the apparent time scales revealed by the signal's local maxima and minima to sequentially sift components of different time scales. Because HHT does not use pre-determined basis functions and function orthogonality for component extraction, it provides more accurate time-varying amplitudes and frequencies of extracted components for accurate estimation of system characteristics and nonlinearities. CPD uses adaptive local harmonics and function orthogonality to extract and track time-localized nonlinearity-distorted harmonics without the end effect that destroys the accuracy of HHT at the two data ends. For parametric identification, the method only needs to process one steady-state response (a free undamped modal vibration or a steady-state response to a harmonic excitation) and uses amplitude-dependent dynamic characteristics derived from perturbation analysis to determine the type and order of nonlinearity and system parameters. A nonlinear two-degree-of-freedom system is used to illustrate the concepts and characterization of nonlinear normal modes, vibration localization, and nonlinear modal coupling. Numerical simulations show that the proposed method can provide accurate time-frequency characterization of nonlinear normal modes and parametric identification of nonlinear dynamical systems. Moreover, results show that nonlinear modal coupling makes it impossible to decompose a general nonlinear response of a highly nonlinear system into nonlinear normal modes even if nonlinear normal modes exist in the system.     

Finite-time resilient decentralized control for interconnected impulsive switched systems with neutral delay

This paper is concerned with the problem of finite-time control for a class of interconnected impulsive switched systems with neutral delay in which the time-varying delay appears in both the state and the state derivative. The concepts of finite-time boundedness and finite-time stability are respectively extended to interconnected impulsive switched systems with neutral delay for the first time. By applying the average dwell time method, sufficient conditions are first derived to cope with the problem of finite-time boundedness and finite-time stability for interconnected impulsive switched systems with neutral delay. In addition, the purpose of finite-time resilient decentralized control is to construct a resilient decentralized state-feedback controller such that the closed-loop system is finite-time bounded and finite-time stable. All the conditions are formulated in terms of linear matrix inequalities to ensure finite-time boundedness and finite-time stability of the given system. Finally, an example is presented to illustrate the effectiveness of the proposed approach.     

Discrete state space modeling and control of nonlinear unknown systems

A novel procedure for integrating neural networks (NNs) with conventional techniques is proposed to design industrial modeling and control systems for nonlinear unknown systems. In the proposed approach, a new recurrent NN with a special architecture is constructed to obtain discrete-time state-space representations of nonlinear dynamical systems. It is referred as the discrete state-space neural network (DSSNN). In the DSSNN, the outputs of the hidden layer neurons of the DSSNN represent the system's (pseudo) state. The inputs are fed to output neurons and the delayed outputs of the hidden layer neurons are fed to their inputs via adjustable weights. The discrete state space model of the actual system is directly obtained by training the DSSNN with the input–output data. A training procedure based on the back-propagation through time (BPTT) algorithm is developed. The Levenberg–Marquardt (LM) method with a trust region approach is used to update the DSSNN weights. Linear state space models enable to use well developed conventional analysis and design techniques. Thus, building a linear model of a system has primary importance in industrial applications. Thus, a suitable linearization procedure is proposed to derive the linear state space model from the nonlinear DSSNN representation. The controllability, observability and stability properties are examined. The state feedback controllers are designed with both the linear quadratic regulator (LQR) and the pole placement techniques. The regulator and servo control problems are both addressed. A full order observer is also designed to estimate the state variables. The performance of the proposed procedure is demonstrated by applying for both single-input single-output (SISO) and multiple-input multiple-output (MIMO) nonlinear control problems.     

Admissibility analysis for linear singular systems with time-varying delays via neutral system approach

This paper studies the admissibility problem for a class of linear singular systems with time-varying delays. In order to highlight the relations between the delay and the state, the singular system is transformed into a neutral form. Then, an appropriate type of Lyapunov–Krasovskii functionals is proposed to develop a delay-derivative-dependent admissibility condition in terms of linear matrix inequalities. The derivation combines the Wirtinger-based inequality and reciprocally convex combination method. The present criterion is also for the stability test of retarded and neutral systems with time-varying delays. Some examples are provided to illustrate the effectiveness and the benefits of the proposed method.     

Generalized predictor based active disturbance rejection control for non-minimum phase systems

In this paper, a generalized predictor based control scheme is proposed to improve system performance of set-point tracking and disturbance rejection for non-minimum phase (NMP) systems. By using a generalized predictor to estimate the system output without time delay, a model-based extended state observer (MESO) is designed to simultaneously estimate the system state and disturbance. Accordingly, an active disturbance rejection control design is developed which consists of a state feedback control and a feedforward control for the disturbance rejection. The MESO and feedback controllers are analytically derived by specifying the desired characteristic roots of MESO and closed-loop system poles, respectively. To improve the output tracking performance, a pre-filter is designed based on a desired closed-loop transfer function for the set-point tracking. A sufficient condition guaranteeing robust stability of the closed-loop system against time-varying uncertainties is established in terms of linear matrix inequalities (LMIs). Three illustrative examples from the literature are used to demonstrate the effectiveness and merit of the proposed control scheme.     

Gain-scheduled predictive extended state observer for time-varying delays systems with mismatched disturbances

In this paper, a novel control scheme for systems with input and output time-varying delays is provided in discrete-time domain. The control strategy combines predictor-like techniques with a delay-dependent gain-scheduled extended state observer. The main goal is twofold: (i) to minimize the negative effect of time-varying delays in the closed-loop performance and, (ii) to actively compensate the effect of mismatched disturbances in the controlled output. Moreover, a sufficient condition based on Linear Matrix Inequalities (LMI) is provided to obtain the maximum delay interval that ensures the stability of the closed-loop system. Finally, the achieved benefits of the proposal are shown by simulation in open-loop unstable plants, and experimentally validated in a test-bed quadrotor platform.     

Finite-time extended dissipative control for fuzzy systems with nonlinear perturbations via sampled-data and quantized controller

This paper investigates the problem of finite-time extended dissipative control for T–S fuzzy time-varying delay systems with nonlinear perturbations via sampled-data and quantized controller. The definition of finite-time bounded mixed extended dissipative of fuzzy systems is first proposed. Based on the constructed Lyapunov–Krasovskii functional(LKF) and Peng–Parks integral inequality, some sufficient conditions are obtained in the form of linear matrix inequalities(LMIs), which are less conservative than other papers. By combining the input delay approach and dynamic quantizer, the sampled-data and quantized controller is designed to guarantee that the T–S fuzzy system is finite-time bounded mixed extended dissipative. Finally, some numerical examples and practical examples are presented to verify the feasibility and effectiveness of the proposed methods.     

基于AEKF的车辆质量与道路坡度实时估计

针对车辆在实际行驶过程中外界噪声的统计特性无法已知的问题,以车辆纵向动力学模型为基础,提出了自适应扩展卡尔曼滤波(adaptive extended Kalman filter,简称AEKF)的车辆质量及道路坡度估计算法。以动态估计车辆系统中的质量与坡度为研究对象,引入了旋转质量换算系数,建立车辆纵向动力学系统的状态空间模型,考虑了不同时刻的档位匹配与行驶特殊工况的处理。对系统状态方程进行离散化处理,得到系统状态方程与系统测量方程,在扩展卡尔曼滤波(extended Kalman filter,简称EKF)的基础上引入带遗忘因子的噪声统计估计器,通过AEKF对状态方程与测量方程实时更新,进行在线估计和校正噪声统计值,从而解决系统的噪声时变问题。本研究算法与EKF算法估计及实测结果的对比分析表明,本研究算法能够很好地对车辆质量和坡度信号进行有效滤波和估计,在短时间内逐渐收敛并逼近实测值,从而能够合理有效地检测车辆在行驶过程中的状态信息。     

Eigenstructure assignment by the differential Sylvester equation for linear time-varying systems

This work is concerned with the assignment of the desired eigenstructure for linear time-varying systems such as missiles, rockets, fighters, etc. Despite its well-known limitations, gain scheduling control continues to be a major focus of research efforts. Scheduling of frozen-time, frozen-state controllers for fast time-varying dynamics is known to be mathematically fallacious and practically hazardous. Therefore, recent research efforts are being directed towards applying time-varying controllers. In this paper, we i) introduce a differential algebraic eigenvalue theory for linear time-varying systems, and ii) propose an eigenstructure assignment scheme for linear time-varying systems via the differential Sylvester equation based upon newly developed notions. The whole design procedure of the proposed eigenstructure assignment scheme is very systematic. The scheme can be used to determine the stability of linear time-varying systems easily as well as to provide a new horizon of designing controllers for linear time-varying systems. The presented method is illustrated by a numerical example.     

液压伺服系统状态估计和参数辨识的鲁棒算法

针对液压伺服系统不易进行状态估计和参数辨识的问题,提出了一种鲁棒算法,把液压伺服系统的动态行为当作一个具有时变参数的线性随机状态空间模型来描述,把故障当作系统参数变化,将参数公式中重要项进行泰勒级数展开,推导线性状态方程和线性测量方程,从而得出状态向量和参数向量的估计。在液压伺服系统中实验结果表明:该鲁棒算法能很好地对液压伺服系统进行状态估计和参数辨识;并且相比于其他算法,收敛速度快,对非高斯噪声和系统参数故障的存在敏感性较低,鲁棒性好。     

A composite control method based on the adaptive RBFNN feedback control and the ESO for two-axis inertially stabilized platforms

Due to the nonlinearity and time variation of a two-axis inertially stabilized platform (ISP) system, the conventional feedback control cannot be utilized directly. To realize the control performance with fast dynamic response and high stabilization precision, the dynamic model of the ISP system is expected to match the ideal model which satisfies the desired control performance. Therefore, a composite control method based on the adaptive radial basis function neural network (RBFNN) feedback control and the extended state observer (ESO), is proposed for ISP. The adaptive RBFNN is proposed to generate the feedback control parameters online. Based on the state error information in the working process, the adaptive RBFNN can be constructed and optimized directly. Therefore, no priori training data is needed for the construction of the RBFNN. Furthermore, a linear second-order ESO is constructed to compensate for the composite disturbance. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed method is validated by a series of simulations and flight tests.     

Modal space three-state feedback control for electro-hydraulic servo plane redundant driving mechanism with eccentric load decoupling

The shaking table based on electro-hydraulic servo parallel mechanism has the advantage of strong carrying capacity. However, the strong coupling caused by the eccentric load not only affects the degree of freedom space control precision, but also brings trouble to the system control. A novel decoupling control strategy is proposed, which is based on modal space to solve the coupling problem for parallel mechanism with eccentric load. The phenomenon of strong dynamic coupling among degree of freedom space is described by experiments, and its influence on control design is discussed. Considering the particularity of plane motion, the dynamic model is built by Lagrangian method to avoid complex calculations. The dynamic equations of the coupling physical space are transformed into the dynamic equations of the decoupling modal space by using the weighted orthogonality of the modal main mode with respect to mass matrix and stiffness matrix. In the modal space, the adjustments of the modal channels are independent of each other. Moreover, the paper discusses identical closed-loop dynamic characteristics of modal channels, which will realize decoupling for degree of freedom space, thus a modal space three-state feedback control is proposed to expand the frequency bandwidth of each modal channel for ensuring their near-identical responses in a larger frequency range. Experimental results show that the concept of modal space three-state feedback control proposed in this paper can effectively reduce the strong coupling problem of degree of freedom space channels, which verify the effectiveness of the proposed model space state feedback control strategy for improving the control performance of the electro-hydraulic servo plane redundant driving mechanism.     

Identification of multi-degree of freedom non-linear systems using an extended modal space model

The identification of non-linear dynamic systems is an increasingly important area of research, with potential application in many industries. Current non-linear identification methodologies are, in general, mostly suited to small systems with few degrees of freedom (DOF) and few non-linearities. In order to develop a practical identification approach for real engineering structures, the capability of such methods must be significantly extended. In this paper, it is shown that such an extension can be achieved using multi-exciter techniques in order to excite specific modes or DOF of the system under investigation.A novel identification method for large non-linear systems is presented, based on the use of a multi-exciter arrangement using appropriated excitation applied in bursts. This proposed non-linear resonant decay method is applied to a simulated system with 5 DOF and an experimental clamped panel structure. The technique is essentially a derivative of the restoring force surface method and involves a non-linear curve fit performed in modal space. The effectiveness of the resulting reduced order model in representing the non-linear characteristics of the system is demonstrated. The potential of the approach for the identification of large continuous non-linear systems is also discussed.     

Robust preview control for a class of uncertain discrete-time systems with time-varying delay

This paper proposes a concept of robust preview tracking control for uncertain discrete-time systems with time-varying delay. Firstly, a model transformation is employed for an uncertain discrete system with time-varying delay. Then, the auxiliary variables related to the system state and input are introduced to derive an augmented error system that includes future information on the reference signal. This leads to the tracking problem being transformed into a regulator problem. Finally, for the augmented error system, a sufficient condition of asymptotic stability is derived and the preview controller design method is proposed based on the scaled small gain theorem and linear matrix inequality (LMI) technique. The method proposed in this paper not only solves the difficulty problem of applying the difference operator to the time-varying matrices but also simplifies the structure of the augmented error system. The numerical simulation example also illustrates the effectiveness of the results presented in the paper.     

Stabilization of systems with interval time-varying delay based on delay decomposing approach

The paper considers the stabilization for systems with interval time-varying delay. By decomposing the delay interval into multiple equidistant subintervals and considering the triple integral terms, a novel Lyapunov-krasovskii functional(LKF) is defined. Then extended integral inequality and convex combination approach are used to estimate the derivative of the constructed functional, and as a result, the new stability criterion with less conservatism and decision variables is obtained. On this basis, the state feedback controller is designed, by using linearization method, the existence condition of controller is obtained in terms of linear matrix inequalities(LMIs), and the specific form of controller is also given, moreover, by selecting the appropriate parameter value, the stabilization time of the system can be reduced. Numerical examples are given to illustrate the effectiveness of the proposed method.     

Vibration analysis of periodically time-varying rotor system with transverse crack

This paper proposes the vibration analysis for the periodically time-varying rotor system with transverse crack based on the complex modal analysis by introducing the modulated coordinates. From the feasibility of the crack modeling by harmonically varying stiffness, for which the dynamic behaviors of breathing crack depending on two modeling structures are investigated, the vibration analysis associated with modal characteristics, whirling, instability, directional frequency response functions (dFRFs) and directional spectrum (dS) is carried out. Using the feature of the reverse dFRFs strongly representing the effect of the crack and the interpretation of the dS patterns, the effective method to identify the modes due to the presence or propagation of a transverse crack is suggested.