Cauer continued-fraction expansion about s = 0 and s = a for biased reduced-order state-space models

A method of linear-system reduction is presented which produces biased state-space models such that combinations of retained time-moments and weighted time-moments may be varied. The method is based on the concept of representing the system transfer function in a biased Cauer form of continued-fraction expansion (CFE) about s = 0 and s = a. A new algorithm for obtaining the continued-fraction expansion of the transfer function of a linear time-invariant system from its state-space model directly, without first determining the corresponding transfer function, is derived. A realization which uses only integrators for the biased Cauer continued-fraction expansion about s = 0 and s = a is presented. The corresponding canonical state-space model is established, which allows the reduced-order state-space model to be formed by directly partitioning the system matrices. Also presented are two new similarity transformation matrices; one is used to transform a state-space model from a general form to a state-space model in the biased CFE canonical form, and the other is used to transform a state-space model from phase-variable canonical form to the biased CFE canonical form.     

Note on ‘ On the definition of transfer function ’

An algorithm for directly obtaining the canonical state-space model corresponding to the Cauer third form of continued fraction expansion (CFE) from a given general state-space model is presented. The algorithm can be used to determine the transfer function of linear time-invariant system from its state-space model as well as to obtain the reduced order models..Two new similarity matrices, one transforms a state-space equation from a general form to a Cauer third CFE canonical form, and the other transforms a state-space model in phase-variable form to a state-space model in a Cauer third CFE canonical form, are derived. Using these matrices an approximate relationship between the original state vector and the state-vector of reduced model obtained by the method of Cauer third CFE is established     

System reduction by Cauer continued-fraction expansion about s = 0 and s = a alternately

A new algorithm to obtain the Cauer continued-fraction expansion (CFE) about the origin and about a general point from the time-moments and weighted time-moments of the impulse response of a linear time-invariant system is presented. Also presented is a systematic approach to deriving a similarity transformation matrix that transforms a general state-space model to a state-space model corresponding to the Cauer CFE about s = 0 and s = a alternately. The transformation matrix enables an approximate relationship to be established to relate the state vector of the original system and that of the reduced model obtained by the CFE about s = 0 and s = a alternately. The step of transformation to phase variable canonical form is thus eliminated.     

A multipoint continued-fraction expansion for linear system reduction

This note presents a multipoint continued-fraction expansion (MCFE) to obtain reduced models for linear time-invariant systems. Algorithms for the expansion and inversion of the MCFE are outlined. A realization for the MCFE of a transfer function is suggested, and the corresponding MCFE canonical state-space model is established. A new similarity transformation matrix is constructed to transform a state-space model in the phase-variable canonical form to one in the MCFE canonical form. The attractive feature of the present MCFE is that it is general in form and the resulting reduced models approximate well the original system in both the frequency and time responses.     

Optimal digital controller and observer design for multiple time-delay transfer function matrices with multiple input–output time delays

In this article, we address the optimal digital design methodology for multiple time-delay transfer function matrices with multiple input–output time delays. In our approach, the multiple time-delay analogue transfer function matrix with multiple input–output time delays is minimally realised using a continuous-time state-space model. For deriving an explicit form of the optimal digital controller, the realised continuous-time multiple input–output time-delay system is discretised, and an extended high-order discrete-time state-space model is constructed for discrete-time LQR design. To derive a low-order optimal digital observer for the multiple input–output time-delay system, the multiple time-delay state obtained from the multiple time-delay outputs is discretised. Then, the well-known duality concept is employed to design an optimal digital observer using the low-order discretised multiple input time-delay system together with the newly discretised multiple time-delay state. The proposed approach is restricted to multiple time-delay systems where multiple time delays arise only in the input and output, and not in the state.     

Irreducible canonical realizations from external data sequences†

A direct procedure for obtaining a minimal realization of a linear multivariable time-invariant discrete system is described, by considering input/output data sequences as initial characterization.

The main feature of the procedure is to lead to a well-defined canonical form of the state-space matrix triple with a remarkable saving of computing effort

An example is given in order to display the mechanization of this approach     

On a generalized algorithm for the transformation of theinput-output model into the state-space model

A generalised algorithm for transformation from an input-output model into a state-space model, which is also suitable for systems with a nondynamic part, is presented. The algorithm is based on a recently developed fast and accurate method which uses a recursive formula. The derivation of the algorithm is presented and a numerical example is also given. A discrete time invariant linear multivariable and completely observable system given in the canonical state-space form with a nondynamic part are considered     

On-line identification and control of multivariablc discrete-time systems based on a transformed model

Recursive algorithms for on-line combined identification and control of linear discrete-time multivariable systems is presented. A variant of the observable canonical model with one-way coupling form of the state model is used to develop a solution of the problem. Exploiting the canonical structure of the model, the proposed solution turns out to be simpler than that obtained by El-Sherief (1983) and moreover, a combined decentralized state and parameter estimation based control scheme can be developed in three stages. In Stage I, the parameters of the system matrices are estimated by a recursive least-square algorithm or by a normalized stochastic approximation algorithm in decoupled manner. These parameters are then employed for state estimation in Stage 2 using a centralized conventional Kalman filter or by a decentralized adaptive Kalman filter which in turn reduces instrumentation and telemetry costs. Estimated parameters and states are then utilized in Stage 3 to implement the square-root based control law along with the good numerical behaviour of the control problem. The proposed algorithms are tested by considering an example of a third-order state-space model.     

New results in state estimation and regulation

An alternative technique to design linear state estimators and regulators is presented. This technique is based on transfer matrix considerations. The optimal regulator or estimator gain is obtained via spectral factorization and the solution of a simple equation in polynomial matrices.This approach provides further insight, displays the duality of estimation and control nicely, and bridges the state-space and frequency-domain techniques. The resulting design procedure is computationally attractive and particularly simple for system matrices in the observer or controller canonical form.     

Determination of a transfer function matrix in multivariablesystems

A conceptually simple method is presented for determining the system transfer function matrix of linear multivariable systems described by their state-space equations. The polynomial coefficients of the transfer function matrix are computed directly by using the controllability matrix method and the transformation to canonical (phase-variable) form matrices, even if the transformation matrices are singular. The method does not require matrix inversion and calculation of eigenvalues, and requires only O(n³) operations     

Sufficient condition for stable control of discrete-time systems with statistical process model

A method for investigating the stability of discrete-time control systems with statistical uncertainties in model parameters is presented. These uncertainties are due to estimation errors arising in the identification of the process model. A mutually independent representation of these errors is applied. The process model and a controller algorithm are investigated in a state-space form. The closed-loop system is considered to be an autonomous one, with some mutually independent statistics affecting the system coefficients. Sufficient conditions for stability of these systems are derived. The example of a second-order non-minimal-phase system with state-space linear quadratic-problem controller and pole-placement controller is discussed.     

一类MIMO系统连续状态空间模型的参数辨识频域方法

在连续时间状态空间模型的参数辨识中,针对系统状态微分项获取困难这一问题,对输入、状态及输出序列应用离散傅里叶变换,得到复数域线性回归方程,并给出了不同形式的最小二乘解估计式.以飞行器多输入多输出(Multiple-input multiple-output, MIMO)状态空间模型为例,设计正交多正弦信号对系统进行多通道同时激励,在一次激励的情况下就可以辨识出所有模型参数,从而提高辨识实验效率.仿真实验证明了方法的有效性和结果的准确性.     

A transformation in a modified continued fraction expansion

A transformation between the state space model corresponding to the Cauer type continued fraction expansion abouts=0ands rightarrow inftyalternately, and the state-space model of the phase variable canonical form is presented.     

GMV control of non-linear continuous-time systems including common delays and state-space models

A non-linear generalized minimum variance control law is proposed for the control of non-linear continuous-time multivariable systems with common delays on input and output channels. The quadratic cost index involves both error and control signal costing terms. The solution for the control law is obtained using a non-linear operator representation of the plant and a linear state-equation model for the disturbance and reference models. The reference and disturbance models are represented by linear subsystems. However, the plant model can be in a very general non-linear operator form, which could involve state-space, transfer operators or non-linear function look up tables. The structure of the system and criterion is chosen so that a simple controller structure and solution is obtained. The controller obtained is simple to implement, particularly in one form, which might be considered to be a state-space version of a non-linear Smith predictor. The results are related to those for discrete-time systems but the presence of the transport delay terms complicates the solution rather more in the continuous-time case.     

State-space forms for higher-order discrete-time models

This paper presents a fundamental study of the connection between continuous- and discrete-time systems. Provided is a definition for discrete-time models, that is discrete-time systems with a continuous-time counterpart, whose order can be higher than that of the continuous-time system. This definition is based on a comparison in a certain sense on the time responses of continuous- and discrete-time systems. A theorem is presented for relating the higher-order discrete-time models to their continuous-time counterparts, which is an extension of a previous theorem for models with order equal to that of the continuous-time system. State-space forms are derived for models obtained through the use of a certain class of hold elements and through the use of mapping models, and these discrete-time systems are shown to be valid according to the definition. Special cases are models obtained using first-order and slewer hold devices, whose convergence to a continuous-time counterpart has not been shown mathematically before, and mapping models corresponding to two-step linear multi-step methods, which have not previously presented in the state-space form. The derived state-space forms provide a convenient way to implement these models for purposes of analysis, design, and implementation of discrete-time systems and finds applications in such areas as digital signal processing, digital simulation, and digital control.