Analysis of linear time-varying systems and bilinear systems via shifted Chebyshev polynomials of the second kind

Linear time-varying systems and bilinear systems are analysed via shifted Chebyshev polynomials of the second kind. Using the operational matrix for integration and the product operational matrix, the dynamical equation of a linear time-varying system (or bilinear system) is reduced to a set of simultaneous linear algebraic equations. The coefficient vectors of shifted Chebyshev polynomials of the second kind can be determined by using the least-squares method. Illustrative examples show that shifted Chebyshev polynomials of the second kind having a finite number of terms are more accurate than either the Legendre or Laguerre methods.     

Integration of Dynamic Equation of Spring-Mass-Damper Systems via Chebyshev Polynomials

A numerical scheme based on Chebyshev polynomials for the determination of the response of spring-mass-damper systems is presented. The state vector of the differential equation of the spring-mass-damper system is expanded in terms of Chebyshev polynomials. This expansion reduces the original differential equations to a set of linear algebraic equations where the unknowns are the coefficient of Chebyshev polynomials. A formal procedure to generate the coefficient matrix and the right-hand side vector of this system of algebraic equations is discussed. The numerical efficiency of the proposed method is compared with that of Runge-Kutta method. It is shown that this scheme is accurate and is computationally efficient.     

Analysis and optimal control of linear time-varying systems via general orthogonal polynomials

The operational matrix consisting of the product of two time functions, and the operational matrices for forward or backward integration consisting of general orthogonal polynomials are derived, respectively, for the analysis and optimal control of linear time-varying systems with a quadratic performance measure. The present results include results obtained via Chebyshev, Legendre, Laguerre, Jacobi, Hermite and ultraspherical polynomials as special cases.     

An efficient method based on the second kind Chebyshev wavelets for solving variable-order fractional convection diffusion equations

In this paper, a class of variable-order fractional convection diffusion equations have been solved with assistance of the second kind Chebyshev wavelets operational matrix. The operational matrix of variable-order fractional derivative is derived for the second kind Chebyshev wavelets. By implementing the second kind Chebyshev wavelets functions and also the associated operational matrix, the considered equations will be reduced to the corresponding Sylvester equation, which can be solved by some appropriate iterative solvers. Also, the convergence analysis of the proposed numerical method to the exact solutions and error estimation are given. A variety of numerical examples are considered to show the efficiency and accuracy of the presented technique.     

Application of discrete Chebyshev polynomials to the optimal control of digital systems

The shift transformation matrix for discrete Chebyshev polynomials is introduced in this study. The discrete variational principle combined with the idea of penalty function is taken to construct the modified discrete Euler-Lagrange equations. Then, the discrete Chebyshev series are applied to simplify the modified equations into a set of linear algebraic ones for the approximations of state and control variables of digital systems. It is seen that this technique is quite straightforward and simple, and computing time can be saved considerably.     

广义正交多项式用于时变延时线性系统的参数辨识

应用广义正交多项式(GOP)的展开式估计时变延时线性系统的参数.其基本思想是状 态函数和控制函数分别用有限多项广义正交多项式表示,利用GOP的运算矩阵,将时变延时 微分方程转化为用展开系数表示的线性方程组,通过输入输出数据,参数能够辨识.     

Predictive control for a class of distributed delay systems using Chebyshev polynomials

In this paper, the model predictive control (MPC) is developed for linear time-varying systems with distributed time delay in state. The Chebyshev operational matrices of product, integration and delay are utilized to transform the solution of distributed delay differential equation to the solution of algebraic equations. The Chebyshev functions are also applied to derive approximate solution of finite horizon optimal control problem involved in MPC. The proposed method is simple and computationally advantageous. Illustrative example demonstrates the validity and applicability of the technique.     

Construction of optimal feedback control for nonlinear systems via Chebyshev polynomials

A method is proposed to determine the optimal feedback control law of a class of nonlinear optimal control problems. The method is based on two steps. The first step is to determine the open-hop optimal control and trajectories, by using the quasilinearization and the state variables parametrization via Chebyshev polynomials of the first type. Therefore the nonlinear optimal control problem is replaced by a sequence of small quadratic programming problems which can easily be solved. The second step is to use the results of the last quasilinearization iteration, when an acceptable convergence error is achieved, to obtain the optimal feedback control law. To this end, the matrix Riccati equation and another n linear differential equations are solved using the Chebyshev polynomials of the first type. Moreover, the differentiation operational matrix of Chebyshev polynomials is introduced. To show the effectiveness of the proposed method, the simulation results of a nonlinear optimal control problem are shown.     

基于二类切比雪夫正交多项式非参数混合模型的图像分割

有参混合模型需要假设模型为某种已知的参数模型,而实际数据往往很难假设出这种参数模型的分布.为此,提出一种二类切比雪夫正交多项式的非参数图像混合模型分割方法.首先,设计出一种基于二类切比雪夫正交多项式的图像非参数混合模型,每一个模型的平滑参数根据误差方法和最小的准则进行计算.然后,利用随机期望最大(SEM)算法求解正交多项式系数和每一个模型的权重.此方法不需要对模型作任何假设,可以有效克服有参混合模型与实际数据分布不一致的问题.实验表明,该方法比高斯混合模型分割效率更高,并比其他非参数正交多项式混合模型有更好的分割效果.     

Some New Properties of the Chebyshev Polynomials and Their Use in Analysis and Design of Dynamic Systems

The possibility of essential simplification of the procedure of approximate analysis and design of various systems obeying the operator equations in appropriate functional spaces was demonstrated by taking into account the new properties of the Chebyshev polynomials of the first and second kinds.     

迭代学习控制在线性时变系统终端控制问题中的应用研究

An iterative learning control algorithm based on shifted Legendre orthogonal polynomials is proposed to address the terminal control problem of linear time-varying systems. First, the method parameterizes a linear time-varying system by using shifted Legendre polynomials approximation. Then, an approximated model for the linear time-varying system is deduced by employing the orthogonality relations and boundary values of shifted Legendre polynomials. Based on the model, the shifted Legendre polynomials coefficients of control function are iteratively adjusted by an optimal iterative learning law derived. The algorithm presented can avoid solving the state transfer matrix of linear time-varying systems. Simulation results illustrate the effectiveness of the proposed method.     

Study on the Application of Iterative Learning Control to Terminal Control of Linear Time-varying Systems

An iterative learning control algorithm based on shifted Legendre orthogonal polynomials is proposed to address the terminal control problem of linear time-varying systems. First, the method parameterizes a linear time-varying system by using shifted Legendre polynomials approximation. Then, an approximated model for the linear time-varying system is deduced by employing the orthogonality relations and boundary values of shifted Legendre polynomials. Based on the model, the shifted Legendre polynomials coefficients of control function are iteratively adjusted by an optimal iterative learning law derived. The algorithm presented can avoid solving the state transfer matrix of linear time-varying systems. Simulation results illustrate the effectiveness of the proposed method.     

Solutions of convolution integral and integral equations via double general orthogonal polynomials

Double general orthogonal polynomials are developed in this work to approximate the solutions of convolution integrals, Volterra integral equations, and Fredholm integral equations. The proposed method reduces the computations of integral equations to the successive solution of a set of linear algebraic equations in matrix form; thus, the computational complexity is considerably simplified. Furthermore, the solutions obtained by the general orthogonal polynomials include as special cases solutions by Chebyshev polynomials, Legendre polynomials, Laguerre polynomials, or Jacobi polynomials. A comparison of the results obtained via several different classical orthogonal polynomial approximations is also presented.     

A new approach for parameter identification of time-varying systems via generalized orthogonal polynomials

A very effective method of using the generalized orthogonal polynomials (GOP) for identifying the parameters of a process whose behaviour can be modelled by a linear differential equation with time-varying coefficients in the form of finite-order polynomials is presented. It is based on the differentiation operational matrix of the GOP, which can represent all kinds of individual orthogonal polynomials. The main advantage of using the differentiation operational matrix is that parameter estimation can be made starting at any time of interest, i.e. without the restriction of starting at zero time. In addition, the present computation algorithm is simpler than that of the integration operational matrix. Using the concept of GOP expansion for state and control functions, the differential input-output equation is converted into a set of linear algebraic equations. The unknown parameters are evaluated by a weighted least-squares estimation method. Very satisfactory results for illustrative example are obtained.     

Chebyshev polynomial solution of the system of Cauchy-type singular integral equations of the first kind

This paper presents a Chebyshev series method for the numerical solutions of system of the first kind Cauchy type singular integral equation (SIE). The Chebyshev polynomials of the second kind with the corresponding weight function have been used to approximate the density functions. It is shown that the numerical solution of system of characteristic SIEs is identical to the exact solution when the force functions are cubic functions.     

Analysis of time-delay systems via shifted Chebyshev polynomials of the first and second kinds

A novel and general approach for obtaining the delay operational matrix of shifted Chebyshev polynomials of first or second kind is presented. This operational matrix is exact in the sense that it does not involve any approximation. Next, this paper shows the application of the delay operational matrix in the analysis of time-delay systems. Two illustrative examples are included and the results are compared with those obtained by the exact method.     

PARALLEL PSEUDOSPECTRAL SOLUTION OF FINANCIAL PARTIAL DIFFERENTIAL EQUATIONS

Abstract

We apply the Pseudospectral method to two fundamental financial equations: the Black-Scholes equation and the Cox Ingersoil Ross model of the term structure of interest rates. The former is used to price a European Call Option and the latter to price a zero coupon bond. Chebyshev polynomials are used as the basis functions and Chebyshev collocation points for the space discretisation. The Crank-Nicolson scheme is used for the time differencing. We have developed a C++ program to solve general second order linear parabolic equations, A parallel quasi-minimal residual version of the Bi-Conjugate Gradient stabilised algorithm is applied to solve the linear system on the AP3000, a parallel computer. The regular space domain and the smooth solutions often encountered in finance suggest the suitability of using this higher order technique.     

Application of general orthogonal polynomials to the optimal control of time-varying linear systems

The operational matrices for forward or backward integration of general orthogonal polynomials are derived. The tensor expression for the generalized orthogonal polynomial approximation of any two arbitrary functions is also introduced. It is shown that the approximation solution obtained using the Chebyshev polynomial is readily obtainable as a special case of the results derived. Thus, the present results include results presented by Shih in 1983 and Chou and Horng in 1984. A linear time-varying optimal-control system with a quadratic performance measure is solved by using the generalized orthogonal polynomials. Comparison of the results with those obtained using several different classical orthogonal polynomial approximations is also included     

利用移位勒让德多项式对时变双线性系统的辨识

本文提出了利用移位勒让德(Shifted Legendrc)多项式辨识时变双线性系统的一个方法。首先,利用移位勒让德多项式展开和积分运算矩阵,把微分方程化为便于计算机计算的矩阵代数方程形式;然后解代数方程从而得到双线性系统未知时变参数的估计;最后给出了仿真例子。本文的方法不仅简化了计算,而且给出了相当精确的辨识结果。     

Optimal control of deterministic systems described by integrodifferential equations

The synthesis of an optimal control function for deterministic systems described by integrodifferential equations is investigated. By using the elegant operational properties of shifted Chebyshev polynomials, a direct computational algorithm for evaluating the optimal control and trajectory of deterministic systems is developed. An example is given to illustrate the utility of this method, and other orthogonal functions are also shown for comparison.