Srimanti Roychoudhury

Bio: Srimanti Roychoudhury is an academic researcher from Budge Budge Institute of Technology. The author has contributed to research in topics: State space & System identification. The author has an hindex of 3, co-authored 28 publications receiving 35 citations.

Identification of multi-delay systems using orthogonal hybrid functions in state space environment

Abstract: In this paper, a set of orthogonal hybrid functions (HF) is utilised for the identification of non-homogeneous as well as homogeneous multi-delay systems. The HF set works with function samples and reconstructs a function in a piecewise linear manner. This reduces the mean integral square error (MISE) of approximation and also the computational burden compared to other competitive methods like Walsh analysis, block pulse analysis, etc. in general. The presented technique uses a simple algorithm for time-delay system identification. After introducing the HF domain approximation and integration, the HF domain theory of identification of multi-delay systems is presented. To support the theory, many numerical examples are treated to identify both first and second order delay systems. The presented tables and graphs prove that the results obtained are highly reliable to establish the validity of the proposal.

The Hybrid Function (HF) and Its Properties

Abstract: Starting with a brief review of block pulse functions (BPF), sample-and-hold functions (SHF) and triangular functions (TF), this chapter presents the genesis of hybrid functions (HF) mathematically. Then different elementary properties and operational rules of HF are discussed. The chapter ends with a qualitative comparison of BPF, SHF, TF and HF.

One-Shot Operational Matrices for Integration

Abstract: This chapter is devoted to develop the theory of one-shot operational matrices. These matrices are useful for multiple integration and, in general, are superior to repeated integration using the first order integration matrices. Theory of one-shot operational matrices is presented and the one-shot operational matrices of n-th order integration have been derived. Three examples with nine figures and four tables elucidate the technique.

Time Invariant System Analysis: Method of Convolution

Abstract: This chapter presents analysis of both open loop as well as closed loop systems based upon the idea of convolution in HF domain. Three numerical examples have been treated, and for clarity, thirteen figures and six tables have been presented.

New sinusoidal basis functions and a neural network approach to solve nonlinear Volterra–Fredholm integral equations

Abstract: In this paper, we present and investigate the analytical properties of a new set of orthogonal basis functions derived from the block-pulse functions. Also, we present a numerical method based on this new class of functions to solve nonlinear Volterra–Fredholm integral equations. In particular, an alternative and efficient method based on the formalism of artificial neural networks is discussed. The efficiency of the mentioned approach is theoretically justified and illustrated through several qualitative and quantitative examples.

Static output tracking control for non-linear polynomial time-delay systems via block-pulse functions

Abstract: In this paper, a new method is introduced to design static output tracking controllers for a class of non-linear polynomial time-delay systems. The proposed technique is based on the projection of the controlled system and the associated linear reference model that it should follow over a basis of block-pulse functions. The useful properties of these orthogonal functions such as operational matrices jointly used with the Kronecker tensor product may transform the non-linear delay differential equations into linear algebraic equations depending only on parameters of the feedback regulator. The least-squares method is then used for determination of the unknown parameters. Sufficient conditions for the practical stability of the closed-loop system are derived, and a domain of attraction is estimated. The implementation of the proposed method is illustrated on a double inverted pendulums benchmark as well as a two-degree-of- freedom mass-spring-damper system. The simulation results show the effectiven...

Frequency-shifting-based stable on-line algebraic parameter identification of linear systems

Abstract: In this paper a new approach to algebraic parameter identification of the linear SISO systems is proposed. The standard approach to the algebraic parameter identification is based on the algebraic derivatives in Laplace domain as the main tool for algebraic manipulations like elimination of the initial conditions and generation of linearly independent equations. This approach leads to the unstable time-varying state-space realization of the filters for the on-line parameter estimation. In this paper, the finite difference and shift operators in combination with the frequency-shifting property of Laplace transform is applied instead of algebraic derivatives. Resulting state-space realization of the estimator filters is asymptotically stable and doesn’t require switch-of mechanism to prevent overflow of the estimator variables. The proposed method is especially suitable for applications in closed-loop on-line identification where the stable behavior of the estimators is a necessary requirement. The efficiency of the proposed algorithm is illustrated on three simulation examples.