TIME DELAY BASEDUNKNOWN INPUT OBSERVER DESIGN FOR NETWORK CONTROL SYSTEM

Similar documents
Introduction to Numerical Analysis. In this lesson you will be taken through a pair of techniques that will be used to solve the equations of.

Application of Homotopy Analysis Method for Solving various types of Problems of Partial Differential Equations

THE FINITE HAUSDORFF AND FRACTAL DIMENSIONS OF THE GLOBAL ATTRACTOR FOR A CLASS KIRCHHOFF-TYPE EQUATIONS

On the approximation of particular solution of nonhomogeneous linear differential equation with Legendre series

Repetitive Control based on Integral Sliding Mode Control of Matched Uncertain Systems

Formation Control of Multi-agent Systems with Connectivity Preservation by Using both Event-driven and Time-driven Communication

Chapter 2. First Order Scalar Equations

1 Widrow-Hoff Algorithm

Fourier Series & The Fourier Transform. Joseph Fourier, our hero. Lord Kelvin on Fourier s theorem. What do we want from the Fourier Transform?

Mean-square Stability Control for Networked Systems with Stochastic Time Delay

THE APPROXIMATE AND EXACT SOLUTIONS OF THE SPACE- AND TIME-FRACTIONAL BURGERS EQUATIONS

An Extension to the Tactical Planning Model for a Job Shop: Continuous-Time Control

b denotes trend at time point t and it is sum of two

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 13, Number 1/2012, pp

Oscillation Properties of a Logistic Equation with Several Delays

2.1 Harmonic excitation of undamped systems

SOLUTIONS TO ECE 3084

LAPLACE TRANSFORM AND TRANSFER FUNCTION

Higher Order Difference Schemes for Heat Equation

An approximate solution for a generalized Hirota-Satsom coupled (Kdv) equation

Phasor Estimation Algorithm Based on the Least Square Technique during CT Saturation

Stability and Bifurcation in a Neural Network Model with Two Delays

For demonstration of the concept of HAM, by considering general non-linear problem (1) Non-linear operator is N and v (t) [ ],

Stochastic modeling of nonlinear oscillators under combined Gaussian and Poisson White noise

Chapter 9 Sinusoidal Steady State Analysis

MODELING AND CONTROL OF THE ACTIVE SUSPENSION SYSTEM USING PROPORTIONAL INTEGRAL SLIDING MODE APPROACH

Mapping in Dynamic Environments

Homework 2 Solutions

Connectionist Classifier System Based on Accuracy in Autonomous Agent Control

arxiv: v1 [math.na] 5 Mar 2013

Anti-Disturbance Control for Multiple Disturbances

Forgetting Factor Nonlinear Functional Analysis for Iterative Learning System with Time-Varying Disturbances and Unknown Uncertain

Polynomial Adjustment Costs in FRB/US Flint Brayton, Morris Davis and Peter Tulip 1 May 2000

A Nonexistence Result to a Cauchy Problem in Nonlinear One Dimensional Thermoelasticity

Dead-time Induced Oscillations in Inverter-fed Induction Motor Drives

An Efficient Approach for Fractional Harry Dym Equation by Using Homotopy Analysis Method

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

h[n] is the impulse response of the discrete-time system:

Analytical Approximation of Nonlinear Vibration of Euler-Bernoulli Beams

A Decision Model for Fuzzy Clustering Ensemble

DUALITY IN NONLINEAR FRACTIONAL PROGRAMMING PROBLEM USING FUZZY PROGRAMMING AND GENETIC ALGORITHM

Joint Spectral Distribution Modeling Using Restricted Boltzmann Machines for Voice Conversion

Lecture 4 Notes (Little s Theorem)

1. Calibration factor

Underwater vehicles: The minimum time problem

Stabilization of NCSs: Asynchronous Partial Transfer Approach

STATE-SPACE MODELLING. A mass balance across the tank gives:

This document was generated at 1:04 PM, 09/10/13 Copyright 2013 Richard T. Woodward. 4. End points and transversality conditions AGEC

1 Introduction. Keywords: Passive radar, likelihood function, Fisher information, tracking, estimation.

Class Meeting # 10: Introduction to the Wave Equation

Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning

SIGNALS AND SYSTEMS LABORATORY 8: State Variable Feedback Control Systems

A HEURISTIC OPTIMIZATION METHOD OF FRACTIONAL CONVECTION REACTION An Application to Diffusion Process

The Homotopy Analysis Method for Solving Multi- Fractional Order Integro- Differential Equations

Optimal Stopping of Partially Observable Markov Processes: A Filtering-Based Duality Approach

Stochastic Network Optimization with Non-Convex Utilities and Costs

ROBOTICA. Basilio Bona DAUIN Politecnico di Torino. Basilio Bona ROBOTICA 03CFIOR 1

An Adaptive Quantum-inspired Differential Evolution Algorithm for 0-1 Knapsack Problem

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

Sliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game

Transitivity of Commutativity for Linear Time-Varying Analog Systems. Mehmet Emir KOKSAL

CHANNEL ESTIMATION FOR SPACE-TIME ORTHOGONAL BLOCK CODES. Cristian Budianu and Lang Tong

Module 4: Time Response of discrete time systems Lecture Note 2

Complete solutions to Exercise 14(b) 1. Very similar to EXAMPLE 4. We have same characteristic equation:

The Anthropomorphic Robot Arm Joint Control Parameter Tuning Based on Ziegler Nichols PID Renli WANG 1, a, Yueming DAI 2, b

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS

A Simple Control Method for Opening a Door with Mobile Manipulator

Form finding analysis based on variational method for multistable structure utilizing snap-through behaviour

Georey E. Hinton. University oftoronto. Technical Report CRG-TR February 22, Abstract

15. Vector Valued Functions

Linear Response Theory: The connection between QFT and experiments

Robust Control Over a Packet-based Network

Lecture 23 Damped Motion

Online Appendix to Solution Methods for Models with Rare Disasters

Research Article Synchronization of the Extended Bonhoffer-Van der Pol Oscillators

Adaptation and Synchronization over a Network: stabilization without a reference model

Sliding Mode Controller for Unstable Systems

Analytical Solution for the Time-Dependent Emden-Fowler Type of Equations by Homotopy Analysis Method with Genetic Algorithm

arxiv: v3 [math.na] 9 Oct 2017

Electroelastic Actuators for Nano- and Microdisplacement

Signal and System (Chapter 3. Continuous-Time Systems)

Estimates and Forecasts of GARCH Model under Misspecified Probability Distributions: A Monte Carlo Simulation Approach

The Operational Semantics of Hybrid Systems

Conduction Equation. Consider an arbitrary volume V bounded by a surface S. Let any point on the surface be denoted r s

Problem set 2 for the course on. Markov chains and mixing times

Riemann Hypothesis and Primorial Number. Choe Ryong Gil

Coherent Targets DOA Estimation Using Toeplitz Matrix Method with Time Reversal MIMO Radar. Meng-bo LIU, Shan-lu ZHAO and Guo-ping HU

In this chapter the model of free motion under gravity is extended to objects projected at an angle. When you have completed it, you should

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

OPTIMAL CAPACITOR PLACEMENT FOR POWER LOSS REDUCTION AND VOLTAGE STABILITY ENHANCEMENT IN DISTRIBUTION SYSTEMS

Available online at I-SEEC Proceeding - Science and Engineering (2013)

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

ANALYSIS OF LINEAR AND NONLINEAR EQUATION FOR OSCILLATING MOVEMENT

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Multivariate Auto-Regressive Model for Groundwater Flow Around Dam Site

FORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSIS

Chapter 3 Boundary Value Problem

Reading. Lecture 28: Single Stage Frequency response. Lecture Outline. Context

10. State Space Methods

Transcription:

TIME DELAY ASEDUNKNOWN INPUT OSERVER DESIGN FOR NETWORK CONTROL SYSTEM Siddhan Chopra J.S. Laher Elecrical Engineering Deparen NIT Kurukshera (India Elecrical Engineering Deparen NIT Kurukshera (India ASTRACT Many odern conrol syses use counicaion neworks o exchange inforaion aong syse s coponens. Due o inserion of counicaion nework hese syses are ofen subjeced o disurbances perurbaion ec. This paper deals wih he observer design proble for he nework conrol syses wih unknown inpus. In his paper he exising approach wih one delay in feedback sysehas been exended by insering wo counicaion neworks wih individual respecive delays in observaion and conrol channels. Nework effec is anifesed in ers of iedelayin signals exchanged beween coponens.a nuerical exaple is also presened and siulaed using MATLA/SIMULINK o deonsrae he approach. Index Ters: Nework Conrol Syse Observer Siulink Tie DelayUnknown Inpu.. INTRODUCTION A conrol syse in which is coponens such as plan sensors acuaors are spaially disribued is called Nework Conrol Syse (NCS. In such syses counicaion akes place via a band-liied counicaion nework. One of he os proinen feaure of he NCS is ha exchange of inforaion beween syse s coponens akes place in for of inforaion packes. NCSs has been an area of exensive research over he pas few decades due o is increased flexibiliy lower coss siple insallaion and easy ainenance ec. On he oher hand here has been soe serious issues due o he use of counicaion nework such liied bandwidh nework induced delay packe dropou. These probles us be look ino as hese can have adverse effec on syse sabiliy. The ypical NCS srucure is shown in Fig... Lieraure review The roos of observer design can be raced back o lae 960s when Luenberger firs designed observer in 966 []. Since hen differen ypes of observers have been developed which are being used in various engineering applicaions. As he large scale syses are ore suscepible o high disurbance and fauls he sudy of UIOs becoe ore pivoal []. Mos of he UIOsproposed in lieraure are for non-neworked syses []. haacharya [4] provided he soluion o he observer design proble for syses subjeced o unknown inpus or 8 P a g e

disurbances.one siple ehod was proposed by Darouach e al. [5] for designing he full order observer he necessary and sufficien condiions for his observer were given. Kobayashi and Nakaizo [6] suggesed an approach based on Silveran s inverse ehod. On he oher hand Hui and Zak [7] proposed a projecion operaor approach. Recenly an UIO was designed by Taha e al. [] for nework conrol syse sabiliy guaranee bounds for he delay and perurbaion induced by nework were also esablished. Plan Acuaor Sensor Counicaion Nework Observer and Conroller Fig Typical Nework Conrol Syse II SYSTEM MODELLING Proposed archiecure for a neworked unknown inpu observer schee is shown in Fig. The inpu o he observer block are heknown inpu u and delayed version of he plan s oupu ha is ŷ. We have assued ha hese wo quaniies are known o he observer block. The innovaion block is differen for differen observers []. Esiae of plan sae ha is x is he oupu of he observer. Reference inpu (V ˆ ref and x acs as inpus o he conroller. The ˆ unknown inpu for he plan is aken as u ha can be any non-lineariy or any unknown plan disurbance.. Review of unknown inpu observer for non-neworked syses: Zak & Hui [] inroduced a projecion operaor approach based on which observer is designed in his paper. We have considered he Linear-Tie invarian (LTI class of syses. The dynaics of plan is given ( x A x u u as: where nn A n n x is plan sae u is known inpu u is unknown inpu y is oupu respecively. I is assued ha A are all 84 P a g e

known syse paraeers. For he non-neworked syse he dynaics of unknown inpu observer (UIO as presened in [] are: z I MC A z A My u L y C z C My ( x z My ( ˆ ( ( ( Plan Model û x x Counicaion (0 Nework ( x A x u u ( Sensor y Counicaion u v ref Nework ( Conroller u kx v x ˆ ˆ ref Unknown Inpu Observer [ z Y ] x I ˆ z z D z Y z A z Y z z z ŷ Y f ( yˆ Innovaion lock z (0 Fig. Neworked UIO Archiecure where M n p is chosen such ha ( ( I MC 0 (4 and L is he addiional gain o iprove he convergence rae []. The iniial condiions for he observer for he above z(0 ( I MC xˆ (0 dynaical syse are (5 The designed observer for he non-neworked syse converges esiaion error o zeroas under he assupion ha he pair (C A is deecable[]. In order o analyse he effec of counicaion nework on sae esiaion he dynaics of he observer by aking x c zcan be wrien as follows: x I MC A x A My u L y C x C My (6 ( ( ( c c c ( x A x y u (7 c c c c c where 85 P a g e

A ( I MC ( A LC ( I MC ( A M L LC M ( I MC c c ( c dynaics of he UIO will ge changed due he presence of he counicaion nework beween plan and observer and can be wrien as follows: ( x A x yˆ u (8 xˆ x Myˆ (9 c c c c c c we assue sae feedback conrol is used: u kxˆ k( x Myˆ c (0 The III NETWORK EFFECT AS PURE TIME DELAY. Closed Loop Dynaics As can be seen in figure ( we have insered wo counicaion neworks one beween unknown inpu observer (UIO and is inpus and anoher one beween conroller and plan due o which plan ges he delayed inpu. In his yˆ y( secion we odel he counicaion nework effec as pure ie-delay. So i is assued ha uˆ u( where and are he ie-delays occurring due o nework effec. Rewriing he dynaics of he observer and conroller in he disinc for of NCS observer/conroller while assuing ha he innovaion funcion of he observer is ebedded in UIO dynaics : ( ( x ( A x ( y( u ( u C x D y c c c c c c c c ( ( ( ( where Cc k and D c km Sae dynaics of plan and conroller can be wrien as: x ( A x ( u ( u ( (4 ( A x ( C x ( D C x ( ( u ( ( c c c x ( A x ( y( u ( ( c c c c c ( ( (5 A x ( C x ( C x ( D C x ( c c c c c c c c Cobining he above wo equaions o find x ( x ( x ( x ( c (6 y siplifying (6 we ge x ( x( x( x( x( ( u ( 0 4 (7 86 P a g e

where A 0 0 0 ( A C c c c 0 0 C D C 0 c c c ( 0 C 0 0 c D C 0 0 0 c 4 (. NCS and Approxiaion of Tie-Delay Fro [] we have x ( 0 x ( 0 c 0 Taking he second derivaive of x( and subsiuing he above approxiaion we have x( x ( u ( (8 0 4 Using he following aylor series expansion for x(-a: n n a ( n x( a ( x ( (9 n! n0 Neglecing he higher order ers we ge x x x x ( ( ( ( (0 x( x( x( x( x( x( x ( x( ( where Subsiuing (0( in (7 we x ( x( [ x( x ( x( ] [ x( x ( x( ] [ x( x ( x( ] u ( ( 0 4 ge Subsiuing (8 in above equaion x x x x x u x x x u ( ( [ ( ( ( ( ( ] [ ( ( ( ( ( ] 0 0 4 0 4 ( [ x( x ( ( x ( u ( ] u ( 0 4 4 Rearranging he above ers we ge x( x( u ( u ( 0 where (5 (4 87 P a g e

( 0 0 ( 4 4 4 4 ( I ( 0 0 0.Tie-Delay ased UIO Design for Neworked Syse In his secion conroller and observer is designed in order o iniize he effec of uliple delay ers as well as of he uknown inpu fro he dynaics of he closed loop syse. We know D C 0 0 0 c 4 0 and 4 ( D C ( c 0 0 0 The observer is o be designed in such a way ha effec of uliple delay ers and unknown inpu is nullified. So ( his eans should resul equal o zero i.e 0 D C 0 or D 0 (6 Subsiuing he 4 4 c c value of Dc km in he above equaion we ge km 0 and we know ha he lone condiion for he ( ( I MC 0 (7 exisence of UIO for he non-neworked syses as in []: So o design he observer ( km 0 (8 ( I MC 0 we have he following equaions o solve: variable o be solved for he design of he Neworked UIO []. (9 As we don have uch conrol over k so M is he p Now uliplying equaion (9 by a non-singular arix H and hen adding i in equaion (8 we ge ( ( km H MC H 0 n p (0 we ge he quadraic equaion in ers of M i.e Neworked UIO design variable. nn Le R k hen above equaion can be represened ( ( as RM H MC H 0 ( n p Above equaion can be wrien as follows: MA M C 0 n p ( Hence he Neworked UIO can be designed by solving equaion (. IV UNKNOWN INPUT OSERVER DESIGN EXAMPLE FOR A NETWORKED SYSTEM In his secion we deonsrae he exaple for he proposed Neworked UIO design following he algorih and algorih given in []. We assue ha he given syse has one known inpu one unknown inpu and one oupu. 88 P a g e

5 0 A C 0 0 4 ( 4 0 4 0 4 Neworked UIO exisence: rank( C ( =; rank( = ( As boh ranks are equal o so he UIO exis. Copue he design arix M : Following he algorih given in [] we ge M 0.8 0.667 0.09 Copue P : 0.676 0.748 0.8 P I MC 0.4 0. 0.667 n 0.058 0.64.09 4 Find Q : 0.88 0.709 0.579 Q 0.468 0.674 0.050 0.0806 0.74 0.8477 5 Copue A and C : ( 9.87.766 4.5565 A A 4.8066.998 5.468 ( C A A C C.87 0.07 5.847 A ( 0 4.08 0 6 Copue eigen values of eigen( ( A : ( A = [ 0.79.04] 7 Since he eigen values of deecable. ( A are negaive which eans ha he arix is sable hen ( A C ( is 8 Design gain L:.448 A C 4.6087 7.04 L= place ( 0 89 P a g e

( 9 Copue NCS paraeers i.e A : c c c.88.5689 4.760 0.88 A P ( A LC.5500.48.9409 P ( A M L LC M 0.595 c c.9685 6.5984.49 0.0007 P ( c 0 UIO observer for he neworked syse can be wrien as follows: x A x yˆ u ( c c c c c xˆ x Myˆ c We assue he sae iniial condiion of plan sae and unknown inpu observer sae as used in [] i.e x 0.56 (0 0.04 and 0.79 x c 6.66 (0.66 6.66 and he unknown inpu is aken as u ( 0.5sin(. Fig. ( and Fig (4 shows he esiaion of plan saes. V SIMULATION RESULTS 5. For Non-Neworked Syse ( 0 Fig. shows he esiaion of plan saes for non-neworked syse wih unknown inpus. Fig (a 90 P a g e

Fig. (b Fig. (c Fig. Siulaion Resuls of Esiaion of Saes for Non-Neworked UIO 5. For Neworked Syse ( 0 0 Fig. 4 shows he esiaion of plan saes for neworked conrol syse. Fig. 4(a 9 P a g e

Fig. 4(b 4(c. Fig. 4 Siulaion Resuls of Esiaion of Saes For Neworked UIO V CONCLUSION NCS has been an acive research area over he years due o wide variey of applicaions. In his paper a ie delay based unknown inpu observer for neworked conrol syse has been proposed.the presence of counicaion neworks adds ie delay o he syse. For differen counicaion neworks individual respecive ie delays are considered. The approach of unknown inpu observer design [] wihou ie delays (non-neworked syse has been reviewed o exend he approach o neworked syse. The closed loop dynaics for nework conrol syse wih unknown inpu observer has been proposed o iniize he effec of ie delay and effec of unknown inpu on sae esiaion. The siulaed resuls of nuerical exaple shows ha he esiaed saes are alos converging o original saes using he proposed approach. For fuure work we would like o exend our resuls o larger delays plus we would like o ake ino coun he copuaion ie of conrol law. 9 P a g e

REFERENCES. S. Hui S.H. Zak Observer Design for Syse wih Unknown inpus Inernaional Journal of Applied Maheaics and Copuer Science Vol. 5 No.4 pp. 4-446 005.. Ahad F. Taha Ahed Elahdi Jiesh H. PanchalDengfeng Sun Unknown Inpu Observer Design and Analysis for Neworked Conrol Syses Inernaional Journal of Conrol 05.. D. G. Luenberger Observers for ulivariable syses. IEEE Transacions on Auoaic Conrol vol. AC- no. pp. 90 97 966. 4. S. P. haacharyya Observer design for linear syses wih unknown inpus IEEE Transacions on Auoaic Conrol vol. no. pp. 48 484 978. 5. M. Darouach M. Zasadzinski S. J. Xu Full-order observers for linear syses wih unknown inpus IEEE Transacions on Auoaic Conrol vol. 9 no. pp. 606 609 994. 6. N. Kobayashi and T. Nakaizo "An Observer design for linear syses wih unkown inpus" Inernaional Journal of Conrol vol. 5 pp 605-69 98. 7. S. Hui and S. H. Zak Observer design for syses wih unknown inpus Inernaional Journalof Applied Maheaics and Copuer Science vol. 5 no. 4 pp. 4 446 005. 8. Ahad F. Taha Ahed Elahdi Jiesh H. PanchalDengfeng Sun Neworked Unknown Inpu Observer Analysis and Design for Tie Delay Syses IEEE Inernaional Conference on Syses Man and Cyberneics04. 9 P a g e