Digital PI Controller Equations

Similar documents
Lesson 16: Basic Control Modes

The Decibel and its Usage

6. Hamilton s Equations

Non-Ideality Through Fugacity and Activity

Lecture 12: Discrete Laplacian

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index

2-Adic Complexity of a Sequence Obtained from a Periodic Binary Sequence by Either Inserting or Deleting k Symbols within One Period

3. MODELING OF PARALLEL THREE-PHASE CURRENT-UNIDIRECTIONAL CONVERTERS 3. MODELING OF PARALLEL THREE-PHASE CURRENT-

Mechanical Systems Part B: Digital Control Lecture BL4

= z 20 z n. (k 20) + 4 z k = 4

1 Matrix representations of canonical matrices

Digital Signal Processing

PID Controller Design Based on Second Order Model Approximation by Using Stability Boundary Locus Fitting

( ) = ( ) + ( 0) ) ( )

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

MAE140 - Linear Circuits - Winter 16 Final, March 16, 2016

Difference Equations

Design of Recursive Digital Filters IIR

Model Reference Adaptive Temperature Control of the Electromagnetic Oven Process in Manufacturing Process

Complex Numbers, Signals, and Circuits

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry

Implicit Integration Henyey Method

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

Advanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function

Translational Equations of Motion for A Body Translational equations of motion (centroidal) for a body are m r = f.

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Iterative General Dynamic Model for Serial-Link Manipulators

Comparing two Quantiles: the Burr Type X and Weibull Cases

12. The Hamilton-Jacobi Equation Michael Fowler

Homework Assignment 3 Due in class, Thursday October 15

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1

Combinational Circuit Design

Naïve Bayes Classifier

One-sided finite-difference approximations suitable for use with Richardson extrapolation

CHAPTER 14 GENERAL PERTURBATION THEORY

The optimal delay of the second test is therefore approximately 210 hours earlier than =2.

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Limited Dependent Variables

PHYS 705: Classical Mechanics. Calculus of Variations II

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017)

The Minimum Universal Cost Flow in an Infeasible Flow Network

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Confidence intervals for weighted polynomial calibrations

10. Canonical Transformations Michael Fowler

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

Evaluating Thermodynamic Properties in LAMMPS

Lecture Note 3. Eshelby s Inclusion II

Numerical Heat and Mass Transfer

A new Approach for Solving Linear Ordinary Differential Equations

Using Genetic Algorithms in System Identification

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

290 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL. 45, NO. 3, MARCH H d (e j! ;e j!

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations

Aerodynamic database for low-rise buildings

AGC Introduction

The Bellman Equation

Research Article Optimal Policies for a Finite-Horizon Production Inventory Model

On the presence of equilibrium points in PI control systems with send-on-delta sampling

DEMO #8 - GAUSSIAN ELIMINATION USING MATHEMATICA. 1. Matrices in Mathematica

Linear Feature Engineering 11

Linear system of the Schrödinger equation Notes on Quantum Mechanics

Michael Batty. Alan Wilson Plenary Session Entropy, Complexity, & Information in Spatial Analysis

Not-for-Publication Appendix to Optimal Asymptotic Least Aquares Estimation in a Singular Set-up

8.6 The Complex Number System

Affine and Riemannian Connections

Department of Statistics University of Toronto STA305H1S / 1004 HS Design and Analysis of Experiments Term Test - Winter Solution

2 Finite difference basics

SELECTION OF MIXED SAMPLING PLANS WITH CONDITIONAL DOUBLE SAMPLING PLAN AS ATTRIBUTE PLAN INDEXED THROUGH MAPD AND LQL USING IRPD

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions

Kernel Methods and SVMs Extension

Linear Approximation with Regularization and Moving Least Squares

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg

A General Class of Selection Procedures and Modified Murthy Estimator

NUMERICAL DIFFERENTIATION

MAE140 - Linear Circuits - Winter 16 Midterm, February 5

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is.

Problem Set 9 Solutions

10-701/ Machine Learning, Fall 2005 Homework 3

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems

PHYS 705: Classical Mechanics. Hamilton-Jacobi Equation

Exercises. 18 Algorithms

Algorithms for factoring

1 Generating functions, continued

The Fundamental Theorem of Algebra. Objective To use the Fundamental Theorem of Algebra to solve polynomial equations with complex solutions

Lecture 10 Support Vector Machines II

Mathematics Intersection of Lines

Solutions to Problem Set 6

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration

ACTM State Calculus Competition Saturday April 30, 2011

Erratum: A Generalized Path Integral Control Approach to Reinforcement Learning

Cubic Trigonometric B-Spline Applied to Linear Two-Point Boundary Value Problems of Order Two

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

The Dirac Equation for a One-electron atom. In this section we will derive the Dirac equation for a one-electron atom.

FE REVIEW OPERATIONAL AMPLIFIERS (OP-AMPS)( ) 8/25/2010

Trees and Order Conditions

SOLVING NON-LINEAR SYSTEMS BY NEWTON s METHOD USING SPREADSHEET EXCEL Tay Kim Gaik Universiti Tun Hussein Onn Malaysia

Transcription:

Ver. 4, 9 th March 7 Dgtal PI Controller Equatons Probably the most common tye of controller n ndustral ower electroncs s the PI (Proortonal - Integral) controller. In feld orented motor control, PI controllers are wdely used for nner current control loos. In dgtal ower suly control, t fnds alcaton n buck, boost, SEPIC, and many other ower toologes. In general, the controller may be desgned to meet secfcatons exressed n ether the tme doman or the frequency doman. me doman secfcatons tycally constran roertes of the transent resonse, such as overshoot, settlng tme, and rse tme. Frequency doman secfcaton nvolves the selecton of a sngle real ero. Ether way, the result s two real numbers corresondng to the gans n the roortonal and ntegral aths. More nformaton on transent tunng usng PI control can be found n the Control heory Fundamentals semnar, and n chater 3 of the accomanyng book []. In ths aer we wll focus on the relatonsh between the gans of contnuous tme (analogue) and dscrete tme (dgtal) PI controllers. We begn by descrbng two common confguratons of controller (seres and arallel), both of whch can be exressed n a smle ero lus ntegrator transfer functon. We then transform ths nto dscrete tme form and comare the dfference equaton wth those of ractcal seres and arallel PI mlementatons. he objectve s to fnd a ar of equatons for each confguraton whch relate the dscrete tme roortonal gans wth those of the corresondng contnuous tme orgnal.. Controller Confguratons he PI controller may be mlemented n ether of two confguratons: seres or arallel. he arallel confguraton s shown below. Fgure In ths confguraton, roortonal and ntegral gans aear n arallel aths. Concetually, the rocess of tunng the controller for transent resonse s straghtforward: one adjusts each gan n turn, blendng together dfferent amounts of roortonal and ntegral control acton, untl the desred secfcatons are met. he arallel PI controller transfer functon s (by nsecton of Fg. ) K K s K s) K () s s An alternatve, but related, confguraton s the seres confguraton (shown below) n whch the roortonal gan aears n seres wth the controller. An attracton of ths structure s that there s less nter-acton between the two gans, slghtly smlfyng the tunng rocess. Note that the seres confguraton cannot be used n alcatons where ero roortonal gan mght be requred.

Fgure he transfer functon of the seres PI controller s (Fg. ) s K K s K K s) K s s () Comarng equatons () and (), we see the relatonsh between seres and arallel controller gans s: K K ; K K K (3) Consequently, once the P & I gans for one confguraton have been found t s a smle matter to comute the gans for the other. In general, both transfer functons have the form of an ntegrator wth a sngle real ero. Adotng a somewhat neutral notaton, we can wrte ether confguraton n the form bs b s) (4) s hs form s the same as the ero lus ntegrator commonly used n ower suly loo comensaton, n whch b = and b s the ero frequency. We wll now examne how the gans are related to the dgtal PI controller.. Dscrete ransformaton here are several methods for convertng a contnuous tme transfer functon nto equvalent dscrete tme form. Among them, the best known s robably the b-lnear, or ustn transform. hs method, named after the Englsh mathematcan whose work on non-lnear systems led to ts ntroducton, can be derved from a numercal aroxmaton of the controller outut (see chater 4 n ref. []). he method nvolves relacement of each nstance of s n the orgnal transfer functon wth the followng term nvolvng and the samlng erod. Alyng the substtuton to equaton (4), we have s b b b b F ( After some re-arrangement, we can wrte the transformed equaton n the form where the numerator coeffcents are c c F ( (6)

c b b ; c b b ustn s method requres that the gans of the orgnal and transformed systems be matched. hs s usually done at =, however the PI controller has nfnte gan there snce t contans an ntegrator. We could match the gans at a dfferent frequency, however n ths case t s robably easer to neglect the ntegrators and match the numerator gans n (4) and (6). b s s b b c c c c herefore the gan of the transformed equaton (6) must be modfed by b A c c whch n ths case turns out to be /. c c F ( A (7) We now have a dscrete tme transfer functon reresentng our PI controller. he corresondng dfference equaton s found by re-arrangement and alcaton of the shftng theorem of the transform []. c ) ( ) u( A c u u( Ac Ac ) ( u u( k ) Ac Ac k ) (8) ( 3. Parallel Controller Gans A reasonable queston s to ask s: what roortonal and ntegral gans do we need to aly n order for the dscrete tme verson to behave smlarly to the contnuous tme orgnal? In the followng, we wll address ths queston to the arallel controller. he seres confguraton s dealt wth n secton 4. In order to roceed, we ll need the dfference equaton of the arallel dscrete tme PI controller. We can then fnd a relatonsh between the gans by matchng coeffcents. he arallel form dscrete tme PI controller structure s shown below. o avod confuson between the orgnal P & I controller gans and those n the dscrete tme structure, we wll refer to the latter as V and V resectvely. 3

Fgure 3 he dfference equaton can be found as follows. Notce that the dscrete ntegrator ntroduces an nternal varable nto the equaton. u( V V ( k ) ( u( V u( V V u( k ) V k ) V V V k ) u( u( k ) (9) he relatonsh between the contnuous and dscrete tme controller gans can be found by matchng coeffcents n (8) and (9). V Ac () V V V Ac A c c () Fnally, substtutng n () and () for c & c, and then for b & b, we fnd the requred dscrete tme controller gans. V A K K () V AK (3) 4. Seres Controller Gans If we are workng wth the seres PI controller, we can correlate dfference equatons coeffcents n a smlar way. o avod ambguty, we wll denote dscrete tme P & I gans W and W resectvely. Fgure 4 Proceedng as before, we have u( W ( ( W W ( k ) ( k ) u( k ) W k ) 4

u( W W W u( k ) W k ) u( u( k ) W W W k ) (4) Comarng equatons (4) and (8), we see W Ac (5) c W (6) c We can now substtute for c & c, b & b, and A, to exress the dscrete tme seres PI gans n terms of the contnuous tme PI gans. W K K (7) Equatons (7) and (8) are related by K W K (8) W K W (9) K Summary Equatons () & (3), and (7) & (8) allow us to comute equvalent dgtal PI controller gans from an analogue rototye. hs has value when a desgner wshes to substtute dgtal control acton for an analogue PI controller. However, the desgner must understand that dgtal control ntroduces a samler (A/D converter) and a reconstructon block (tycally PWM). Both nvolve scalng the nut and outut varables to match the dgtal numerc format. Furthermore, dgtal control ntroduces dynamc effects nto the loo, rncally n the form of hase lags, whch are not resent n the analogue system. In almost all ower electronc control systems, hase lag s detrmental to control and must be accounted for carefully. Further nformaton on these matters can be found n the followng references. References [] Control heory Fundamentals, R. Poley, CreateSace, 3 rd Ed., 5 [] Dgtal Control of Dynamc Systems, Frankln, Powell, & Workman, 3 rd. Ed., 997 5