Chapter 5 Digital PID control algorithm. Hesheng Wang Department of Automation,SJTU 2016,03

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

LAPLACE TRANSFORM AND TRANSFER FUNCTION

EECE 301 Signals & Systems Prof. Mark Fowler

Embedded Systems and Software. A Simple Introduction to Embedded Control Systems (PID Control)

Determination of the Sampling Period Required for a Fast Dynamic Response of DC-Motors

Robust Learning Control with Application to HVAC Systems

Unified Control Strategy Covering CCM and DCM for a Synchronous Buck Converter

Chapter 8 The Complete Response of RL and RC Circuits

Sliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game

Inductor Energy Storage

Linear Time-invariant systems, Convolution, and Cross-correlation

Homework-8(1) P8.3-1, 3, 8, 10, 17, 21, 24, 28,29 P8.4-1, 2, 5

dv 7. Voltage-current relationship can be obtained by integrating both sides of i = C :

Dynamic Effects of Feedback Control!

EECE 301 Signals & Systems Prof. Mark Fowler

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

The field of mathematics has made tremendous impact on the study of

i L = VT L (16.34) 918a i D v OUT i L v C V - S 1 FIGURE A switched power supply circuit with diode and a switch.

Dual Current-Mode Control for Single-Switch Two-Output Switching Power Converters

CHAPTER 6: FIRST-ORDER CIRCUITS

Design of a control system

Ordinary Differential Equations

Sliding Mode Controller for Unstable Systems

2.4 Cuk converter example

Lecture 1 Overview. course mechanics. outline & topics. what is a linear dynamical system? why study linear systems? some examples

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder#

Announcements: Warm-up Exercise:

Dynamic Parameter -PI Control Method of STATCOM for Voltage Stability: Self-Adjustable Approach

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3.

CHBE320 LECTURE IV MATHEMATICAL MODELING OF CHEMICAL PROCESS. Professor Dae Ryook Yang

4.6 One Dimensional Kinematics and Integration

di Bernardo, M. (1995). A purely adaptive controller to synchronize and control chaotic systems.

where the coordinate X (t) describes the system motion. X has its origin at the system static equilibrium position (SEP).

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

6.2 Transforms of Derivatives and Integrals.

Vehicle Arrival Models : Headway

04. Kinetics of a second order reaction

Lecture 13 RC/RL Circuits, Time Dependent Op Amp Circuits

INVERSE RESPONSE COMPENSATION BY ESTIMATING PARAMETERS OF A PROCESS COMPRISING OF TWO FIRST ORDER SYSTEMS

Some Basic Information about M-S-D Systems

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

EECS 2602 Winter Laboratory 3 Fourier series, Fourier transform and Bode Plots in MATLAB

The problem with linear regulators

Sterilization D Values

Math 333 Problem Set #2 Solution 14 February 2003

2.9 Modeling: Electric Circuits

ECE 2100 Circuit Analysis

DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2008

CSE 3802 / ECE Numerical Methods in Scientific Computation. Jinbo Bi. Department of Computer Science & Engineering

Robust and Learning Control for Complex Systems

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

Basic Circuit Elements Professor J R Lucas November 2001

Pattern Classification and NNet applications with memristive crossbar circuits. Fabien ALIBART D. Strukov s group, ECE-UCSB Now at IEMN-CNRS, France

Spring Ammar Abu-Hudrouss Islamic University Gaza

L1, L2, N1 N2. + Vout. C out. Figure 2.1.1: Flyback converter

( ) = Q 0. ( ) R = R dq. ( t) = I t

Anti-Disturbance Control for Multiple Disturbances

First Order RC and RL Transient Circuits

EECE251. Circuit Analysis I. Set 4: Capacitors, Inductors, and First-Order Linear Circuits

Accurate RMS Calculations for Periodic Signals by. Trapezoidal Rule with the Least Data Amount

Chapter 7 Response of First-order RL and RC Circuits

Ordinary differential equations. Phys 750 Lecture 7

Linear Response Theory: The connection between QFT and experiments

Electrical Circuits. 1. Circuit Laws. Tools Used in Lab 13 Series Circuits Damped Vibrations: Energy Van der Pol Circuit

Notes on Kalman Filtering

RC, RL and RLC circuits

Chapter 1 Fundamental Concepts

Wall. x(t) f(t) x(t = 0) = x 0, t=0. which describes the motion of the mass in absence of any external forcing.

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

ln 2 1 ln y x c y C x

Speed Control of BLDC Motor by Using Tuned Linear Quadratic Regulator

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems.

Haar Wavelet Operational Matrix Method for Solving Fractional Partial Differential Equations

A Dynamic Model of Economic Fluctuations

RL Lecture 7: Eligibility Traces. R. S. Sutton and A. G. Barto: Reinforcement Learning: An Introduction 1

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

Online Appendix to Solution Methods for Models with Rare Disasters

Problemas das Aulas Práticas

Differential Equations

EE 435. Lecture 31. Absolute and Relative Accuracy DAC Design. The String DAC

non-linear oscillators

CHAPTER 2: Mathematics for Microeconomics

EECS 141: FALL 00 MIDTERM 2

Math 10B: Mock Mid II. April 13, 2016

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n

Optimal Control of Dc Motor Using Performance Index of Energy

Lectures 29 and 30 BIQUADRATICS AND STATE SPACE OP AMP REALIZATIONS. I. Introduction

ENGI 9420 Engineering Analysis Assignment 2 Solutions

(b) (a) (d) (c) (e) Figure 10-N1. (f) Solution:

Silicon Controlled Rectifiers UNIT-1

Analytic Model and Bilateral Approximation for Clocked Comparator

CHE302 LECTURE IV MATHEMATICAL MODELING OF CHEMICAL PROCESS. Professor Dae Ryook Yang

On-line Adaptive Optimal Timing Control of Switched Systems

Non Linear Op Amp Circuits.

EE 301 Lab 2 Convolution

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

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model

555 Timer. Digital Electronics

Homework 6 AERE331 Spring 2019 Due 4/24(W) Name Sec. 1 / 2

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

Transcription:

Chaper 5 Digial PID conrol algorihm Hesheng Wang Deparmen of Auomaion,SJTU 216,3

Ouline Absrac Quasi-coninuous PID conrol algorihm Improvemen of sandard PID algorihm Choosing parameer of PID regulaor Brief summary

Ouline The PID( Proporional - Inegral - Differenial ) regulaor conrol depending on he proporional, inegral and differenial of he deviaion PID regulaion is he mos maure and he mos widely used echnology of coninuous sysem. The subsance of is regulaion is based on he deviaion of he inpu value, a funcion of he proporional, inegral and differenial operaor, The resul of he calculaion for he oupu o conrol. In pracical applicaions, depending on he circumsances, he srucure of he PID conrol can be flexibly changed.

Ouline (2) The advanage of PID maure echnology Easily familiar wih and maser Do no need o creae a mahemaical model Good conrol performance

Ouline (3) To realize PID conrol Analog: elecronic circui regulaor, he measured signal compared wih a given value, hen he difference afer PID circui operaion is sen o he acuaor, change he amoun of inpu o achieve he purpose of regulaion. Digial: using a compuer, he resul of he calculaion is convered o he analog oupu o conrol he acuaors. The regulaor design issues. ---------. Terminal conroller design problem ---. Disurbance Conrolu x Conrolu x x f

algorihm Analog PID regulaor Plan

algorihm(2) Proporional regulaor u K P e u u K e u P e() oupu uy Scale facor inpu deviaion basis of conrol inpu Proporional acion: rapid response error, bu does no eliminae he seady sae error, easily lead o insabiliy if i is oo large KP e()

algorihm(3) e() Proporional inegral regulaor 1 u KP e edu T I T I Inegral ime consan Inegral acion: eliminae saic error, bu may cause overshoo easily, or even oscillaion uy e() uy y2 y1=kp e() K1 KP e()

algorihm(4) proporional and differenial regulaor de u KPeTD u d T D Derivaive ime consan Derivaive acion: reduce he overshoo, o overcome he oscillaion Improve sabiliy, o improve he sysem dynamic characerisics u u

algorihm(5) Proporional inegral differenial regulaor 1 de u KPe ed T D u TI d u e() y KP KD e() KP K1 e() KP e()

algorihm(6) Digial PID conrol algorihm -PID conrol law wih he numerical approximaion -Numerical approximaion: he summaion insead of inegraion, wih he Backward difference insead of differenial analog PID discreized ino he differenial equaion - Two forms: Posiional, incremenal

algorihm(7) The posiional PID conrol algorihm o e ()dt e k j d() e ek ek 1 d T k T TD uk KP[ ek ej ( ek ek )] u T T I j j 1 Posiional conrol algorihm provides acuaor posiion u k, cumulaive e k

algorihm(8) Incremenal PID conrol algorihm T T u K e e e e u k D k P[ k j ( k k1)] TI j T T T u K e e e e u k 1 k1 D P[ k1 j ( k1 k2)] TI j T T T u u u K [ e e e ( e 2 e e )] D k k k 1 P k k 1 k k k 1 k 2 TI T The incremen uk is feedback o he acuaor jus need o keep 3 previous deviaion values

algorihm(9) Posiional and incremenal PID conrol algorihm comparison Posiional PID algorihm plan PID incremenal algorihm Sepper moor plan

algorihm(1) Incremenal algorihm do no need o accumulae - have low inference from he calculaion error and accuracy; posiional algorihms use he accumulaed value of deviaion -> have a bigger cumulaive error. conrol is swiched from manual o auomaic he posiional algorihm mus firs se he compuer oupu value as he iniial value u( impac of he swich); incremenal algorihm is independen of he original value (no impac)..

algorihm(11) PID posiion program The posiional PID conrol algorihm programming - Ideas: k u K e K e K ( e e 1) k P k I j D k k j wk ( ) yk ( ) P ( k) K e P P k k P( k) Ke K e P( k 1) I I j I k I j PD( k) KD( ek ek 1) K K T / T, K K T / T I p I D p D P (k) is convered ino a double-bye ineger reurn

algorihm(12) Enrance Take w y1 Incremenal PID conrol algorihm programming u d e d e d e k k 1 k1 2 k2 Iniializaion placed adjus he parameers d, d1, d2, and he se value w, and iniial value seing error e i =e i 1 = e i 2 = Form Deviaion e=w-y1 Take d d1 d2 Calculae Reurn