Controllers Daniel Mosse cs1657 cs1567.

Slides:



Advertisements
Similar presentations
Unit 4 The Performance of Second Order System Open Loop & Close Loop Open Loop: Close Loop:
Advertisements

PID Control for Embedded Systems
ERT 210 Process Control & dynamics
PID Controllers and PID tuning
Modern Control Systems (MCS)
1 ChE / MET Apr 12. Feedback Controller Tuning: (General Approaches) 1)Simple criteria; i.e QAD via ZN I, t r, etc easy, simple, do on existing.
Basics of Feedback Control
Chapter 4: Basic Properties of Feedback
دکتر حسين بلندي- دکتر سید مجید اسما عیل زاده
Add and Use a Sensor & Autonomous For FIRST Robotics
The Proportional-Integral-Derivative Controller
CHE 185 – PROCESS CONTROL AND DYNAMICS
CHE 185 – PROCESS CONTROL AND DYNAMICS
Embedded Systems Design: A Unified Hardware/Software Introduction 1 Chapter 9: Control Systems.
Roberto - Balancing Robot RIT Computer Engineering Senior Design Project.
Intelligent Steering Using PID controllers
PID Control & ACS550 and ACH550
LECTURE#11 PID CONTROL AUTOMATION & ROBOTICS
Chapter 7 PID Control.
Proportional/Integral/Derivative Control
Lecture 5: PID Control.
2008 Indication Product Workshop Temperature / PID Controls.
CHAPTER 11 Op-Amp Applications. Objectives Describe and Analyze: Audio mixers Integrators Differentiators Peak detectors Comparators Other applications.
Ch. 9 Application to Control. 9.1 Introduction to Control Consider a causal linear time-invariant system with input x(t) and output y(t). Y(s) = Gp(s)X(s)
Proportional control Consider forward path gain A Feedback and Control If the size of the loop gain is large, that is if |A  >> 1, then or.
CS 478: Microcontroller Systems University of Wisconsin-Eau Claire Dan Ernst Feedback Control.
Fuzzy Logic Control of Blood Pressure During Anesthesia
Automation & Control Any process consist of :- (1) Application (2) Control System The Process Application (Operative Part) Control System (Action Coordinator)
Embedded Systems Design: A Unified Hardware/Software Introduction 1 Chapter 9: Control Systems.
Low Level Control. Control System Components The main components of a control system are The plant, or the process that is being controlled The controller,
Feedback Control system
Control Theory in Industry, Robotics and Infrastructure
Process Control 2.1 – Control Systems.
Control Theory Control System Objectives  Establish a final condition  Provide safe operation  Eliminate the human element  Assure economical operation.
Design Realization lecture 22
University of Virginia PID Controllers Jack Stankovic University of Virginia Spring 2015.
PID. The proportional term produces an output value that is proportional to the current error value. Kp, called the proportional gain constant.
Control Theory D action – Tuning. When there’s too much oscillation, this can sometimes be solved by adding a derivative action. This action will take.
PID CONTROLLERS By Harshal Inamdar.
IVR 30/10/2009 Herrmann1 IVR: Control Theory Overview: PID control Steady-state error and the integral method Overshoot and ringing in system with time.
CSCI1600: Embedded and Real Time Software Lecture 12: Modeling V: Control Systems and Feedback Steven Reiss, Fall 2015.
Control Theory D action – Tuning. When there’s too much oscillation, this can sometimes be solved by adding a derivative action. This action will take.
PID Control of Car Position Exercises in Manual Tuning.
Lecture 25: Implementation Complicating factors Control design without a model Implementation of control algorithms ME 431, Lecture 25.
Lec 11. Common Controllers Some commonly used controllers –Proportional Controller –Integration Controller –Derivative Controller Reading: 5-8. TexPoint.
Lecture 17: Introduction to Control (part III)
Swerve Drive Software Design. Software Layers Joystick Axis Correction Joystick Response Calculation Field-oriented Angle Adjustment Swerve Drive Steer.
Basics of control Lin Zhong ELEC424, Fall
Control 3 Keypoints: PID control
Chapter 4 A First Analysis of Feedback Feedback Control A Feedback Control seeks to bring the measured quantity to its desired value or set-point (also.
System A collection of parts that perform a function.
Embedded Control Systems Dr. Bonnie Heck School of ECE Georgia Tech.
1 Teaching Innovation - Entrepreneurial - Global The Centre for Technology enabled Teaching & Learning, M G I, India DTEL DTEL (Department for Technology.
Lecture 9: PID Controller.
Modern Control Systems Lab#04 PID Position and speed control of D.C Motor Dr. Imtiaz Hussain
BIRLA VISHWAKARMA MAHAVIDHYALAYA ELECTRONICS & TELECOMUNICATION DEPARTMENT o – ANKUR BUSA o – KHUSHBOO DESAI UNDER THE GUIDENCE.
1 PID Feedback Controllers PID 反馈控制器 Dai Lian-kui Shen Guo-jiang Institute of Industrial Control, Zhejiang University.
CIS 540 Principles of Embedded Computation Spring Instructor: Rajeev Alur
Process Control. Feedback control y sp = set point (target value) y = measured value The process information (y) is fed back to the controller The objective.
EEN-E1040 Measurement and Control of Energy Systems Control I: Control, processes, PID controllers and PID tuning Nov 3rd 2016 If not marked otherwise,
PID Control for Embedded Systems
Feedback Control System
Introduction to PID control
Design via Root Locus (Textbook Ch.9).
Control Loops Nick Schatz FRC 3184.
CSCI1600: Embedded and Real Time Software
PID Controller.
Electronic Control Systems Week 7 – PID Control
Advanced LabVIEW
The Design of Feedback Control Systems
Presentation transcript:

Controllers Daniel Mosse cs1657 cs1567

Introduction Suppose you have a system that needs to be controlled Your software gives commands, the system responds to it Turn x degrees to the right Move forward 15 wheel rotations Can you always trust your commands will be executed accurately? cs1567

Problem example Increase the quantity until you get to the setpoint Ripple overshoot setpoint Increase the quantity until you get to the setpoint Temperature, angle, speed, etc If too much, reduce the quantity, until the setpoint cs1567

Closed loop controller setpoint error signal output controller system measured quantity closed loop because it has feedback output is measured at a certain frequency signal is generated at a certain frequency which frequency is not smaller? cs1567

On-off control For some systems, on-off signaling is sufficient For example, a thermostat, when the heater is either on or off, and early cruise-control systems Could do airflow or speed control also More modern systems do it Depending on the frequency of control, overhead of on-off, etc, this could cause overshoots and undershoots (ripples) Oscillation is a common behavior in control systems Need to avoid it at all costs… well, almost all costs cs1567

Proportional control Good alternative to on-off control: more “control”  Signal becomes proportional to the error P ( setpoint – output ) Example, car speed for cruise control Need to find out value of constant P Tuning the controller is a hard job If P is too high, what happens? If P is too low, what happens? Typically a prop cntrl decreases response time (quickly gets to the setpoint) but increases overshoot cs1567

Adding derivative control To avoid (or reduce) overshoot/ripple, take into account how fast are you approaching the setpoint If very fast, overshoot may be forthcoming: reduce the signal recommended by the proportional controller If very slow, may never get to setpoint: increase the signal In general: D ( current measure – previous measure) PD controllers are slower than P, but less oscillation, smaller overshoot/ripple cs1567

Integral control There may still be error in the PD controller For example, the output is close to setpoint P is very small and so is the error, discretization of signal will provide no change in the P controller D controller will not change signal, unless there is change in output Take the sum of the errors over time, even if they’re small, they’ll eventually add up I * sum_over_time (setpoint — output) Again the main problem is the value of I Can we let sum grow to infinity? cs1567

Summary Different types of controllers PID hardest task is tuning Response time Overshoot Error On-off Smallest Highest Large Proportional Small Integral Decreases Increases Zero Derivative Small change cs1567

Where to Get More Information newton.ex.ac.uk/teaching/CDHW/Feedback/ ~don/cs1567/reference/pidworksheet.xls cs1567