Exercise 1 Suppose we have a simple mass, spring, and damper problem. Find The modeling equation of this system (F input, x output). The transfer function.

Slides:



Advertisements
Similar presentations
Discrete Controller Design
Advertisements

Design with Root Locus Lecture 9.
Chapter 4: Basic Properties of Feedback
PID CONTROLLER. Click to edit the outline text format  Second Outline Level Third Outline Level  Fourth Outline Level Fifth Outline Level Sixth Outline.
Lect.7 Steady State Error Basil Hamed
CHE 185 – PROCESS CONTROL AND DYNAMICS
PD Controller 1.Find the steady-state output due to unit-step r d. 2.Find the steady-state output due to unit-step input (with r d =0)
Chapter 10 – The Design of Feedback Control Systems
Chapter 10 – The Design of Feedback Control Systems PID Compensation Networks.
Feedback Control Systems
Prof. Wahied Gharieb Ali Abdelaal Faculty of Engineering Computer and Systems Engineering Department Master and Diploma Students CSE 502: Control Systems.
Examples of Control Systems Application. Modeling the Ball and Beam Experiment.
Review last lectures.
Design of Control Systems Cascade Root Locus Design This is the first lecture devoted to the control system design. In the previous lectures we laid the.
PID Control and Root Locus Method
ME 270 Final Project Presentation Operational Amplifiers.
CIS 540 Principles of Embedded Computation Spring Instructor: Rajeev Alur
f(t) m x(t) fd(t) LINEAR CONTROL C (Ns/m) k (N/m)
ECE 4115 Control Systems Lab 1 Spring 2005
It is the time response of a system to an input that sets the criteria for our control systems. Many quantitative criteria have been defined to characterise.
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.
Modified by Albert W.J. Hsue,
ME375 Handouts - Spring 2002 Root Locus Method.
INC341 Design Using Graphical Tool (continue)
o Problem Reconsider Problem
University of Virginia PID Controllers Jack Stankovic University of Virginia Spring 2015.
Modern Control System EKT 308
MESB374 System Modeling and Analysis PID Controller Design
1 MATLAB AND CONTROLS PRESENTED BY:- AGILESWARI K. RAMASAMY DR. FARRUKH HAFIZ NAGI.
Lecture 17: Introduction to Control (part III)
Overall controller design
ENTC 395 Lecture 7a. Today 4 PID control –Overview –Definitions –Open loop response 4 Example –SIMULINK implementation.
Design via Root Locus 1. 1 Introduction The root locus graphically displayed both transient response and stability information. The locus can be sketched.
Modern Control System EKT 308 Root Locus and PID controllers.
Lecture 22: Frequency Response Analysis (Pt II) 1.Conclusion of Bode plot construction 2.Relative stability 3.System identification example ME 431, Lecture.
Modern Control System EKT 308 Steady-State and Stability.
Lecture 16: Introduction to Control (Part II)
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.
Review. Feedback Terminology In Block diagrams, we use not the time domain variables, but their Laplace Transforms. Always denote Transforms by (s)!
Discrete Controller Design
System Time Response Characteristics
1 Time Response. CHAPTER Poles and Zeros and System Response. Figure 3.1: (a) System showing input and output; (b) Pole-zero plot of the system;
Exercise 1 (Root Locus) Sketch the root locus for the system shown in Figure K 1 (
Modern Control System EKT 308
Lecture 9: PID Controller.
Introduction to Linear System Theory and simple feedback PID Controllers EE125 Ruzena Bajcsy.
Intelligent Robot Lab Pusan National University Intelligent Robot Lab Chapter 7. Forced Response Errors Pusan National University Intelligent Robot Laboratory.
SKEE 3143 Control Systems Design Chapter 2 – PID Controllers Design
BIRLA VISHWAKARMA MAHAVIDHYALAYA ELECTRONICS & TELECOMUNICATION DEPARTMENT o – ANKUR BUSA o – KHUSHBOO DESAI UNDER THE GUIDENCE.
Lecture 11/12 Analysis and design in the time domain using root locus North China Electric Power University Sun Hairong.
ABE425 Engineering Measurement Systems ABE425 Engineering Measurement Systems PID Control Dr. Tony E. Grift Dept. of Agricultural & Biological Engineering.
CIS 540 Principles of Embedded Computation Spring Instructor: Rajeev Alur
Page : PID Controller Chapter 3 Design of Discrete- Time control systems PID C ontroller.
ET 438a Automatic Control Systems Technology Lesson 17: Combined Mode Control 1 lesson17et438a.pptx.
Chapter 12 Design via State Space <<<4.1>>>
Lesson 13: Effects of Negative Feedback on System disturbances
Salman Bin Abdulaziz University
Chapter 7 The Root Locus Method The root-locus method is a powerful tool for designing and analyzing feedback control systems The Root Locus Concept The.
PID Controllers Jordan smallwood.
Lecture 20: Root Locus for Design
PID Controller.
Basic Design of PID Controller
Digital Control Systems (DCS)
UNIT-II TIME RESPONSE ANALYSIS
HW-03 Problem Kuo-95 (p. 377) Find the steady-state errors for step, ramp and parabolic inputs. Determine the type of the system. ) s ( R Problem.
4. Closed-Loop Responses Using the Laplace Transform Method
E(s): Laplace transform of the error e(t)
The Design of Feedback Control Systems
Exercise 1 For the unit step response shown in the following figure, find the transfer function of the system. Also find rise time and settling time. Solution.
Presentation transcript:

Exercise 1 Suppose we have a simple mass, spring, and damper problem. Find The modeling equation of this system (F input, x output). The transfer function. Let M = 1 kg b = 10 N s/m k = 20 N/m F = 1 N 3. Find Open-Loop Step Response. 4. Design a proportional controller to improve the output ( 𝜔 𝑛 =17.89). 5. Design a proportional derivative controller to improve the output (𝜁=0.56 and 𝜔 𝑛 =17.89).

1. The modeling equation of this system Solution 1 1. The modeling equation of this system 𝑓=𝑀 𝑑 2 𝑥 𝑑 𝑡 2 𝑀 𝑥 =−𝑏 𝑥 −𝑘 𝑥+𝐹 ⟹ 𝑀 𝑥 +𝑏 𝑥 +𝑘 𝑥=𝐹 2. The transfer function. Taking the Laplace transform of the modeling equation, we get 𝑀 𝑠 2 𝑋 𝑠 +𝑏 𝑠𝑋(𝑠)+𝑘 𝑋(𝑠)=𝐹(𝑠) ⟹ 𝐺 𝑠 = 𝑋 𝑠 𝐹 𝑠 = 1 𝑀 𝑠 2 +𝑏 𝑠+𝑘 Let M = 1 kg b = 10 N s/m k = 20 N/m F = 1 N 𝐺 𝑠 = 𝑋 𝑠 𝐹 𝑠 = 1 𝑠 2 +10 𝑠+20 Plug these values into the above transfer function 3. Find Open-Loop Step Response. Create a new m-file (Matlab) and run the following code: the DC gain of the plant transfer function is 1/20, so 0.05 is the final value of the output to an unit step input. this corresponds to the steady-state error of 0.95, quite large indeed. the rise time is about one second, the settling time is about 1.5 seconds

4. Proportional Control The proportional controller (Kp) reduces the rise time, increases the overshoot, and reduces the steady-state error. 𝐺 𝑠 = 𝑋 𝑠 𝐹 𝑠 = 𝐾 𝑃 𝑠 2 +10 𝑠+(20+ 𝐾 𝑃 ) 1 𝑠 2 +10 𝑠+20 𝐾 𝑃 + - 𝐹 𝑠 𝑋 𝑠 𝜔 𝑛 2 =20+ 𝐾 𝑃 ⟹ 𝐾 𝑃 = 𝜔 𝑛 2 −20=300 Let the proportional gain equal 300 and change the m-file to the following The above plot shows that the proportional controller reduced both the rise time and the steady-state error, increased the overshoot, and decreased the settling time by small amount.

Proportional-Derivative Control Now, let's take a look at a PD control. From the table shown above, we see that the derivative controller (Kd) reduces both the overshoot and the settling time. The closed-loop transfer function of the given system with a PD controller is: 20+ 𝐾 𝑃 = 𝜔 𝑛 2 ⟹ 𝐾 𝑃 = 𝜔 𝑛 2 −20=300 10+ 𝐾 𝐷 =2𝜁 𝜔 𝑛 ⟹ 𝐾 𝐷 =2𝜁 𝜔 𝑛 −20=2 0.56 17.89 −10⟹ 𝐾 𝐷 =10 This plot shows that the derivative controller reduced both the overshoot and the settling time, and had a small effect on the rise time and the steady-state error.

Exercise 2 Use a PD controller to control the system G s = 1 𝑠 2 +𝑠 to meet the specifications 𝜁=0.2 𝑎𝑛𝑑 𝜔 𝑛 =4 𝑟𝑎𝑑/𝑠𝑒𝑐.

The open Loop Analysis: the system poles p = 0 and p= - 1. Solution the system TF: G s = 1 𝑠 2 +𝑠 The open Loop Analysis: the system poles p = 0 and p= - 1. - 1 System poles Im Re 3.9 Desired 𝜁=0.2 𝜔 𝑛 =4 Desired Poles Specifications: 𝑠 2 +2𝜁 𝜔 𝑛 𝑠+ 𝜔 𝑛 2 =0 𝑃 1,2 −0.8±𝑗3.9 0.8 The system does not meet the desired specification, we need a controller. 1 𝑠 2 +𝑠 𝐾 𝑃 + 𝐾 𝐷 𝑠 + - 𝑦 𝑑 𝑠 𝑦 𝑠 Controller 𝐶𝐿𝐶𝐸 : 𝑠 2 +𝑠 +1 𝐾 𝑃 + 𝐾 𝐷 𝑠 =0 For the design, we need to find 𝐾 𝑃 and 𝐾 𝐷 to meet the specifications . 𝐷𝑒𝑠𝑖𝑟𝑒𝑑 𝐶𝐿𝐶𝐸 : 𝑠 2 +2𝜁 𝜔 𝑛 𝑠+ 𝜔 𝑛 2 = 𝑠 2 +2 0.2 4 𝑠+ 4 2 = 𝑠 2 +1.6 𝑠+16=0 𝐶𝐿𝐶𝐸 : 𝑠 2 + 1+ 𝐾 𝐷 𝑠+ 𝐾 𝑃 =0 1+ 𝐾 𝐷 =1.6 𝐾 𝐷 =0.6 By matching coefficients: 𝐾 𝑃 =16 𝐾 𝑃 =16

Exercise 3 Use a PI controller to control the system G s = 1 𝑠+3 to meet the specifications 𝜁=0.7 𝑎𝑛𝑑 𝑡 𝑠 <1 𝑠𝑒𝑐.

The open Loop Analysis: the system pole: p= - 3. Solution The system is type zero, it has no integrator. In order to have no steady-state error we need to add an integrator to make the system type one. The open Loop Analysis: the system pole: p= - 3. - 3 System poles Im Re - 4 𝜎>4 𝜁=0.7 satisfy the settling time 𝜁=0.7. 𝜔 𝑛 > 4 𝜁 = 4 0.7 𝑡 𝑠 = 4 𝜎 <1 𝜔 𝑛 >5.71 𝜔 𝑛 =6 𝜎=𝜁 𝜔 𝑛 >4 1 𝑠+3 𝐾 𝑃 + 𝐾 𝐼 𝑠 + - 𝑦 𝑑 𝑠 𝑦 𝑠 The controller design: PI controller 𝐾 𝑃 + 𝐾 𝐼 𝑠 = 𝐾 𝑃 (𝑠+ 𝐾 𝐼 𝐾 𝑃 ) 𝑠 Gain Zero = 𝐾 𝐼𝑃 Integrator The PI controller can be written as: 𝐶𝐿𝐶𝐸 :𝑠 𝑠+3 + 𝐾 𝑃 𝑠+ 𝐾 𝐼 𝐾 𝑃 =0 𝑠 2 +(2+ 𝐾 𝑃 ) 𝑠+ 𝐾 𝐼 =0 𝐷𝑒𝑠𝑖𝑟𝑒𝑑 𝐶𝐿𝐶𝐸 : 𝑠 2 +2𝜁 𝜔 𝑛 𝑠+ 𝜔 𝑛 2 = 𝑠 2 +2 0.7 6 𝑠+ 6 2 = 𝑠 2 +8.4 𝑠+36=0 2+ 𝐾 𝑃 =8.4 𝐾 𝑃 =7.4 𝐾 𝐼 =36 𝐾 𝐼 =36