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ENT364/4 – Control System Sazali Yaacob BEng(Malaya), MSc(Surrey), PhD(Sheffield) Chartered Engineer, CEng (United Kingdom) Member Institute of Engineers.

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Presentation on theme: "ENT364/4 – Control System Sazali Yaacob BEng(Malaya), MSc(Surrey), PhD(Sheffield) Chartered Engineer, CEng (United Kingdom) Member Institute of Engineers."— Presentation transcript:

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2 ENT364/4 – Control System Sazali Yaacob BEng(Malaya), MSc(Surrey), PhD(Sheffield) Chartered Engineer, CEng (United Kingdom) Member Institute of Engineers and Technologist, MIET (United Kingdom) s.yaacob@unimap.edu.my 019-4772260

3 Course Assessment Lecture 3 hours per week Lab/Tutorial/Design2 hours per week Final Examination 50 marks Mid-SemesterTest10 marks Quiz/Design25 marks Lab works15 marks

4 Weekly Schedule Week 1: Introduction Week 2: Modeling Week 3: Modeling Week 4: Time Response Week 5: Time Response Week 6: Time Response/Root Locus Week 7: Root Locus/Mid-Semester Revision

5 Weekly Schedule Week 8: Frequency Response Week 9: Frequency Response Week 10: Frequency Response Week 11: Frequency Response Week 12: Design Week 13: Design Week 14: Revision

6 OBJECTIVES Basic terminologies. Open-loop and closed-loop Block diagrams Control structure Advantages and Disadvantages of closed-loop Introduction to control system

7 Human control

8 System control

9 GPS Control

10 Force Control

11 Vision Control

12 Primary Source (Loudspeaker) Secondary source (Actuator) Block Diagram for Active Noise Cancellation 24 cm Error Microphone Sensor Microphone 36 cm Primary pathError path 12 cm BEFORE ANCAFTER ANC Sound Control

13 Satellite Control

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15 Magnetometer Magnetorquer Driver OBCACS Torque command for the MT Processed attitude data Attitude Ref

16 Process Control

17 Pilot Plant

18 Servo Control

19 Steering Control Complete System Set-up for Mobile Robot using Mecannum wheel

20 Omni-directional Motion for the Mobile Robot

21 Basics terminologies Sub-system and System subsystem subsystem subsystem –System is a combination of physical and non-physical components that are configured to serve certain tasks to maintain the output –Subsystem is part of the system that is grouped for a certain function blower room thermostat

22 Plant subsystem input output Plant is the main subsystem where the control signal will act on and produce the output. plant

23 Disturbance is unwanted signal that may sway the output Controller is a subsystem that is used to ensure the output signal follows the input signal controller plant input disturbance output + Disturance and Controller

24 Error controller plant - + + + input Error is a signal made up of the difference of input and output error disturbance

25 Control Structure For any control system the following flow structure is needed model analysis design Objective

26 Example of an open-loop system motor Turn table rheostat amplifier motor Turn- table Required speedActual speed Open-loop system

27 Closed-loop system example of closed-up system motor tachometer + - Turn-table rheostat Differential amplifier amplifier motor Turn- table tachometer required speed Actual speed + -

28 Block Diagram Transfer function, H input, Routput, Y Transfer function is the ratio of the ouput over the input variables The output signal can then be sderived as Example of multi-variables ++ + - R C E B Block diagram reduction H G H.G = abcac

29 Feed Forward and Feedback Transfer function + - R(s)R(s) E(s)Y(s)Y(s) B(s)B(s) E(s error signal B(s) feedback signal R(s) reference signal Y(s) output signal Feed forward transfer function Feedback transfer function

30 Open Loop Transfer Function H(s) G(s)G(s) H(s)G(s)H(s)G(s) E(s)E(s)Y(s)Y(s) B(s)B(s) E(s)E(s)B(s)B(s) Open loop transfer function + - R(s)R(s) E(s)Y(s)Y(s) B(s)B(s)

31 Closed Loop Transfer Function The feedback is. Variable difference Characteristic equation Closed-loop transfer function The error signal is The closed loop transfer function is The characteristic equation is very important in determining the behaviour of a system

32 Model Many type of models: Physical model Graphical model Mathematical model Example: Current-voltage relationship v – voltage in V i – current in A R – resistance in Ohm Example: Force-deflection realtionship f – force in N k – spring constant x – displacement in m Mass-spring model sistem jisim-pegas

33 From Newton’s law where m is the mass and a is the acceleration. Substituting Example: Mass-spring model - applied force x - displacement - reaction force Velocity Acceleration

34 Black-box Modelling

35 Input-output reltionship Torque-Speed Characteristics of a Squirrel-Cage Induction Motor

36 Identification Procedure

37 Neural Network Training Forward Plant Modeling

38 Neural Network Structure A two layer Artificial Neural Network

39 Neural Network Control The Experimental Work

40 Input-output Data

41 Analysis Transient state A state whereby the system response after a pertubation before the response approach to a steady condition Steady state A state whereby the system response becomes steady after a transient state Stability The condition of the steady state. If the response converges to a finite value then it is said to be in a stable condition and if the response diverges, it is known to be unstable.

42 Time Response Transient s stateSteady state

43 Example of Time Response

44 Design Analogue controller A controller that used analogue subsystem Digital Controller A controller that used computer as its subsystem computerdriveplant sensor _ + referene input Actual output

45 Adaptive Control

46 Computer Control The Control Experiment.

47 Step Input The Induction Motor Unit Step Speed Response with the Direct Inverse Control Scheme

48 Sinusoidal Input Speed Response to a Sine Wave Reference Signal under DIC Scheme.

49 Ramp Input Speed Response to a Ramp Wave Reference Signal under DIC Scheme.

50 Square-wave Input Speed Response to a Square Wave Reference Signal under DIC Scheme.

51 Advantage of Feedback Loop (1) Not susceptible to disturbance H + + + - d r y Assume, then changes in y is negligible  Not sensitive to parameters changed

52 (2) Insensitive to changes in parameters Consider H y+ - r Define sensitvity as where T is the transfer function of the system  is the parameter of the system. Closed-loop transfer function Let us investigate the effect on the system when the plant is subjected to perturbance i.e.,. If, thus.

53 (3) Increased in bandwidth Consider a first order where K is the dc gain and T is the time constant If a feedback is applied a + - The closed-loop transfer function is Hence the new time constant is reduced and increased the system bandwidth

54 Output for open loop Output for feedback system. If thus. (4) Accurate control. + - R(s)R(s)Y(s)Y(s) This means that the output will follow the input which signify a god control objective


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