AC 2010-462: LABORATORY INNOVATIONS IN UNDERGRADUATE CONTROLENGINEERING EDUCATION

Ahmed Rubaai, Howard UniversityAhmed Rubaai received the M.S.E.E degree from Case Western Reserve University, Cleveland,Ohio, in 1983, and the Dr. Eng. degree from Cleveland State University, Cleveland, Ohio, in1988. In 1988, he joined Howard University, Washington, D.C., as a faculty member, where he ispresently a Professor of Electrical Engineering. He is the Founder and Lead Developer of HowardUniversity Motion Control and Drives Laboratory and is actively involved in many projects withindustry, while engaged in teaching, research and consulting in the area of artificial intelligenceand motion controls. His research interests include intelligent system monitoring, built-inintelligent controller for high performance industrial drives, hardware testing in laboratory,research and development of intelligent applications for manufacturing systems and industrialapplications.

© American Society for Engineering Education, 2010

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LABORATORY INNOVATIONS IN UNDERGRADUATE CONTROL

ENGINEERING EDUCATION

Abstract

A three-year funding and a kind equipment donation from Moog Aerospace have enabled the

author to develop Howard University Motion Control and Drives Laboratory using state-of-the-

art control systems technology. The primary elements of this laboratory are establishing a

comprehensive facility in an interdisciplinary, team-oriented environment, and developing a

laboratory curriculum based on hands-on experience. The key hardware element of such

capability is an embeddable dSPACE digital signal processor (DSP) that can be connected to

various sensors and actuators, depending upon the system objectives. The key software used in

the laboratory exercises is based on MATLAB/Simulink environment. The MATLAB/Simulink

environment is used to build the control algorithms, allowing the students to design, and test

their controllers without being distracted by software implementation issues. The controllers are

first designed in Simulink. Then, the Real-Time Workshop (RTW) is used to automatically

generate optimized C code for real-time applications. Afterward, the interface between

MATLAB/Simulink and the dSPACE DSP DS 1104 allows the control algorithms to run on the

hardware processor of the DSP. Generation of a C program with RTW is an automated process,

and students are relieved from cumbersome hand coding. The laboratory environment was used

in teaching an introductory laboratory control course. Implementation of the laboratory exercises

gave the students a sense of accomplishment. Much enjoyment was realized in the

implementation of the dSPACE DSP system and Simulink intuitive model-based programming.

Introduction

Students in engineering often express apparent frustration in justifying the relevance of their

classroom-oriented education. Moreover, this feeling materializes in the demands for hardware-

oriented control courses1. As educators, we are sympathetic with these requests but find that the

university is generally unable to apply “hands-on” design experience with eventually leads to the

production of a prototype. This problem has not gone unnoticed in the field of education today,

and there have been great leaps in the creation of more “hands-on” teaching methods that lend

themselves to industrial applications2. Throughout schools and universities within the United

States and internationally, there has been growing interest in the use of practical control concepts

in and beyond the classroom. This has been accomplished to a large extent through the use of

laboratory courses, with incorporation of technology tools that enable students to work on

different real-world control configurations. This adjustment to incorporate the more practical

format into the classroom has taken different forms throughout the academic world. In the

Technische Universiteit Eindhoven, The Netherlands, the modeling of control systems is an

important part of their Bachelor’s in mechanical engineering degree curriculum3. There is a

gradual introduction to real world systems that begins with a lower level course where the

students are introduced to mathematical concepts and A/D conversion and ends with a final year

project that incorporates the manipulation of various feedback controllers to accomplish a

specific task. In this way the students are transported from the theoretical understanding to actual

applications by the end of the degree program. At the Department of Automatic Control at the

Lund Institute of Technology in Sweden4, all disciplines in their four and a half year Master of

Science degree, excluding chemical and biotechnical engineering, must complete a basic control

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course. The second half of this course involves the assignment of control projects in conjunction

with the lectures, which is another clear indication that there is great importance placed on the

practical applications of control theory. All control courses have three mandatory four-hour labs

that make use of mobile desktop processes and standard computing equipment. The Institute is

also credited with having “pioneered the teaching of real-time programming and real-time

systems,” 4. At the University of Maryland, College Park

5, their main focus with regard to the

practical application of control systems is a multidisciplinary senior-level course (in the

Bachelor’s degree program of computer and electrical, mechanical and aerospace engineering)

that combines digital control and networks with information technology. One of the major

advantages seen at Maryland is in the use of an all-digital controls lab, which allows controller-

implementation using relatively cheap computers. Another article6 promotes the control-systems

laboratory at the University of Illinois at Urbana-Champaign. An appealing quality of this

facility is that it is shared among several departments. With regard to the types of controllers that

have been utilized in the educational arena, there are a number of practical approaches being

used for the illustration of the control systems concepts 7-11

. With the technology available to

various laboratories and schools continuously evolving, the students will soon be able to have all

the required exposure and ability required to enter the work field with more than just a mere

exposure to real-world applications of control theory. They will actually enter with a clear

practical understanding. At Howard University, the study of control has been accelerated by the

integration of motion controls laboratory, which affords the student an opportunity to interact

and utilize an “embeddable dSPACE digital signal processor (DSP)-based data acquisition and

control system. This is seen by Howard University as a solution to the need for a cost effective,

“hands on instructional laboratory” which would “adequately provide hands on experience

necessary for effective learning.” Another key aspect of this laboratory is the close integration of

the conventional simulation tools MATLAB and SimulinkTM

.

Laboratory Goals § Hands-on: The objective is to bring the ‘real world” into an otherwise theoretical

education. The lab promotes control-systems education with experimentation, requiring

identification and control of physical device(s). The laboratory experiments are designed

to complement and synchronize with the lecture course in order to best reinforce concepts

learned in class with hands-on experience. Using the laboratory facility, students should

be allowed to conduct design and simulation projects in a simulated virtual environment.

These projects allow students the opportunity to be involved in the development of

software for modern controls, embedded systems, power electronics and industrial drive

control systems.

§ Industrial need: The lab addresses the need of industry to have engineers educated in the

principles and applications of state-of-the-art sensing and control technologies, embedded

systems, and electric drive technologies. The Accreditation Board for Engineering and

Technology (ABET) criteria have recognized that a well developed laboratory is a key

for preparing a modern technologies workforce. This laboratory introduces students to

electromechanical system modeling, sensing and controls, embedded technologies, data

acquisition, and computer programming. Thus, crossing the traditional border between

electrical/computer and mechanical engineering.

§ Communication skills: To improve student competencies in communication skills and

teamwork. The lab components consciously focus on these skill areas through team-

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oriented, project-based, interdisciplinary projects and experiments. This has become a

critical issue in the preparation of the nation’s technical workforce.

§ Lifelong learning: To develop among students a better appreciation for the need for

lifelong learning. The competition project in the laboratory encourages students to look at

resources outside the classroom and learn the skills necessary to research topics on their

own.

§ Assessment: To include assessment of the learning objectives for the developed

laboratory according to department assessment process-based ABET criteria. Focus

groups are used as one of the assessment methods. The assessment result is used to

further improve the laboratory course.

§ Economy: As much as possible, space, money and student time should be economized. A

multidisciplinary facility, shared between ECE and ME classes would allow efficient use

of space and equipment, better use of available funds, and elimination of overlap among

individual departmental labs. Focusing experiments on control technologies, embedded

systems, and industrial drives rather than a plurality of devices would result in economies

of space, money and student time.

To achieve these goals we have carefully planned the new control laboratory. As part of this

process, we consulted with academia and motion control industry, including Black&Decker,

Honeywell and Moog. The advice we received was very helpful to us, and the hardware-in-the-

loop laboratory configuration we plan to implement is useful for both educational and training

purposes as it is very similar to that used by these companies when designing their own control

systems. With regard to the dynamic systems, we necessitate devices or configurations that

would demonstrate linear (or nearly linear) control, nonlinear control, control of stable and

unstable systems, control of multi-input multi-output systems, and some really challenging

problems for advanced students. With regard to the controlling mechanisms, we require ways to

implement (or emulate) continuous-time and discrete-time (digital) control systems. Specific

items required to fully explore digital control are: the capability of sampling analog data at a

user-specified rate; the choice of using either fixed-or floating-point arithmetic; and the ability to

implement discrete-time computational structures.

Laboratory Activities

The activities that the laboratory expected to support can be classified as follows:

§ Hardware: The student receives considerable information of the operation of PC-based

systems with data acquisition capability for simulation and hardware tests, DSP board

(custom design and out-of-shelf) based systems, and advanced digital control

implementation means such as field programmable gate arrays (FPGA) which allows the

student to learn the sequential interfaces between the host computer, the driving circuit,

and the system under control. The student, thus, experiences the connection and use of

different peripheral devices, such as pulse-width-modulated (PWM) inverters,

transducers, serial interfaces, sensors, etc. In this way, student learns how to be an

experimenter.

§ System design: The student learns how to design, build, or assemble a part, product,

configure control systems especially adapted to automation applications; and testing and

debugging a prototype using appropriate engineering tools. This helps the student to gain

insight and understanding of the real-world. Page 15.831.4

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§ Software: The student obtains good learning abilities in running programming peripheral

devices such as A/D and D/A converters, serial communication devices, input-output

interfaces. Rather than requiring that our students write C-language code and interrupt-

service routines, the students can use the dSPACE DSP software tools12

with

MATLAB/SIMULINK interface13

.

Underlying Educational Objectives

The laboratory experiments are intended to achieve the following educational objectives:

1. To introduce the state-of-the-art simulation tools as employed extensively by industry;

2. To reinforce and support lecture-based courses in control systems;

3. To train a new cadre of graduates who value experimentation as an essential and natural

part of solving engineering problems;

4. To expose important measurement techniques and safety concerns in laboratory

environment;

5. To develop good experimental skills.

Hence, the controls engineering education becomes more attractive and meaningful to the

students.

Student Learning Outcomes

The fundamental student learning outcomes of the control laboratory course are to demonstrate

the following:

1. An ability to design, build, or assemble a part or product that configures control systems

especially adapted to automation applications;

2. An ability to conduct experiments for measurements and analysis of feedback controls,

and to write effective laboratory reports;

3. An ability to use MATLAB/ Simulink graphical-user-interface (GUI) to build a real-time

model;

4. An ability to use dSPACE DSP ControlDesk GUI for real-time control;

5. An ability to achieve adequate learning skills in testing and debugging a prototype using

appropriate engineering tools and learn how to be an experimenter.

Hardware Selection

Laboratory experiments using real-time systems are necessary in control education. Experiments

help the students understand the theoretical concepts and provide important motivation. It is

therefore essential for the students to have a thorough understanding of hands-on

experimentation and real-time systems. Primarily, making a decision on a set of hardware to

interface between the host computer and the process (system to be controlled) was a challenge.

Finding a compatible set of hardware that would work with MATLAB/SIMULINK/Real-Time

Windows Target by MathWorks13 was also a challenge. The intention is to use a general-purpose

DSP controller board that controls the operator interface, performs data acquisition, and executes

the control algorithm. Our search led us to dSPACE DSP DS1104 controller board14 which could

meet our specifications from a hardware point of view. The DSP DS1104 is equipped with a

real-time interface (RTI) to MATLAB/Simulink by which the controller board converts the

Simulink block-set to machine code. In this regard, the student writes no code at all. The

dSPACE DSP has also its own ControlDesk graphical-user-interface (GUI), allows the drag-and-

drop reconfiguration of the user interface and offers the required level of interaction with the

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process. One of the salient features of the dSPACE DSP DS 1104 is the ease of building real-

time applications.

Laboratory Workstations The workstations described here offer many possibilities for experimentation on controls similar

to those that students will encounter in the “the real world.” The Lab has currently five

workstations. In addition, a novel workstation has been established as a prototype and spare. A

Dell PC with 3GB main memory is used as a host computer for each workstation. Each

workstation is equipped with an embeddable dSPACE DS1104 digital signal processor (DSP)-

based data acquisition and control (DAC) system. Aside from the duties of controlling the

operator interface, it performs the acquisition of the feedback signal, computes an error signal,

delivers the error signal to the control algorithm, and executes the control algorithm to determine

a control signal. The laboratory experiments run completely on the real-time hardware DSP

DS1104 board. Real-Time Interface (RTI) generates the required real-time code together with

Real-Time Workshop from The MathWorks. The DS1104 DSP equipped with its own graphical-

user-interface (ControlDesk) allows the drag-and-drop reconfiguration of the user interface and

offers the required level of interaction with the process. Compiling and downloading the object

code into the DS1104 DSP board is automated and totally transparent to the students.

The first three laboratory workstations are identical and utilize Moog, dSPACE, Motorsoft, Dell,

and Agilent components almost exclusively. Each workstation consists of Moog brushless dc

motor14

, Moog driving circuit15

, a PM DC generator as load, a torque transducer, a variable

transformer, and a power supply mounted on the top shelf. A dSPACE DS1104 DSP-based DAC

system, oscilloscopes, a function generator, and a personal computer (PC) mounted at the

bottom. The variable auto-transformer is used to supply the driving circuit with AC voltage of

230V. A power supply is also used to supply the inverter component of the driving circuit with

24V DC. Fig. 1 displays the hardware apparatus of the lab workstations. Much of the wiring has

been linked so that students can see how the components are interconnected.

Fig. 1 Snapshot of the Hardware Apparatus

Variable Auto-

Transformer

BLDC Motor

24 DC Logic Power Supply

Driving Circuit

Simulink / Matlab ControlDesk / dSPACE

Torque Transducer

PMDC Generator

Torque Readout

PMDC Load Voltage

42V DC Prog. Power Supply

Oscilloscope DSP dSPACE

Board

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The fourth workstation utilizes Schott Power Systems, dSPACE, Dell, Motorsoft, and Agilent

components almost exclusively. Fig. 2 exhibits a view of the developed workstation. In addition

to the embeddable dSPACE DS1104 digital signal processor (DSP)-based data acquisition and

control (DAC) system, the workstation is equipped with a custom made Computer-Controlled

Drive Board (Driving Circuit). The drive board has been designed to enable a variety of

experiments on ac/dc motor drives and has introduced digital control and digital signal

processing technologies by using MATLAB Simulink and dSPACE. It has two completely

independent three-phase Pulse-Width modulation (PWM) inverters for complete simultaneous

control of two dc or ac machines, a 42-V dc-bus voltage input from a rectifier dc power supply,

digital PWM input channels for real-time digital control of converters, and complete

digital/analog interface with a dSPACE board. This workstation is also equipped with a torque

calibrated PM DC generator and one of the following 4 test motors: 1) brushless dc, 2) ac

induction, and 3) PM dc motor. Each motor is fitted with encoder, and coupled via a clutch and a

torque transducer. The station is also equipped with a PC, an oscilloscope, and a function

generator. Control is implemented through MATLAB Simulink using the dSPACE DS1104

DSP.

Fig. 2 Photo of the Hardware Apparatus

The laboratory is also equipped with a bearing vibration and fault diagnostics testbed

system. It allows studies of the vibration spectra of common faults and learning of fault

signatures as well as their consequent algorithm development and implementation on a large

scale. It also provides modular, versatile, robust, and comprehensive testbed for different types

of rotor, stator faults of electrical machines. This workstation is designed so that it is both easy to

operate and versatile. The instrument is constructed with special kinds of bearings, rotors with

split collar ends, a split bracket bearing housing, and reciprocating system, all of which make it

easy to remove and replace various components for specific types of tests. This unique

workstation is equipped with a Machinery Fault Simulator Test System. It allows studies of the

vibration spectra of common faults and learning of fault signatures as well as their consequent

Driving Circuit

Torque Readout

Oscilloscope

4 Pole 3ΗΗΗΗ ∀∀∀∀

AC Ind. Motor

dSPACE CLP 1104 Connector Board

Load

4 pole 3ΗΗΗΗ Switched Rel Motor

2 Pole PM DC Gen

2 Pole PMDC Motor

Transformer

3ΗΗΗΗ BLDC Motor

AMATLAB/SIMULINK ControlDesk/dSPACE

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algorithm development and implementation on a large scale. It also provides modular, versatile,

robust, and comprehensive testbed for different types of rotor, stator faults of electrical

machines. Fig. 3 displays different hardware components of the system. It consists of three

identifiable sections: an electromechanical actuator (EMA) system, a dSPACE DS1104 DSP-

based DAC system, and a Dell PC. Each component passes unidirectional data to the next, and

the student may vary the output screen display via the PC keyboard. The EMA system includes

the following hardware apparatus: 1) position sensor, 3-phase induction machine, 3) temperature

sensor, 4) shaft coupling, 5) current sensor, 6) inverter, 7) x-axis vibration sensor, 8) y-axis

vibration sensor, 9) rotational disk and 10) front and rear bearing. The position sensor is

mounted to the machine casing and coupled to the unloaded shaft end of the rotor via a flexible

coupling, allowing it to run with the motor.

The workstation is designed so that it is both easy to operate and versatile. The

instrument is constructed with special kinds of bearings, rotors with split collar ends, a split

bracket bearing housing, and reciprocating system, all of which make it easy to remove and

replace various components for specific types of tests.

Fig. 3 Snapshot of the Laboratory Hardware Apparatus

Pre-lab Activities

Each lab exercise has a pre-lab preparation segment in which the students build their controllers

in Simulink, and prepare real-time models that are subsequently used during the experiment.

This method ensures that students are ready to carry out the experiment. The pre-lab activity is

followed by an in-lab activity where students perform the experiments in the lab. In the first two

laboratory experiments students are taught to become familiar with MATLAB/Simulink by

writing their own script files and developing their own block diagrams. The author believes that

eminent software environments, such as MATLAB/Simulink, are advantageous since students do

not desire to learn control languages that are tailored for a particular laboratory.

Motor with stator winding faults

Motor with misaligned rotor

Motor with broken rotor bars

Machinery fault simulator dSPACE board

Induction motor

Accel#4

Accel#1 Accel#3

Accel#2

Simulink / MATLAB/ ControlDesk

Oscilloscope

Current Probe

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User Manual

A user manual for the laboratory experiments and handouts of each experiment are developed for

the students. The student manual includes, for each of the laboratory experiments, the experiment

objectives, the actual experimental procedure, and a section listing a series of discussion

questions, which aid and guide the student in understanding the experimental results. The

questions are intended to direct the post experiment analysis of the results, focusing on the

objectives of the laboratory experiment. Specifically, the manual explains basic operator

interface functions such a selecting control algorithm, entering set-points, monitoring actual

position, entry of tuning parameters, and initiation and termination of control action. Also, a brief

explanation of the operation of the dSPACE DSP controller board is presented since it will be

used throughout the experimental procedure. In addition, the user manual details the actual

structure of the hardware and provides a view of the overall system from the student's

perspective. The following experiments were successfully performed using the laboratory

workstations under MATLAB/Simulink and dSPACE DS1104 environment:

1. Learning How to use MATLAB/Simulink to Build a Model;

2. Building Real-Time Models in Simulink. Learning about dSPACE DS1104 DSP;

Familiarizing students with DS1104 programming tool, ControlDesk, and how to build

layouts; and, compare simulation and real-time results;

3. Studying the bang-bang control algorithm under dynamic load and the effects of the

saturation limits;

4. Studying the proportional-integral (PI) control algorithm and the effects of non-ideal

motor characteristics on the closed loop performance of the controller;

5. Studying the dual loop (outer proportional position loop with inner proportional-integral

speed loop) control algorithm and tuning;

6. Studying the proportional-Plus-derivative (PID) control algorithm with an anti-windup

scheme;

7. Studying the state-feedback pole placement controller with full/reduced-order observer

and the effects of load disturbance on the closed loop performance;

8. Studying the state feedback control with Kalman filter.

These exercises provide insight into the hardware aspects of the controller. Controller parameters

are tuned by the students such that the closed-loop control system will be stable and will meet

given specifications associated with the following:

§ Stability robustness and robustness against environmental uncertainty;

§ Set-point following and tracking performance at transient, including rise-time,

overshoot; and, settling time;

§ Regulation performance at steady-state, including load disturbance rejection;

Running the Experiments

Students can demonstrate many control concepts using the laboratory workstations. After

choosing which experiment to run, students can design their controllers in Simulink blocks. Once

the controllers have been built, the MATLAB Real-Time Workshop (RTW) routine is used to

automatically generate optimized C code for real-time application. When using RTW with the

dSPACE DS 1104 DSP-board, target specific software is developed using dSPACE DS1104

Real-Time Interface (RTI) to Simulink. MATLAB RTW and dSPACE RTI provide an integral

environment that automates the task for building an executable file that is downloaded onto the

dSPACE processor. Subsequently, the interface between Simulink and the dSPACE DS 1104

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allows the control algorithm to be run on the hardware of the dSPACE DS1104 which is an

MPC8240 processor. Using these interfacing routines, students can implement and test their

design simply by the click of a mouse button. While the experiments are in progress, the student

can change controller parameters, reference signals, and observe results without having to

rebuild and download a new Simulink model to the dSPACE DS1104. When the student stops

the experiment, it is possible to download a file in a MATLAB format where the experimental

results have been stored. This file can be used to perform offline analysis, such as evaluation of

the maximum overshoot, steady state error, and settling time.

Hands on Laboratory Experimentation

The first controller the students studied is the bang-bang controller. It is an intuitively simple

direct control algorithm. The controller is perhaps the simplest and yet most effective solution to

many real-world control problems in the industry, and students should be familiar with its

practicality. A simple control law is used, based on the error:

IF the | ERROR | < D THEN uc(k) = 0

IF the ERROR< -D THEN uc(k) = - C

IF the ERROR > D THEN uc(k) = + C

where uc (k) is the output of the controller, D is half the width of the controller dead-band region,

the error is the difference between the set-point value and the motor position, and C is the

magnitude of the output of the controller when the error lies outside of the dead-band range. The

error is the only factor that the controller uses to determine the controller output. The control

action moves the motor in the proper direction to correct any error conditions measured. Students

stop the control action when the error is within the dead-band region. Examples of the broad

control decisions are:

§ IF the ERROR is positive (lies outside the dead-band region), THEN the controller output

is positive

§ IF the ERROR is negative (less than the dead-band), THEN the controller output is

negative

§ IF the ERROR lies within the dead-band range, THEN the controller output is zero

The Simulink model implementing the bang-bang controller is shown in Fig. 4.

Fig. 4 Simulink model implementing the bang-bang controller

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In order to protect the motor drive system from excessive control voltages, saturation is often

used to limit the controller output uc(k) as follows:

u(k) = umax when uc > umax

uc when umin ≤ uc ≤ umax

umin when uc< umin

where uc is the input to the saturation block and umax is the upper limit and umin is the lower limit

of the saturation block.

The students operated the laboratory hardware and observed closed loop responses for different

values of the algorithm's two parameters, the control magnitude C, and the deadband D. The

students easily modified the values of the parameters of the control algorithm in the Simulink

diagram and they observed the effects of the changes in real-time without rebuilding and re-

downloading the model to the dSPACE DSP. Several test cases were conducted to assess the

performance of the bang-bang controller. However, for briefness, only few cases are reported for

illustration purposes. The students set the reference signal to amplitude of 0.2 volt

(20 revolutions) and frequency of 0.15 Hz. The controller is operated within a dead-band of

± 0.01 volt (1 revolution) and output (control signal) of ± 1 V. Figure 4a and 4b show both

responses of motor position trajectory and the control signal. The students assess the effects of

the two gains on system performance.

Fig. 5a Position tracking under normal condition Fig. 5b Corresponding control signal

For the next test, the students studied the effects of the saturation limits on the controller

performance. They kept the dead-band constant (± 0.01v or 1 revolution) and operated the

controller at an output of ± 20V. Figure 6a shows the results of the change in the controller

output. Since a saturation of ± 5V was placed within the closed loop system, figure 5b, the

control signal settles at the limits of saturation, ± 5 volts in an attempt to get to ± 20V setting.

Fig. 6a Position tracking under the effects of saturation Fig. 6b Corresponding control signal

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The students were asked to design a state feedback pole placement speed tracking controller-

based observer to specifications and analyze its responses to square-wave inputs, and sinusoidal

inputs. This controller was chosen since it is a product of modern control theory and it is

desirable to expose the student to an algorithm based on this theory. The inclusion of state-

feedback also provides the student the opportunity to contrast modern and classical approaches

to a control problem. The controller is built in Simulink and implemented in the dSPACE

DS1104 DSP. The Simulink model implementing the state feedback controller is shown in

Figure 7a, while Figure 7b shows the block diagram of the observer.

Fig. 7a Simulink block diagram of control system

Fig. 7b Block diagram of observer

The DAC (Digital to Analog Conversion) and the ADC (Analog to Digital Conversion) blocks

represent the interface between dSPACE DSP and the motor drive system (plant).

After the students observed the controller baseline operation, the performance of the proposed

controller was evaluated by completing several test cases in the laboratory under different

operating conditions. Figure 8 illustrates the performance of the controller under loading

conditions for sinusoidal-wave inputs, respectively. The students observed that, in every case, the

controller brings the measured rotor speed to the desired value smoothly and with a slight

overshoot. The slight overshoot was almost diminished with the sinusoidal reference since the

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controller was not required to react to the abrupt change of direction. The discussion by the

students can address these issues with reference to the performance specifications. For the

baseline case, the rotor speed was set to 750 rpm and this was also the limit set within the

saturation block.

Fig. 8 Speed tracking under normal condition

The students tested the saturation limits setting the reference signal to a 900 rpm (9 volt) set-

point which is beyond the 750 rpm saturation limit. The baseline test was run again and the effect

of the saturation on the system was observed. Figure 9 shows that the pre-saturation control

signal was limited by the saturation limits and that the motor was controlled to the 750 rpm

saturation block setting.

Fig. 9 Speed tracking under the effects of saturation block

Assessment

At the end of the 2008 spring semester student are asked to rate the value of the component of

the laboratory exercises. The students respond with a rating of 1 (Strongly Disagree) to 5 (Strongly

Agree). Table I displays the student self survey. Over 27 undergraduates participated in the

survey and provided anonymous comments about the laboratory exercises. Review of these

comments indicated that the students liked using the framework of MATLAB/Simulink/dSPACE

DSP and believed that the process helped them to apply modern design tools to a real time

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system. Additionally, the students commented that more formal instruction of

MATLAB/Simulink in courses prior to the laboratory control course would be helpful. The lab

course was a success because of the value it added to strengthen their understanding of learned

principles, applying their engineering knowledge to understand new systems, and the opportunity

to practice their engineering skills. Implementation of the laboratory exercises gave the students

a sense of accomplishment. Much enjoyment was realized in the implementation of the dSPACE

DSP system and Simulink intuitive model-based programming. Students also improved their

written and oral communication skills as well as experimental proficiency from the hands-on

approach. In addition, working in a team of diverse students encouraged constant discourse and

exchange of ideas through the course of the design of the controllers. All students have reacted

positively to the experiment and overall interest has definitely been increased. The authors found

the laboratory experiment to help reach the goal of lab-based teaching. The experiment definitely

required critical thinking by the students. Some comments from student evaluations concerning

the laboratory control course are as follows:

1. “The laboratory course was the most challenging and the most rewarding course that I

have taken thus far.”

2. “I found the control laboratory course to be a first-rate lab which prepared me for the

industry---not only by the laboratory exercises it offered but most importantly, by

teaching me how to use deductive logic in solving problems.”

3. “I find it easier to understand material presented via laboratory experiment than solely via

a textbook.”

4. “A very good practical experience. Finally, hands-on labs.”

Table I Course Evaluation Survey Question 1 2 3 4 5

Strongly Disagree Unsure Agree Strongly Average

Disagree Agree

1. Was the course challenging and motivating? 0 0 3 5 20 4.6

2. Did the course meet your expectations? 0 0 3 8 17 4.5

3. Is the lab experiment easy to follow? 0 0 3 15 10 4.3

4. Are the course materials easy to comprehend? 0 0 8 10 10 4.1

5. Are you comfortable using MATLAB/Simulink? 0 0 1 4 23 4.8

6. Are you comfortable using ControlDesk of dSPACE? 0 0 2 6 20 4.6

7. Is the laboratory platform versatile and easy to use? 0 0 3 6 19 4.6

8. Does the implementation of state-feedback controller in 0 0 3 8 17 4.5

dSPACE DSP help your understanding of industrial controls?

9. Does the implementation of a switching controller in 0 0 4 9 15 4.4

dSPACE DSP help your understanding of industrial controls?

10. How do you rate this course? 0 0 2 8 18 4.6

11. Would you recommend other students to take this Course? 0 0 4 6 18 4.5

I learned the most from the control lab that:

I learned the least from the control lab that:

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14

Conclusions

This paper presented a state-of-the-art instructional laboratory that is practical and relevant

component of an engineer’s education. The students learned how to build real-time applications

using dSPACE DSP quickly, and were able to test different control schemes successfully. The

laboratory sessions are adaptable and enable a large group of undergraduate students to carry out

variety of laboratory experiments. Students have gained extensive experience with the

implementation of industrial controllers. They were excited to have access to real hardware to

synthesize their controllers through MATLAB/Simulink programs, validate the controller on a

Simulink model, run the dSPACE DS 1104 DSP-board experiment, download data, and analyze

the control system performance offline without being distracted by software implementation

issues. This environment allowed for extensive experimentation, performance comparison, and

development of several practical control algorithms. It is expected that the techniques employed

in the controller designed for the laboratory experiment will likely be used by the students in

their subsequent employment after completion of their college education.

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