Motivation for the present work

In view of the elaborated literature survey on application of PD, PI and PID logic

controllers in the field of electromechanical and process control instrumentation,

most of the research reported on the application of PID logic controller for

controlling the process parameters. Yuen Fong Chan et. al., reported that the

Modular designing of embedded feedback controllers using PID control. A novel

distributed-arithmetic (DA) based proportional-integral-derivative (PID)

controller algorithm is proposed and integrated into a digital feedback control

system. By using the DA –based PID controller 80% savings in hardware

utilization and 40% savings in power consumption are achieved compared to the

multiple-based scheme. It also offers good closed-loop performance while using

less resource, resulting in cost reduction, high speed, and low power consumption,

which is desirable in embedded control applications [54].

Further, the designing of hardware is reduced the and real time implementation of

PD, P1, PID logic controllers for process control is very rare. Even if so, it is not

found in any research paper or report that the design of ARM Cortex

Microcontroller based complete hardware (including F/V converter, necessary

signal conditioning, control circuitry, LCD and Keypad) and development of

software to realize PID algorithms (using ‘Embedded C’ language) for

measurement and control of a process parameter. For most of the applications PC,

microprocessor, and DSP based/MATLAB/Simulations/PLC/LabVIEW software

and National Instruments’ hardware have been used. Hence it is taken as the

motivation for the present work and it focuses on the design and development of

both the hardware and software aspects of ARM Cortex Microcontroller based

PD, P1, and PID logic controllers for the process parameter such as DC motor

speed measurement and controlling. The present study emphasizes the complete

design of the microcontroller based control systems.

PREFACE

Knowledge-based control has become an important approach towards the

realization of intelligent control that aims to incorporate artificial intelligence into

control systems. The motivation of the present work is to implement a knowledge-

based PID control. It attempts to show how heuristics developed can be

implemented to achieve some of the visionary goals of knowledge-based control.

The architecture adopted in this implementation allows it to be easily interfaced to

current conventional control system to improve on their capabilities.

Remote supervision and controlling as became predominant technology in

the present world, which incorporates TCP/IP protocol into the control

system. The motivation of the present work is to implement a knowledge-

based PID control

The first speed-controlled drive was introduced by Harry Ward Leonard and it

required three machines for scheme implementation. After the invention of

transistor and rapid development of electronics, new possibilities for accurate

control of DC motor, such as PWM technology, appeared. The present research

work describes the development of an embedded system which can be used in the

on-line tuning of industrial PID controllers. Three term (PID) control is still

widely used in industry because of its simplicity, versatility and since it allows

flexible performance over a wide range of operational conditions. Thanks to the

fairly recent arrival of the new families of microprocessor based systems, these

controllers are currently going through an interesting phase of development

(Portillo et. al,1998).

Industrial automatic controllers are used according to their control action as on-off

control, proportional control [P], proportional plus integral [PI] and proportional

plus integration plus derivative control [PID]. Mathematically PID lop tuning

induces an impulse in the system, and the PID loop values are designed based on

control system response. Linear quadratic regulatory theory has been used to

formulate tracking problems whose solution leads to develop the P, PI and PID

controllers.

The most prominent controller in the industrial sector is the PID controller. A PID

controller with a predictive structure has marked advantages, as it will have the

ability to predict an error using the process model, stochastic disturbance model

and a priori knowledge of the future set point and then adjust its controller

coefficients to minimize the predictive future errors before any disturbance to the

process output. A major factor to consider is that in the duty cycle of industrial

plants, different operating conditions and working points require that the PID lop

controllers meet performance specifications that change over the duty cycle.

Hence a PID controller with static coefficients optimized over the entire duty

cycle does not necessarily provide optimal performance.

The closed loop systems consist of an input stage, a processing stage, and an

output stage. The input stage maps sensor to other inputs, such as switches,

thumbwheels etc, to the appropriate error detecting with the help of feedback and

results in modifying and amplifying the error to produce a better result action and

passes to output state (control element). The PID logic is a combination of the

three basic logic modes of proportional, integral and derivative control. This PID

logic can improve all aspects of the system performance. The proportional

controller stabilizes the gain but produces a steady state error. The derivative

controller reduces the rate of change of error. The combined effect of all the three

can be judged.

The DC motor has been used widely in industry and the PID logic is applied to

control motor speed, due to its excellent speed control characteristics. The PID

family controllers are successfully applied to many practical process control

applications involving the physical parameters like liquid level, liquid flow,

pressure temperature, rotational speed of motor etc, The methodology

encompasses the design of PID controllers for D.C motor controlling with step

response and provides the means for a systematic adjustment of the controller gain

in order to meet transient performance specifications.

During the past several years, PID control has emerged as one the most active and

fruitful area for research. The logics allow precise and qualitative information to

be presented in qualitative way. According to a survey of the state of process

control systems conducted by the Japan Electric Measuring Instrument

Manufacturer’s Association, more than 90% of the control loops were of the

proportional-integral-derivative (PID) type. In view of the fact that P/PI/PID

controllers are widely used in industry, the present study is focused on these

controllers.

The great advantage of the proposed control architecture is that the parameters of

PID controllers do not need to adapt and designing with fast response. It can be

easily achieved through scheduling the system output. Most of the industrial

processes are employing PID control technique because of two reasons. One is its

simple structure and the development of w ell-known Ziegler-Nichols tuning

algorithms. Second reason is the reduced number of parameters to be tuned. The

conventional PID controller design usually needs to retune the parameters

(proportional gain, integral time constant and derivative time constant) mutually

by a skilled operator. Control is important for most industrial processes to avoid

disturbances which degrade the overall process performance and a great deal of

work is being done in this field. Control mechanisms can be expensive, but the

low cost and rapidly increasing power of digital circuit technology is providing

the stimulus for digital controllers to be implemented in typical process examples

such as low cost automation controllers, process controllers and automatic test

equipment.

The present thesis describes the design, development, fabrication, and analysis of

ARM processor based P, P1 and PID logic controllers for DC motor speed control

systems, . The thesis is organized into six chapters as follows:

The present thesis describes the design, development, fabrication, and analysis of

remote supervisory control system for implementing PD,PI, PID control logics for

DC motor speed control using ARM Cortex based controller, and DC motor

position control system for solar tracking application. The thesis is organized into

six units as follows;

The chapter one describes an overview of embedded systems. Recent trends in

embedded systems, details of ARM Cortex based Microcontroller LM3S9B96

which includes the introduction of microcontrollers, architecture, 12-bit Analog to

digital converter, PWM generator, general purpose of Input/output ports and

Ethernet communication details.

The second chapter reviews and discusses the general literature survey, literature

survey on ARM processors, methods and applications of P, PI, and PID Logic

Controllers for Process parameters in Control System and solar trackers. This

chapter also discusses the motivation for the present work.

Third chapter gives an overview on origin and evolution of P, P1, and PID theory,

introduction to control system and process control system theory, servo control

system, ON/OFF control theory. The control strategies of Proportional [P] control

action, Proportional plus integral [PI] logic control and Proportional plus integral

and derivative logic control [PID] are discussed detail. It also discusses the

Zeiglar-Nichols method, optimal and non-optimal methods. A brief review of

comparisons of the on/Off, P, PI, and PID controls are presented and references

are mentioned at the end of the chapter.

Chapter 4 deals with design and development of Ethernet based DC Motor speed

control by using ARM Processor. This chapter discusses the principle, hardware,

and software features. The hardware includes the PMDC motor and speed sensing

unit, F/V converter, Personal Computer, driver circuit and final control element.

The experimental implementation of PID is discussed. The software includes PID,

flowcharts for embedded “C” language program implementation. The

experimental results, relevant interpretations for these results and conclusions are

also discussed.

Chapter 5 deals with design and development of DC motor position control

system for solar tracking application using RTC. This chapter discusses the

principle, hardware, and software features. The hardware includes the DC motor

and solar panel, sensor circuit, Personal Computer, relay circuit and final control

element. The experimental implementation of RTC based solar tracking system is

discussed. The software includes flowcharts for embedded “C” language program

implementation. The experimental results, relevant interpretations for these results

and conclusions are also discussed.

Chapter six presents the experimental results and important conclusions of the

present study and scope for the future work in this area.

Preface

The Stanford AI lab cart is a card-table sized mobile robot controlled remotely through a radio link, and equipped with a TV camera and transmitter. A computer

has been programmed to drive the cart through cluttered indoor and outdoor spaces, gaining its knowledge about the world entirely from images broadcast by

the onboard TV system.

The cart deduces the three dimensional location of objects around it, and its own motion among them, by noting their apparent relative shifts in successive images obtained from the moving TV camera. It maintains a model of the location of the

ground, and registers objects it has seen as potential obstacles if they are sufficiently above the surface, but not too high. It plans a path to a user-specified destination which avoids these obstructions. This plan is changed as the moving

cart perceives new obstacles on its journey.

The system is moderately reliable, but very slow. The cart moves about one meter every ten to fifteen minutes, in lurches. After rolling a meter, it stops, takes some

pictures and thinks about them for a long time. Then it plans a new path, and executes a little of it, and pauses again.

The program has successfully driven the cart through several 20 meter indoor courses (each taking about five hours) complex enough to necessitate three or four avoiding swerves. A less sucessful outdoor run, in which the cart swerved around

two obstacles but collided with a third, was also done. Harsh lighting (very bright surfaces next to very dark shadows) resulting in poor pictures, and movement of shadows during the cart's creeping progress, were major reasons for the poorer

outdoor performance. These obstacle runs have been filmed (minus the very dull pauses).

In the process control industry field, majority of control loop theories deals with the

control of the simple process techniques. In practical process control applications

such as speed and position controlling of the motors and many complex processes, the

mathematical model construction is impossible because of its time varying and non-

linearity. In such processes optimal and effective operation controller techniques are

economically vital for process industries, the algorithm based on Proportional-

Integral-Derivative (PID) controllers is one of such techniques. The basic structure of

the PID controllers makes it easy to regulate the process output. Design methods

leading to an optimal and effective operation of the PID controllers. Robust control

has been a recent addition to the field of control engineering that primarily deals with

obtaining system robustness in presences of uncertainties. In this thesis, a graphical

design method for obtaining the entire range of PID controller gains that robustly

stabilize a system in the presence of time delays and additive uncertainty is

introduced. This design method primarily depends on the frequency response of the

system, which can serve to reduce the complexities involved in plant modeling.

This dissertation demonstrates the development of PID algorithms and

supervisory control of DC motors remotely through Ethernet communication from

remote location/anywhere.

The DC motor is one of the most commonly used motors in industrial applications. Being a highly nonlinear system, it poses challenging control problems for high performance applications. This thesis demonstrates how PID control theory provides a systematic way to achieve good performance for these problems. The main contributions of this thesis are the application of the PID control theory to DC motor control. Within the last decade the theoretical background for control of LPV systems has been developed. PID systems constitute a large class of nonlinear systems with a special structure allowing for a systematic approach to controller design. Based on a widely used model of the induction motor and the well-known rotor flux-oriented control scheme, it is demonstrated how LPV methods can be applied to several sub problems in induction motor control.The current equations of the induction motor have a particular structure, which allows them to be written on a complex form. It is shown that for an LPV system with this structure, the optimal controller will also possess this structure. This knowledge can be employed to improve the numerics of the controller synthesis

and to reduce the computational burden in the implementation. Viewing the rotational speed as an external parameter, the current equations of the inductionmotor constitute an LPV system. This is used to design an LPV flux observer.The result is an observer with good performance and very little tuning needed.

At the cost of some conservatism the LPV control theory can be applied to an even wider range of systems known as quasi-LPV systems. It is demonstrated how this can be applied to the design of a stator current controller. As in the case of the flux observer design, the resulting controller performs well and requires very little tuning. In certain cases it is difficult to obtain accurate models using physical principles. We therefore turn our attention to nonlinear black-box modeling with multi-layer perceptrons (MLPs). A novel method for transforming MLP models into quasi-LPV models is presented. An MLP model of an induction motor system is obtained, and the aforementioned model transformation is performed. The resulting quasi-LPV model is then used in the design of a speed controller. This demonstrates how LPV methods can be used in a systematic approach all the way from modeling to controller implementation. Finally, robustness to uncertainty in the time-varying parameters is considered. More specifically, we consider the case where the parameter variation is represented by a diagonal gain matrix, which is fully known except for some small perturbation. A novel type of sufficient conditions for robustness is presented, and it is illustrated how this can beused in the speed controller design.

All controllers and observers are tested on a laboratory setup.The key results have been presented at international conferences or have been submitted for publication in international journals. In the process control industry, majority of control loops are based on Proportional-Integral-Derivative (PID) controllers. The basic structure of the PID controllers makes it easy to regulate the process output. Design methods leading to an optimal and effective operation of the PID controllers are economically vital for process industries. Robust control has been a recent addition to the field of control engineering that primarily deals with obtaining system robustness in presences of uncertainties. In this thesis, a graphical design method for obtaining the entire range of PID controller gains that robustly stabilize a system in the presence of time delays and additive uncertainty is introduced. This design method primarily depends on the frequency response of the system, which can serve to reduce the complexities involved in plant modeling. The fact that time-delays and parametric uncertainties are almost always present in real time processes makes our controller design method very vital for process control. We have applied our design method to a DC motor model with a communication delay and a single area non-reheat steam generation unit. The results were satisfactory and robust stability was achieved for the perturbed plants.

The need for efficient, accurate and simple advanced alternatives arises especially

in the embedded development for process control applications, where most of the

real processes are generally complex, time variant, nonlinear, partially known and

difficult to model. The usage of ARM controllers in wide range of control

applications has made possible establishment of intelligent control in these areas.

Its appeal, from the process control theory point of view, lies in the face that this

technique provides a good support for translating the heuristic knowledge of the

skilled operator, expressed in linguistic terms, into computer algorithms. Fuzzy

control solves real problems, previously not tacked due to their complexity or lack

of information. Fuzzy logic control (FLC) provides a formal methodology for

representing, manipulating, and implementing a human’s heuristic knowledge

about how to control a system. This is the motivation to do research on the design

and development of fuzzy and integrated fuzzy logic controllers for process

parameters and further to provide a motivation for, and overview of, the entire

thesis.

During the past several years, ARM based controllers have emerged as one of the

most active and fruitful controllers for research application development and

control algorithms implementation. That is why the ARM controllers are

frequently used for various applications implementation. ARM controller allows

accurate, efficient and cost effective implementation. It offers a rigorous and

practical technique for manipulating the qualitative results originally expected;

ARM controllers are used because of its low power consumption and efficient

performance.

Since the inception of microcontrollers, ARM is the efficient and low power

conservative controller found in interesting applications developed world wide.

ARM (formerly Advanced RISC Machine and Acorn RISC Machine) is a

reduced instruction set computer (RISC) instruction set architecture (ISA)

developed by ARM Holdings. The ARM architecture is the most widely used 32-

bit instruction set architecture in numbers produced.[2][3]

Originally conceived by Acorn Computers for use in its personal computers, the

first ARM-based products were the co-processor modules for the BBC Micro

series of computers. Its first practical application was as a second processor to the

BBC Micro, where it was used to develop the simulation software to finish work

on the support chips (VIDC, IOC, MEMC) and to speed up the operation of the

CAD software used in developing ARM2.

Fuzzy controllers are very simple conceptually. They consist of an input stage, a

processing stage, and an output stage. The input stage maps sensor or other inputs,

such as switches, thumbwheels, and so on, to the appropriate membership

functions and truth-values. The processing stage invokes each appropriate rule and

generates results for each, then combines the results of the rules. Finally, the

output stage converts the combined result (fuzzy) back into specific (crisp) control

output value. The integrated (fuzzy + PID) fuzzy logic controller is also very

simple in the design. It comprises the fuzzy logic controller cascaded with the

conventional proportional plus integral plus derivative (PID) controller.