Information engineering and computer science

information engineering methodology ppt and information systems and software engineering ppt
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Published Date:14-07-2017
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Introduction to Information Engineering Stephen RobertsLecture 1 A gentle introductionAims • To provide you with an overview of what B4 and information engineering in general is concerned with • To make explicit links between information engineering and the core syllabus especially A1, A2 and A3 • To give you some sense of how central information engineering is to the engineer’s career and to our every day lives.Course Outcomes At the end of this 4 lecture course you should • be able to deconstruct overall data capture / analysis / control system into components and understand how they interact • appreciate the role of the computer as a general purpose information processing tool • understand the role of the operating system and how both sensors and actuators can be interfaced to a computer at the hardware and software level • understand the role of probability as the mathematical tool for modelling uncertainty in sensors, and how to use Bayes rule as a means to combine sensor measurements or prior information • understand the consequences of sampling and ZOH, and how to discretize continuous controllers • be able to analyse the components of a fast-sampled feedback system both in isolation and in the context of the complete systemThe Information Engineering Domain Inference and Analysis Estimation Data Processing Modelling and Control Operating System Data Acquisition Output Hardware Sensors Actuators Real WorldThe Role of Feedback • Note the presence of a feedback loop in the previous architecture. + C(s) G(s) - H(s) • The control system block diagrams you manipulate in A3 are powerful mathematical abstractions for devising control strategies for systems • To actually instantiate/embed this control system in a real vehicle, the controller design and analysis, is only part of the story. Information engineering (inc B4) is much more than control theory.What is C(s) + C(s) G(s) - H(s) A controller that is implemented in all likelihood on a C(s) computer Issues: •What does the software of the controller look like? •What speed must it run at? •Computers are discrete devices but the world is continuous so how does one link the two? •Does using a discrete controller have stability implications? •What design tools are available for the discrete domain? •Do familiar continuous domain analysis tools have discrete time duals?What is H? + C G - H A transfer function between a sensed plant output and the H quantity we wish to control Issues: •How does one sample the plant output ? •How does one transmit measurements to the CPU running the controller? •How does one guarantee that measurements will always be processed ? •What does one do if the sensed output is not what we wish to control e.g sensing color but wanting to control flow rate? •How does one deal with noisy sensor data? •How does one fuse multiple measurements?Information Systems Exemplar • The “Segway” robot shown here is a container of many of the central concerns of the information engineer (and as it happens, electrical engineers) • Sensing (accelerometers, gyro) • Actuation Control (varying payload) • Computing – IO from sensors – Output to actuators – Controllers in software – Estimation of state by processing sensor dataNote: •Duplication of electronics (safety) •Requires interfacing of sensors and motors to computation •Requires control to be implemented on a computer •Control laws are non trivial : to stop you have to first speed up •Requires interpretation of sensor data •Requires an internal modelInfo Eng. Components of the Segway • Sensors - 5 Corriolis (interesting) gyros How do you combine the information from 5 noisy sensors in a principled way? (B4…)Computation Hardware • Data Acquisition : The PIC16F87x Flash microcontrollers process sensor data from the inertial monitoring unit and communicate information to the control module. • Control Module is a 100 MIPS Digital Signal Processor TMS320C2000 from Texas Instruments. • Communication is via CAN and I2C bus • Two boards acting in duplicate for safety • Some interesting stories on redundancy here….Exemplar II – a 3D laser System •Issues – synchronisation of disparate data streams •Estimation of system latencies3D ReconstructionCompelling Cross Discipline Problems Engine Management Building climate control Medical imaging Abnormality detection Very uncertain Plant Imprecise sensor data Machine Learning Large unknown lags Deformable structure Complex 3D reconstruction Diagnosis from measurementsAnd Some More Network analysis Car design National Grid Complex optimisation task Complicated non-linear coupled Active suspension dynamics Traction control, slip estimation Plant identificationLecture II –The Role of the Computer • IO sensor interfaces – Serial ports – Ethernet – PCI – Firewire • Microcontrollers – PICs – embedded systems, – pic diagram ref segway • OS – device drivers • Processes and IPC (inter process communication)Motivation • If we are to design a complete information engineering system we may need to consider of how data is or should be marshalled • Data transfer technology is ubiquitous and 5 Engineers should be able to say something sensible about every day equipmentSensor/Actuator Interfacing • How to get data from sensor to processor? Common choices – Direct to bus (PCI) – External serial protocols RS232, firewire, USB – CAN bus (controller area network) – All need hardware/software to transport data Flight surface control and Vehicle control Seismic sensing networks anomaly detection

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