Control engineering is an engineering discipline that focuses on the mathematical modelling systems of a diverse nature, analysing their dy...

Control engineering is an engineering discipline that focuses on the mathematical modelling systems of a diverse nature, analysing their dynamic behaviour, and using control theory to create a controller that will cause the systems to behave in a desired manner.
The impact of control systems engineering is seen everywhere around us. Control systems are found in cars, house appliances, medical instrumentation, petrochemical refineries, commercial and military jets, robotic manufacturing systems, precision missile systems, etc. At the core of every control system are basic feedback principles.
Control systems engineering is a sub-branch of engineering which addresses modelling, analysis, design, and implementation of feedback control systems. Perhaps the best way to introduce feedback control systems is to refer to the cruise control system found in most cars. The cruise control system accepts a desired speed command from the driver. The actual speed of the vehicle is measured. This measurement is fed back and subtracted from the commanded speed to produce an error signal. This error signal is processed by a control system which figures out — on the basis of a mathematical model — how much fuel must be sent to the engine for the actual speed to “closely match” the commanded speed.The control system tries to achieve this close match in the presence of unmodelled wind disturbances and sensor noise as well as uncertain (or poorly modelled) vehicle/engine properties. In the above car example, the driver specifies speed commands. In autonomous vehicles (e.g. the voyager spacecraft), commands are generated by a guidance system; i.e. a higher level control system.
The above (very simplified) description captures the essence of feedback control systems. Similar control systems and feedback principles are found in many areas: satellite attitude control systems, launch vehicle guidance and control systems, modelling of neural cortex functions and other biological processes, semi-conductor manufacturing furnace temperature control systems, environmental systems (eg ozone depletion), autonomous exploration vehicle guidance and control systems, etc.
Control engineering is necessary in the design of many other products such as robots, automobiles, computers and peripherals, medical equipment, household appliances and space stations. In addition to being useful in many engineering systems, control engineering methods also are highly applicable to diverse areas such as economics, biological systems, climatology and sociology.
The curriculum contains major components in basic mathematics and science, humanities and social sciences, communication, engineering science, engineering design and ethics, breadth in electrical engineering and depth in control engineering.
Control Engineers work in research, design, sales, testing, installation, development and teaching. Many graduates find that an engineering education provides excellent training for fields other than engineering such as business, medicine or law. Since engineers are problem-solvers, there is a constant demand for engineers to solve problems outside typical engineering fields.
Modelling, analysis, design, and implementation are all vital components of control systems engineering. When all are considered, the job opportunities for control engineers are excellent. Graduating engineers who possess implementation/building skills should have no problem finding challenging positions. Individuals interested in modelling, analysing, and designing control systems should note that mathematical maturity is essential. Controlling, for example, a critical communications satellite cannot be taken lightly. Systemspecific modelling knowledge is important. Such knowledge can be obtained via independent study and senior design projects. Internship positions are also highly recommended. New graduates can find job opportunities in many areas: aerospace, chemical, medical instrumentation, semiconductor manufacturing, robotics, intelligent systems, etc.



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