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CONTROLS Dr. Konstantinos Tsakalis Area Chair: Dr. Andreas Spanias Professor and Director NSF SenSIP I/UCRC. Control Systems at ASU. EE Faculty: (Lai), Rodriguez, Si, Tsakalis Topics: System Modeling, Control Systems Design, Neural Networks, Adaptive and Learning systems,
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CONTROLSDr. Konstantinos TsakalisArea Chair: Dr. Andreas SpaniasProfessor and Director NSF SenSIPI/UCRC
Control Systems at ASU • EE Faculty: (Lai), Rodriguez, Si, Tsakalis • Topics: System Modeling, Control Systems Design, Neural Networks, Adaptive and Learning systems, Fault Detection, Real-time control applications • Applications: Aerospace (aircraft/missile control, optimal path planning) Semiconductor Manufacturing (process control, scheduling) Power Systems (generation, distribution) Biomedical applications (prosthetics, neuroscience)
Control Systems Applications Control Systems: Use feedback to counteract the effects of uncertainty Early feedback control applications: Amplifiers, Telephony 60’s-70’s successes: Optimal and Multivariable Control, Rocket/Missile/Aircraft control Optimal path planning
Control Systems Applications Cruise control “Launch” control Engine management Active Suspension ABS 80’s - 90’s themes: Sophisticated & reliable embedded control systems Simulation and Visualization Robotics Large-scale systems, Networks (Small and powerful computers, Cheap computations)
Control Systems Applications High performance multivariable controllers designed from data. Reliable, with quick design turnaround time. Award-winning industrial controller • Philosophy and Expertise: • Control systems design and implementation • Modern multivariable modeling and control • Theory to experiment • Transferable technology, Systematic, Reliable • Integrated modeling and control • System identification, Uncertainty estimation, Controller design • Linear-Nonlinear methods, Feedback-Feedforward • Adaptive systems, Optimization • Embedded controller implementation • Controller performance and “health-status” monitoring • Applications: • Semiconductor Manufacturing (Semy/Brooks,Motorola,Intel) • Furnace temperature control, Run-to-Run, Scheduling • Process Control (Honeywell) • Paper machines, Petrochemical industry • Wastewater treatment using microbial fuel cells with peroxide production (SERDP, new) • Power Systems (EPRI) • Pulverizers, Power System Stabilizers • Biomedical (NSF, ERF) • Closed-Loop Control of Brain Dynamics in Epilepsy • Electromechanical, Embedded (CEINT-educational) We have developed a “feedback decoupling” control technology to design implantable brain stimulators that suppress seizures with high therapeutic efficacy and less side effects. Based on biologically plausible computer models of the brain.
Control Systems Education A variety of application domains: Understanding first principles (more is better) Unified analysis and design methods: The systems approach Undergraduate Courses Background: EEE202, MAT*** (ODE, Lin. Algebra, Laplace) Systems fundamentals: EEE 203, 304 (Frequency domain) Classical feedback theory: EEE 480 (Basic concepts, simple designs) Computer Controlled Systems : EEE 481 (Discrete, embedded control) Graduate EE Courses: Linear (582) & Nonlinear (586) Systems, Transform Theory (550) Robust Multivariable (588), Optimal (587), Neural Nets (511) Filtering of Stochastic Processes (581), Adaptive Control (686) Other Courses: System Identification, Applied Optimization, Numerical Analysis MSE Exam: 480-481-581-582-586-587; + selection from 588, 511
Job Opportunities Industrial needs for Control Engineers Process Engineers with control/optimization background Typical EE employment: (Mostly MS/PhD, some BS) Aerospace (Boeing, Hughes, … ) Automotive (GM, Ford, …) Semiconductors (IBM, TI, AMD, Motorola, Intel) Equipment Manufacturers (Applied Materials, …) Component manufacturers (Seagate, …) Support industry/Control solutions (Honeywell, Foxboro, Brooks, …) Simulation Software (Matlab, Microsoft) Chemical/Bio Industries, Power, Communications, …