You can find all the course materials related to the courses that have been held by Dr. Taghirad here along with the complimentary materials that are being updated regularly.

Introduction to Electrical Engineering

In this course the general contents of the Electrical Engineering Program is detailed for first year undergraduate students. This course describe the academic program and motivates the students by describing the potential positions of an electrical engineer in industries. The fields of studies in Electronic systems, Power systems, Communications and Control systems are detailed by four lecturers expert in these fields.

Course site, Ecourses

Modern Control

This course aims to introduce the state space methods in modeling and feedback control of linear time invariant systems. The concepts induced in this framework such as controllability, stabilzability, observability and detectability is defined and elaborated in this course. Next the system transformation, stability and realization and state controller and observer design will be explained. Due to the structure of this course, required linear system theories are developed, while with an applied vision, the application of those theories in practice is emphasized.  Finally the expertise of the students are examined  in a thorough and comprehensive design task  as a term project.

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Introduction: Why Feedback, Conceptual components of feedback systems, Physical components of Feedback systems, State definition, and state feedback. Week 2 LTI System Representation: State space representation, modeling based on physical principles, electrical systems, electromechanical systems, mechanical systems. Week 3 LTI System Representation: Hydraulic systems, modeling based on Lagrange equation, mathematical linearization, modeling uncertainty. Week 4 Linear system theory: Linear system properties, solution to linear system D.E., zero-input solution, zero state solution, state transition matrix. Week 5 Linear system theory: State transition matrix derivation methods: Laplace, Dynamical modes, Caley-Hamilton, Silvester methods, similarity transformations. Week 6 Linear system theory: System poles and transmission zeros, diagonalization, Jordan forms,  block-Jordan forms. Week 7 Controllability and Observability: Observability, observability matrix, eigenvector test, controllability, duality, Kalman canonical  decomposition. Week 8 Midterm Week 9 Realization and Stability:  Controllable and Observable canonical  form, realization of MISO systems, realization of SIMO systems, MIMO realizations. Week 10 Realization and Stability:  Stability definitions, internal stability, BIBO stability, Lyapunov matrix equation. Week 11 State feedback: State feedback properties, tracking objective, pole placement methods, pole placement for MIMO systems. Week 12 State feedback: Optimal state feedback LQR, applied gain selection, disturbance rejection, State integral feedback. Week 13 State Observer: State observer general idea, full state observer, Luengerger Observer. Week 14 State Observer: Optimal state Observer LQE, Kalman Filter. Week 15 State feedback-Observer: Separation Theorem, state feedback with disturbance estimation, closed loop performance.

Reference Texts

• حميد رضا تقی راد، مقدمه ای بر كنترل مدرن، انتشارات دانشگاه صنعتی خواجه نصيرالدين طوسی، 1393.
• علي خاكي صديق، اصول كنترل مدرن، انتشارات دانشگاه تهران، 1392.
• Control engineering: a modern approach, Pierre Bélanger, Saunders College Pub., 1995.
• Linear systems, Thomas Kailath, Englewood Cliffs, N.J. Prentice-Hall, 1980.
• Modern control theory, William L. Brogan, 3rd ed., Englewood Cliffs, N.J., Prentice Hall,
• Modern control engineering, Katsuhiko Ogata, 4th ed., NJ, Prentice Hall, 2010.
Linear Systems Control

This course aims to introduce the basic concept of linear feedback control to the students. As the first and main course in control, special emphasis is on the analysis of feedback control systems, especially on the stability analysis. First modeling of the systems with transfer functions, and block diagrams are introduced, and flow graphs and Mason rule for its simplification is taught. Then the time response characteristics of first and second order system are explained, and the stability analysis is started using Roth-Horowitz criteria. Next static feedback compensation, and stability analysis through Root Locus method is detailed, and then frequency response method and Bode, Nyquist and Nichols charts are elaborated. Finally, Dynamic compensation, and general method of feedback controller design for lead-lag and PID’s are explained, based on the frequency response method. The expertise obtained by the students in this course is examined in a thorough and comprehensive design task as a term project.

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Introduction: Why feedback, conceptual components of feedback systems, physical components of feedback systems, the magic of feedback. Week 2 Introduction: the characteristics of feedback systems, stability, tracking, disturbance attenuation, noise rejection and insensitivity to model uncertainty. Week 3 System Representation: Laplace transform, modeling of the systems with transfer functions, block diagrams, rules and simplifications, flow graph, Mason rule. Week 4 Linear system time response: impulse and step response, first and second order time response characteristics, rise time, settling time, steady state error, overshoot, decay ratio, time and frequency domain relation. Week 5 Stability analysis: BIBO stability definition, characteristic polynomials, poles, stability condition, Routh – Horwitz stability criteria. Week 6 Root Locus: Closed-loop pole relation to the loop gain, Root locus graphical method of pole representation, magnitude and angle laws. Week 7 Root Locus: Rules of root locus representation, gain selection, static feedback design, desired characteristics, time and frequency domain relation. Week 8 Midterm Week 9 Frequency Response:  Bode response, Bode theorem,  the relation between magnitude and phase, cross over frequency, bandwidth, and frequency domain characteristics of second order systems. Week 10 Frequency Response:  Nyquist diagram, encirclements and number of closed loop poles, Nyquist contour, nyquist stability criteria. Week 11 Frequency Response:  Ultimate point, stability characteristics,  poles and zeros on imaginary axis, controller design based on nyquist diagram, relation between Bode and Nyquist plot. Week 12 Frequency Response:  Nichols chart, M circles, sensitivity, and complementary sensitivity transfer functions, loop gain and feedback characteristics in  Nichols chart. Week 13 Dynamic feedback design: Basic definitions, stability margins, gain and phase margin, bandwith, cross over frequencies, relation between time and frequency response. Week 14 Dynamic feedback design: P controller design based on stability margin,  PI controller design based on steady state characteristics or disturbance rejection in steady state. Week 15 Dynamic feedback design: Lag controller design, PD controller and closed loop bandwidth, lead controller, PID and lead-lag controller, comprehensive example.

References

 1 Modern control Systems, R.C. Dorf and R.H. Bishop, 12th Edition, Prentice Hall, TJ 216.D67 2010. 2 Automatic Control Systems, 8th Edition,  Farid Golnaraghi and Benjamin C. Kuo, Wiley, TY 213.K8354 2010. 3 Modern control engineering, Katsuhiko Ogata, 5th ed., NJ, Prentice Hall, TJ 213.O28 2010. 4 Control engineering: a modern approach, Pierre Bélanger, Saunders College Pub., 1995.
Instrumentation

This course aims to introduce the fundamentals of measurements and instrumentation systems. In this course the student learn how to choose the correct method of sensing, the requires sensor and transducer for a particular application, in addition to the conditioning circuit required to accomplish an instrumentation task. The quantities covered in this course are, force, torque, pressure, position, velocity, acceleration, temperature, and fluid flow. The course consists of usual course lectures in addition to a complete research project, in which each student research on a particular instrumentation system for a particular application, whose result is presented and published on the web in the selected project page.

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Introduction: Application of Instrumentation systems, measurement error and accuracy, sensors for different measurements. Week 2 Introduction: Sensors for different measurements. Week 3 Conditioning circuits:  Active and passive conditioning circuits, for bias compensation, amplifier and gain, filters, … Week 4 Force, torque and pressure:  Introduction to strain and stress, strain gauges, conditioning circuits. Week 5 Force, torque and pressure: Different force and torque sensors. load cells, link and beam type load cells, ring type, torsion torque meters. Week 6 Force, torque and pressure:  2 axis force-torque measurement, 3 and 6 axis force-torque measurement, pressure transducers, vacuum transducers. Week 7 Position Measurements:  Definitions, Kinematics relations, potentiometers, resistive, capacitive, magnetic type transducers Week 8 Position and Velocity:  Incremental encoders, quadrature counter, linear and angular velocity measurements, Seismic measurements. Week 9 Midterm Week 10 Temperature: Definitions and methods of measurements, resistive thermometers, RTD’s, Thermistors, Methods of Calibrations. Week 11 Temperature  Thermocouples, thermoelectric properties, thermelectric materials, Thermocouple types. Week 12 Temperature:  Thermocouple industrial types, Pyrometers, photonic thermometers, other industrial types of thermometers. Week 13 Fluid Flow:  Definitions, laminar and turbulant  flow. velocity profiles in the pipes, Pitot tubes, calibration methods. Week 14 Fluid Flow:  compressible flow measurements, hot wire and hot film anymometers, Rotameters,  flow meters in open channels. Week 15 Fluid Flow:  Turbine flowmeters, Venturi, nozzle and orifice flow meters Sluice and Wier gates, capillary tubes, Laser-doppler anymometers.

References:

 1 مبانی اندازه گیری در سیستمهای ابزار دقیق، حمید رضا تقی راد و سید علی سلامتی، انتشارات دانشگاه صنعتی خواجه نصیرالدین طوسی، 1392 2 Instrumentation for engineering measurements, J.W. Dally, W.F. Riley and K.G. McConnell, Prentice Hall, TA 165 D34, 1983. 3 Process Control Instrumentation Technology, Curtis D. Johnson, Prentice Hall, TS 156.8 J63, 2000 4 Principles of measurements and instrumentations, A.S. Morris, Prentice Hall, TS 156.8 M638, 1988. 5 Industrial Control Handbook, E.A. Parr, Industrial Press, 3rd Ed., TS 156.8 P24, 1998. 6 Electronic instrumentations and measurements, L.D. Jones and A. Foster, Prentice Hall, TK 7878.4 J66, 1991.
Principles of Nonlinear Control
This course aims to introduce Principles of nonlinear system, and nonlinear control schemes. The course is divided into two parts, namely analysis and synthesis. In the analysis part, the state space description of nonlinear system is introduced, and the phase portrait analysis of the second order system is elaborated. Stability analysis of the nonlinear system, based on linearization method, and direct method of Lyapunov are explained next, while the stability analysis is completed with Lasalle theorem. In the synthesis part, input-output feedback linearization are described, and sliding mode control is introduced next. To evaluate the expertise of the student in nonlinear control analysis and synthesis, a thorough and comprehensive design task is performed by students as a term project using Matlab simulations.

The tentative course contents are as following:

 Time: Teaching Contents Week 1 Introduction: Common nonlinear systems, state space representation, equilibrium point. Week 2 Introduction: Common behaviors of nonlinear systems, and limit cycles. Week 3 Phase plane Analysis: 2nd order nonlinear systems, phase portrait graphical representation, singular points. Week 4 Phase plane Analysis: Numerical methods of phase portrait generation, stability analysis of linear systems via phase portrait. Week 5 Phase plane Analysis: Stability analysis of nonlinear system with phase portraits. Week 6 Stability Analysis: Different definition of stability for nonlinear systems, Lyapunov linearization method. Week 7 Stability Analysis:  Lyapunov direct method, globally asymptotically stability analysis. Week 8 Stability Analysis: Lyapunov direct method extensions, Lasalle’s theorem,  instability theorems. Week 9 Midterm Exam Week 10 Describing Functions: Limit cycle definition and characteristics, existance theorems, describing function definitions. Week 11 Describing Functions: Describing function for saturation, relay, dead zone and hysteresis, limit cycle analysis by describing function, limit cycle stability analysis. Week 12 Feedback Linearization: input-output feedback linearization algorithm, internal dynsmics. Week 13 Feedback Linearization: Zero dynamics, asymptotically minimum phase nonlinear systems, comprehensive example. Week 14 Sliding mode: General description, sliding surfaces, switching mode controller law, sliding mode controller structure, comprehensive example. Week 15 Sliding mode: Chattering problem, boundary layer description, sliding condition extension, fixed threshold boundary layer, variable boundary layer, comprehensive example.

References

 1 Nonlinear systems, H. Khalil, Prentice Hall, 3rd Edition, QA427.K48, 2002. 2 Applied Nonlinear Control, J.J. Slotine and W. Li, Prentice Hall, 1991. 3 Nonlinear Control Systems, A. Isidori, Springer Verlag, 1995. 4 Nonlinear System Analysis, M. Vidyasagar, Prentice-Hall, 1993. 5 Selected papers. E-books on this subject are available in my ebooksControl EngineeringNonlinear. Contact me if you need one.
Industrial Control

This course aims to introduce the basic concept of industrial automation and modeling and control of industrial process. The course is divided into two parts, namely industrial automation and process modeling and control. The first part of the course covers modeling of industrial processes through physical principles, and also identification of them using time and frequency domain techniques. Tuning of industrial controllers like PID is elaborated using Ziegler-Nichols criteria as well as other techniques. Finally the controller implementation through pneumatic, electric, electronic hardware as well as digital implementation is introduced. In the second part, hydraulic and pneumatic system in industrial automation is introduced and their logic design is elaborated. Next, Programmable logic controllers (PLC) are introduced and their hardware and software are explained, special attention to ladder programming for industrial processes are examined through comprehensive examples. Siemens S7 PLC’s are briefly introduced here, due to its intensive use in industries. The student will practice their knowledge of PLC programming in the PLC LAB, which is offered as a one credit course.

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Process Modeling: modeling with physical principals, state equations, electromechanical system modeling, hydraulic systems modeling. Week 2 Process Modeling: Mechanical systems modeling with Lagrange, open tank modeling, level control, modeling of tanks with pump, drums, thermal processes. Week 3 Process Identification: Dynamic models, time response methods, two, three and four components models, integrating systems, oscillating systems. Week 4 Process Identification: Frequency response methods, Z.N. frequency responce method, relay feedback method, parametric identification, least-squares solution. Week 5 PID controllers, implementation: PID controller characteristics, electical implementation, electronic implementation, pneumatic implementation, microprocessor implementation. Week 6 PID controllers, tuning: Ziegler-Nichols tunings methods, IAE, ISE, and other methods. Week 7 PID controllers, tuning:  Extended Z.N. method, when and why Z.N. are effective, integral windup, systems with delay. Week 8 PID controllers, design: P controller design based on stability margin,  PI controller design based on steady state characteristics or disturbance rejection in steady state. Week 9 PID controllers, design: Lag controller design, PD controller and closed loop bandwidth, lead controller, PID and lead-lag controller, comprehensive example. Week 10 Midterm Week 11 Introduction: Industrial process, Automation benefit, automation components, process modeling and control, PID controllers. Week 12 Industrial Automation: Pneumatic and hydraulic in automation,  valves and actuators, position control of hydraulic cylinders, Week 13 Industrial Automation: position control of hydraulic cylinders, sequence control, cascade control. Week 14 Industrial Automation: Programmable Logic Controller (PLC), basics, hardware, programming methods, simple program development. Week 15 Industrial Automation: PLC applied examples, ladder programming, PLC industrial process examples, introduction to Siemens S7 PLC’s.

References

 1 Hamid D. Taghirad, An Introduction to Industrial Automation and Process Control, With Presentation of Siemens Step7 PLC, 2nd Edition, K.N. Toosi University Publication. 2 Advanced PID Control, K.J. Astrom, and T. Hagglund, Third Edition, Inst. Soc. America, TJ 223.P55A85, 2006 3 Control Engineering, A Modern Approach, P.R. Belanger, Saunders College Pub. 1995. 4 PLC and their engineering application, A.J. Crispin, McGraw Hill, TJ223.P76C75, 1990 5 Power Pneumatics, M.J. Pinches and B.J. Caller, Prentice Hall, TJ950.C35, 1997
Digital Control
This course aims to introduce the concept of digital control system. In this course, the sampled-data and digital control system are introduced, and data sampling and reconstruction modeling and theorems are elaborated. Discrete time difference equation and Z transform transfer functions are used for system representation, and state transition matrix is introduced. Stability analysis of digital control system is then explained, using Jury criteria. Digital implementation of analog controllers is explained next, and different digital controller design methods, like deadbeat and pole placement is introduced. A brief introduction to optimal control schemes will conclude the first part. To evaluate the expertise of the student in control analysis and synthesis, a thorough and comprehensive design task is performed by them as a term project using Matlab simulations.

The tentative course contents are as following:

 Time: Teaching Contents Week 1 Introduction: Sampled-data control systems, sample and hold, sampling modeling, data reconstruction , Shannon theorem, aliasing. Week 2 Digital system representation: Z-transform, difference equation, state transition matrix, system characteristics. Week 3 Digital system representation: Discrete models from continuous models, D/A convertor models, ZOH models. Week 4 Digital system characteristics: Controllability and observability, stability, Jury test. Week 5 Digital implementation of analog controllers: Forward difference, backward difference, bilinear Tustin, Tustin with pre-warping. Week 6 Implementation: Impulse invariance, step invariance, matched poles and zeros, anti-aliasing filters. Week 7 Digital controller Design: Classical methods, digital PID’s, digital lead-lags, dead-beat controller. Week 8 Midterm Exam Week 9 Digital controller Design: State space methods, pole placement methods. Week 10 Digital controller Design: Controller implementations,  tracking performance. Week 11 Digital controller Design: Optimal state space controllers, LQR controllers. Week 12 Digital Observers: State observers, pole placement methods, optimal observers. Week 13 Digital Observers: Kalman filters, current estimates observers. Week 14 LQR/LQG controllers: State observer-state feedback configuration, disturbance rejection, tracking performance.

References

 1 Digital control systems, Benjamin Kuo, Saunders College, TJ223.M53 K86 1991. 2 Computer-controlled systems, Astrom and Wittenmark,  Addison-Wesley,1998. 3 Discrete-time control systems, Ogata, Prentice Hall, QA402.04, 1987.
Signals and Systems
This course aims to introduce the basic concepts and mathematical analysis  for signals and system representations. Linear time invariant continuous and discrete time domain systems are considered in this course. Impulse response and  convolution integral is the main tools for the signals and system analysis in time domain, while Fourier analysis, discrete Fourier analysis, Laplace and Z transform are introduced as the main tools for signals and system analysis in frequency domain. Finally, the application of the mathematical analysis on the filter design, and the frequency response of feedbak control system is taught.

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Introduction: Signals and system mathematical definition, the characteristics and properties of them. Week 2 LTI continuous systems: Time domain analysis, and convolution integral for LTI systems, properties and characteristics. Week 3 LTI discrete systems: Time domain analysis, and convolution sum  for LTI systems, properties and characteristics. Week 4 Fourier analysis: Frequency domain representation of signals, periodic signals and Fourier series,  Fourier series properties, conversion tables. Week 5 Fourier analysis: Frequency domain representation of signals, aperiodic signals and Fourier transform,  Fourier Transform properties, conversion tables, inverse fourier transform. Week 6 Fourier analysis: System representation with Fourier transform, region of convergence and stability, block diagram representation. Week 7 Discrete Fourier analysis: Frequency domain representation of discrete time signals, periodic signals and discrete Fourier series,  discrete Fourier series properties, conversion tables. Week 8 Discrete Fourier analysis: Frequency domain representation of discrete time signals, aperiodic signals and discrete Fourier transform,  Fast Fourier Transform. Week 9 Midterm Week 10 Laplace Transform:  Frequency domain representation of continuous time systems, definition, properties, inverse Laplace transform. Week 11 Laplace Transform: Laplace transform properties, duality properties, region of convergence, stability. Week 12 Z  Transform:  Frequency domain representation of discrete time systems, definition, properties, inverse Z transform. Week 13 Z  Transform: Z transform properties, duality properties, region of convergence, stability. Week 14 Application: Analog filters, frequency separation, ideal filter, Butterworth filter, cross over frequency, bandwidth, design limitations. Week 15 Application: Feedbak control systems, unstable systems, stabilizing usin feedback, Bode diagrams, stability margin.
 1 A.V. Oppenheim and A.S. Willskey , Signals and systems, Third Edition, Prentice, 1998 2 ترجمه کتاب فوق توسط آقايان دکتر علي خاکي صديق و کمال محامدپور، انتشارات دانشگاه صنعتي خواجه نصير، 1380 3 H.Kwakernaak and R. Sivan, Modern Signals and Systems, Prentice Hall, 1991 4 R.E. Ziemer, W.H. Tranter and P.R. Fannin, Signals and systems: Continuous and discrete, Third Edition, McMillan Pub. Co., 1993

Robotics

This course aims to introduce the fundamentals of mechanics and control of robotic manipulators. For this the required mathematics is introduced, concepts like manipulator Kinematics and Dynamics are elaborated, and different approaches to derive them are explained. Jacobian, singularity and redundancy is introduced next, and different control algorithm in joint-space and Cartesian space is introduced. The linear and nonlinear control algorithms are developed through the course, and a thorough and comprehensive design task is performed by them as a term project.

Course site, Ecourses

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Introduction: Robotics at a glance, robotic manipulators, joints, links, DOF, … Week 2 Introduction: Mathematical Transformations, positions and orientations, rotation matrix, Euler angles, homogeneous transformations. Week 3 Kinematics:  Joint space and Cartesian space, Denavit-Hartenberg parameters, forward Kinematics, inverse Kinematics. Week 4 Kinematics:  Geometrical approach, Inverse Kinematics, Pfeifer Theorem. Week 5 Jacobians:  Linear and angular velocity, Jacobian definitions, Singularity and Redundancy, velocity propagation, force and torque relation. general method. Week 6 Dynamics:  linear and angular acceleration, Newton-Euler method, force propagation. Week 7 Dynamics:  Lagrange method, general description, robot dynamic derivation, Lagrange iterative method. Week 8 Path Planning:  Joint space and Cartesian space methods, cubic interpolation, Parabolic Blend interpolation, multiple points with via points. Week 9 Midterm Week 10 Linear Control:  Robots with gearbox, dynamic remodeling, linear identification, linear controller design. Week 11 Nonlinear Control:  General controller topology, Feedforward control, Feedback linearization, computed torque method. Week 12 Nonlinear Control:  Cartesian space control schemes, Inverse Jacobian method, Jacobian Transpose method, Modified JT method. Week 13 Force Control:  The general topology, virtual damper-spring concept, force measurements, force control schemes Week 14 Hybrid Control:  force-position control, matrix inclusion method, hybrid force-motion control topology Week 15 Impedance Control:  General topology structure, application of virtual damper-spring concept, defining of desired impedance of a robot, impedance control scheme.

References

 1 M. W. Spong, S. Hutchinson, M. Vidyasagar, “Robot Modeling and Control”, New York, Wiley, 2006. 2 Lung-Wen Tsai, “Robot analysis: the mechanics of serial and parallel manipulators”, New York, Wiley, 1999. 3 John J. Craig, “Introduction to robotics: mechanics and control”, 3rd Edition, Mass., Addison Wesley, 2005. 4 H.Asada and J.J. Slotine, “Robot Analysis and Control”, J. Wiley, 1989. 5 Selected papers.
Parallel Robots

In this course the kinematics, dynamics analysis and control of parallel manipulators are studied in detail. The main emphasis of the course is the mechanics of complex structured robots such as parallel manipulators. Comprehensive kinematics and dynamic analysis of parallel manipulators is presented, and the control topologies for these robots are described. In a comprehensive design project as a series of exercises in the assignments, the students learn how to analyze the kinematics and dynamics of a planar parallel manipulator. Furthermore, A research project is conducted by the student as a term project.

The tentative course contents are as following.

 Time: Teaching Contents Week 1 Introduction: Robotics at a glance, kinematic chains, Grubler criterion, loop mobility criterion, robot classifications, Week 2 Introduction: Description of position and orientation, screw-axis representation, Euler angle representations. Week 3 Kinematics: Kinematics analysis of parallel manipulators, vector loop equations, 3RRR manipulator. Week 4 Kinematics: Kinematics analysis of spatial orientation manipulator and Stewart Gough manipulator. Week 5 Jacobian:  Angular and linear velocity, Jacobian matrices, Singularity conditions, conventional Jacobians, 3RRR manipulator, spatial orientation manipulator and Stewart Gough manipulator, Screw-based Jacobians. Week 6 Stiffness: Force-moment relations, principle of virtual work, 3RRR manipulator, stiffness analysis of parallel manipulators, stiffness analysis of Stewart-Gough platform. Week 7 Midterm Exam Week 8 Dynamics: Dynamics analysis of parallel manipulators, Newton-Euler formulation, dynamic analysis of Stewart-Gough platform. Week 9 Dynamics:  dynamics analysis of parallel manipulators, Principle of virtual work, Week 10 Dynamics:  Lagrange formulation, dynamic analysis of CKCM Robot, properties of manipulator dynamics. Week 11 Control: Introduction to control of parallel manipulators, position control topologies, Nonlinear Control Background. Week 12 Control: Position control: inverse dynamics control. Week 13 Control: Robust inverse dynamics control, Force control topologies stiffness control. Week 14 Control: Force control topologies: Direct force control, impedance control. Week 15 Hybrid Control:  Force-position control, matrix inclusion method, hybrid force-motion control topology

References

 1 Hamid D. Taghirad, “Parallel Robots: Mechanics and Control”, To appear, CRC Press, 2012. 2 Lung-Wen Tsai, “Robot analysis: the mechanics of serial and parallel manipulators”, New York, Wiley, 1999. 3 M. W. Spong, S. Hutchinson, M. Vidyasagar, “Robot Modeling and Control”, New York, Wiley, 2006. 4 L. Sciavicco, B. Siciliano, “Modelling and Control of Robot Manipulators” , Springer Verlag, 2nd ed. 2001. 5 J.P. Merlet, “Parallel robots”, Boston, MA : Kluwer Academic Publishers, 2000. 6 Carl Crane, “Screw theory for spatial robot manipulators”, Cambridge, Oxford, 2005. 7 Selected papers.
Nonlinear Control

This course aims to introduce the analysis of nonlinear system, and the common nonlinear control schemes. The course is divided into two parts, namely analysis and synthesis. In the analysis part, the state space description of nonlinear system is introduced, and the phase portrait analysis of the second order system is elaborated. Stability analysis of the nonlinear system, based on linearization method, and direct method of Lyapunov is explained next, while the stability analysis is completed with Lasalle’s theorem, absolute stability notion, Popov, and circle criteria, and the stability analysis of time varying nonlinear systems. finally, the analysis of limit cycles is thoroughly elaborated using describing functions. In the synthesis part, after introducing of Lie Algebra, and required mathematics, Feedback linearization methods for input-state, and input-output cases are described, and backstepping method and sliding mode control is introduced next. To evaluate the expertise of the student in nonlinear control analysis and synthesis, a thorough and comprehensive design task is performed by students in a series of the assignment exercises using Matlab simulations. Moreover, a research project is assigned to each student to further study the topics which are less emphasized throughout the course as a term project.

Course site, Ecourses

The tentative course contents are as following:

 Time: Teaching Contents Week 1 Introduction: Common nonlinear systems, state space representation, equilibrium point, common behaviors of nonlinear systems, and limit cycles. Week 2 Phase plane Analysis: 2nd order nonlinear systems, phase portrait graphical representation, singular points. Week 3 Phase plane Analysis: Graphical and  numerical methods of phase portrait generation, stability analysis of linear systems via phase portrait, stability analysis of nonlinear system with phase portraits. Week 4 Stability Analysis: Different definition of stability for nonlinear systems, Lyapunov linearization method, Lyapunov direct method, globally asymptotically stability analysis. Week 5 Stability Analysis: Lyapunov direct method extensions, Lasalle’s theorem, time varying nonlinear systems stability theorems, instability theorems Week 6 Stability Analysis: Absolute stability theorems, Sector nonlinearity, Popov and circle criteria, Lyapunov based controller synthesis. Week 7 Describing Functions: Limit cycle definition and characteristics, existance theorems, describing function definitions. Week 8 Describing Functions: Describing function for saturation, relay, dead zone and hysteresis, limit cycle analysis by describing function, limit cycle stability analysis. Week 9 Midterm Exam Week 10 Feedback Linearization: Background mathematics, Lie algebra, input-state feedback linearization, feedback linearizability, involutivity, and controllability conditions. Week 11 Feedback Linearization: input-state feedback linearization algorithm, normal forms, diffeomorphism, comprehensive examples. Week 12 Feedback Linearization: input-output feedback linearization algorithm, internal dynsmics, zero dynamics, asymptotically minimum phase nonlinear systems, comprehensive example. Week 13 Back Stepping: Controller general description, required conditions, Back stepping method, controller characteristics, comprehensive example. Week 14 Sliding mode: General description, sliding surfaces, switching mode controller law, sliding mode controller structure, comprehensive example. Week 15 Sliding mode: Chattering problem, boundary layer description, sliding condition extension, fixed threshold boundary layer, variable boundary layer, comprehensive example.

References

 1 Nonlinear systems, H. Khalil, Prentice Hall, 3rd Edition, QA427.K48, 2002. 2 Applied Nonlinear Control, J.J. Slotine and W. Li, Prentice Hall, 1991. 3 Nonlinear Control Systems, A. Isidori, Springer Verlag, 1995. 4 Nonlinear System Analysis, M. Vidyasagar, Prentice-Hall, 1993. 5 Selected papers.
Robust Control

In this course the stability and performance analysis of feedback system in the presence of model uncertainty are introduced, and robust controller synthesis methods for uncertain systems are presented. The scope of the course is limited to linear systems, LFT type of uncertainty, H control and μ-analysis and synthesis. In addition to elaborate the required theory, the students learn how to use Robust Control Toolbox of Matlab. Moreover, a comprehensive design project is thoroughly accomplished by the students as a term project.

The tentative course contents are as following.

 Time: Contents Week1 Introduction:  Modeling, uncertainty and robustness,  Sensitivity function,  General regulator problem,  Small-gain theorem and H∞ Week2 Normed Spaces:  Norms of signals, Norms of systems, Relation between signals and systems norm, Computing 2 and ∞ norms, Multivariable norms, Hilbert and Banach spaces. Week3 Robust problems Modeling: Plant uncertainty, different types of uncertainty, parametric uncertainty, unstructured uncertainty, illustrative examples. Week4 Robust problems Analysis:  Internal stability, Robust stability, based on Sensitivity functions, H∞ norms, and structured singular values. Week5 Robust controller synthesis:  Controller parameterization, Design constraints, algebraic constraints, analytic constraints, interpolation conditions, waterbed effect. Week6 Mixed Sensitivity Problem:  Definition to mixed sensitivity, the augmented state-space model. Week7 Solution to general regulator problem (Methods): H2, H∞ solutions based on Ricatti Equations. H∞ solutions based on LMI, H2/ H∞ solutions. Week8 Solution to general regulator problem (Methods): H∞ solutions based on LMI, H2/ H∞ solutions. Week9 Midterm Exam Week10 Solution to general regulator problem (implementations): Design for SISO and Non-minimum phase, Comprehensive case study. Week11 Solution to general regulator problem (implementations): Design for unstable and Non-minimum phase systems and disturbance rejection, Comprehensive case study. Week12 μ Analysis: Structured singular values,  μ -Analysis. Week13 μ synthesis:  μ -Synthesis, Comprehensive case studies. Week14 Case studies: Control of F14 Aircraft, robust problem formulation, controller synthesis, performance evaluation and improvement. Week15 Case studies: Three inertia system: robust modeling and identification, weighting function selection, H∞ and H2/ H∞ controller design and improvement, μ synthesis, controllers performance evaluations.

References:

 1 کنترل مقاوم H∞ ، حمیدرضا تقی راد، محمد فتحی و فرینا زمانی اسگویی، انتشارات دانشگاه صنعتی خواجه نصیرالدین طوسی، چاپ دوم، 1393. 2 Doyle, Francis, Tannenbaum, “Feedback Control Theory” ,Macmillan Publishing, 1990 . 3 Zhou K., with  J. Doyle, “Essentials of Robust Control”, Prentice Hall, 1998. 4 Skogestad S. and I. Postlethwaite “Multivariable Feedback Control”, John Wiley & Sons, 1996. 5 G.E. Dullerud and F. Paganini, “A course in Robust Control Theory: A convex Approach” , Springer Verlag, 1991. 6 P.R. Belanger, “Control Engineering, A modern approach”,  Saunders College, 1995. 7 “Robust toolbox”, user manual, version 3.1.1, Mathworks, 2006. 8 Selected papers and handouts.