## Dr. Shyam KamalProject Assistant ProfessorDepartment of Systems Design and Informatics Kyushu Institute of Technology 680-4 Kawazu, Iizuka Fukuoka 820-8502, Japan Room No. W 417 Email: kamal@ces.kyutech.ac.jp
valid until July 29, 2016 |

Mathematical Biology: An Introduction: Lecture Slides

**Tips:**Interested in BIOLOGY? BIOTECHNOLOGY? Or MEDICINE? Please join us to learn more!**Date**: Wednesday, July 27, 2016; 18:00-19:00 Room GCL

Fractional Order Systems: Lecture Slides

**A Brief Overview:**In the last two decades fractional differential equations have been used more frequently in physics, signal processing, fluid mechanics, viscoelasticity, mathematical biology, electro chemistry and many others. It opens a new and more realistic way to capture memory dependent phenomena and irregularities inside the systems by using more sophisticated mathematical analysis. The goal of this lecture is to discuss how to define fractional order derivative and integral and its application?**References**:(1). B. Bandyopadhyay, Shyam Kamal, ''Stabilization and control of fractional order systems: A sliding mode approach.'' Lecture Notes in Electrical Engineering, Springer-Verlag (2015). (2). I. Podlubny "Fractional differential equations." Elsevier. ISBN 9780125588409.(1999). (3). I. Podlubny "Geometric and physical interpretation of fractional integration and fractional differentiation." arXiv:math/0110241, 2001. (4). Y. Li, Y. Q. Chen and I. Podlubny, "Mittag-Leffler stability of fractional order nonlinear systems." Automatica, 45(8): 965-969, 2009. (5) Image courtesy: Internet**Date**: Tuesday, July 5, 2016; 18:00-19:00 Room GCL

DNA Computers: Lecture Slides

**A Brief Overview:**Millions of natural super-computers exist inside living organism including our body. DNA (deoxyribonucleic acid) molecule, the material our genes are made of, have the potential to perform calculations many times faster than the world's most powerful human build computers. The goal of this lecture is to discuss how the DNA molecule can act as elementary logic gates analogous to the silicon based gates of ordinary computers?**References**:(1). Martyn Amos, ''Theoretical and Experimental DNA Computation'' Springer-Verlag Berlin Heidelberg (2005). (2). Gearheart, Christy M., Eric C. Rouchka, and Benjamin Arazi. "DNA-Based Active Logic Design and Its Implications." Journal of Emerging Trends in Computing and Information Sciences 3, no. 5 (2012). (3). Shapiro, Ehud, and Tom Ran. "DNA computing: Molecules reach consensus." Nature nanotechnology 8, no. 10 (2013): 703-705. (4) Image courtesy: Internet**Date**: Monday, June 13, 2016; 18:00-19:00 Room GCL

Mathematical Modeling of Diabetes: Lecture Slides

**A Brief Overview:**The goal of this lecture is to provide an overview of the mathematical techniques and concepts to the study of biological phenomena.**References**:(1). Braun, Martin, and Martin Golubitsky. Differential equations and their applications. Vol. 4. New York: Springer, 1983. (2). Makroglou, Athena, Jiaxu Li, and Yang Kuang. "Mathematical models and software tools for the glucose-insulin regulatory system and diabetes: an overview." Applied numerical mathematics 56, no. 3 (2006): 559-573. (3). Lozada, Samantha. "Glucose Regulation in Diabetes." (2012). (4) Image courtesy: Internet**Date**: Friday, May 20, 2016; 18:00-19:00 Room GCL

How Physics Limits Intelligence?: Lecture Slides

**A Brief Overview:**The goal of this lecture is to discuss how the laws of physics may well prevent the human brain from evolving into an even more powerful thinking machine (inspired by Prof. Douglas Fox work ''The Limits of Intelligence'')?**Date**: Wednesday, April 27, 2016; 18:00-19:00 Room GCL

How Different is the Machine from the Brain?: Lecture Slides

**A Brief Overview:**The goal of this lecture is to share control mechanism that is different in the brain and in the computer (inspired by Prof. Rodolphe Sepulchre talk ''Do brains compute ?'').**Date**: Wednesday, Feb. 24, 2016; 17:00-18:00 Room GCL

Mathematical Modeling of Cancer Growth: Lecture Slides

**A Brief Overview**: The goal of this lecture is to provide an overview of the mathematical techniques and concepts to the study of biological phenomena.**Date**: Thursday, Dec. 3, 2015; 18:00-19:00 Room GCL

Vedic Mathematics: As a part of India's Timeless Culture

**A Brief Overview:**The word Vedic is used as an adjective in connection with the Vedas. There are four Vedas: Rigveda, Samaveda, Yajurveda and Atharvaveda in Indian culture. Each of these deals with a specific set of subjects. Out of these Vedas, the Atharvaveda dealt with subjects of architecture, engineering and general mathematics. Vedic Mathematics is the collective name given to a set of sixteen mathematical formulae discovered by Jagadguru Swami Sri Bharati Krishna Tirthaji Maharaj. Each formula deals with a different branch of Mathematics. These sixteen formulae can be used to solve problems ranging from arithmetic to algebra to geometry to conics to calculus.**Goal:**In this lecture I am going to recall these formula using some appropriate examples.**Date :**Friday, Jan. 22, 2016, 18.00-19.00, Room GCL; Thursday, Dec. 1, 2015, 18.00-19.00, Room GCL, Thursday, June 25; Time: 18.00-19.00; Monday, May 25, Tuesday, April 28, 2015; Place: Global Communication Lounge (GCL)

Fundamentals of Lyapunov Theory: Part-2

**A Brief Overview:**Given a control system, the first and most important question about its various properties is whether it is stable, because an unstable control system is typically useless and potentially dangerous. Qualitatively, a system is described as stable if starting the system somewhere near its desired operating point implies that it will stay around the point ever after. The most useful and general approach for studying the stability of nonlinear control systems is the theory introduced by Lyapunov.**Date :**Wednesday, April 13, 2016, Time: 13:00-14:30; Room No: W406.

Fundamentals of Lyapunov Theory: Part-1 : Seminar Flyer

**A Brief Overview:**Given a control system, the first and most important question about its various properties is whether it is stable, because an unstable control system is typically useless and potentially dangerous. Qualitatively, a system is described as stable if starting the system somewhere near its desired operating point implies that it will stay around the point ever after. The most useful and general approach for studying the stability of nonlinear control systems is the theory introduced by Lyapunov.**Date :**Wednesday, March 30, 2016, Time: 13:00-14:30; Room No: W406.

Nonlinear Control: An Introduction

**A Brief Overview:**Physical systems are inherently nonlinear. Thus, all control systems are nonlinear to a certain extent. Nonlinear control systems can be described by nonlinear differential equations. However, if the operating range of a control system is smal, and if the involved nonlinearities are smooth, then the control system may be resonably approximated by a linearized system, whose dynamics is described by a set of linear differential equations. The behavior of nonlinear systems, however, is much more complex. Due to the lack of linearity and of the associated superposition property, nonlinear systems respond to external inputs quite differently from linear systems.**Date :**Wednesday, March 2, 2016, Time: 13:00-14:30; Room No: W406.

Exact Feedback Linearization : Seminar Flyer

**A Brief Overview:**Feedback linearization is a one of popular approaches to nonlinear control design. The central idea is to transform nonlinear systems dynamics into linear dynamics, so that linear control techniques can be applied. This differs from conventional (Jacobian) linearization, because feedback linearization is achieved exactly by state transformation and feedback, rather than by linear approximations of the dynamics.**Date :**Thursday, July 30, 2015, Time: 16:20-17:50; Room No: W507.

Backstepping Control Design : Seminar Flyer

**A Brief Overview:**In control theory, backstepping is a popular technique for designing stabilizing controllers for nonlinear dynamical systems. In this methodology, the designer can start the design process at a stable subsystem and then recursively design a new controller based on the Lyapunov theory to stabilize the whole system.**Date :**Thursday, July 2, 2015, Time: 16:20-17:50; Room No: W507.

Fundamentals of Sliding Mode Control and Its Applications: Seminar Flyer ; SMC Introduction ; Some Basic Concepts

**A Brief Overview:**In sliding mode control, variable structure control systems are designed to drive and then constrain the system states to lie in a predefined manifold. During sliding mode, the system dynamics is governed by the chosen manifold which results in a well celebrated invariant property towards certain class of disturbances and model mismatches and thus clearly makes this methodology an appropriate candidate for robust control.**Date :**Tuesday, Feb 24, 2015, Time: 14.40-16.10; Room No: W507; Wednesday, March 4, 11, 18, 2015, Time: 16.20-17.50; Room No: W507.

Mathematics and its Application to Control Theory (18 Feb. 2015): Lecture Slides

**Contents:**Motivating student towards control theory based on basic knowledge of mathematics.

2016

**Period :**From March 2016 to June 2016.