References

The content of this lecture is standard and is discussed by a number of books and online resources. When preparing our own material, we took much inspiration from [1]. In particular, we are trying to follow Kirk’s way of relating the optimal control problem to the calculus of variations. Although not available online, the printed book is fairly afordable. We also used [2], in particular the chapters 3 (application of calculus of variations to general problem of optimal control) and chapter 4 (Pontryagin’s principle). Online version of the book is freely available.

Other recommendable classics are [3] and [4]. The popular [5] is a bit less detailed when it comes to the topics of this particular chapter/lecture.

We did not discuss the proof of Pontryagin’s principle and we do not even command the students to go through the proof in the book. Admittedly, it is rather challenging. But if you are courageous, have a look at [2]. Understanding the very statement of the theorem, its roots in calculus of variations, and how it removes the deficiencies of the calculus of variations will suffice for our purposes.

The transition from the calculus of variations to the optimal control, especially when it comes to the definition of Hamiltonian, is somewhat tricky. Unfortunately, it is not discussed satisfactorily in the literature. Even [2] leaves it as an (unsolved) exercise (3.5 and 3.6) to the student. Other major textbooks avoid the topic altogether. We find an exceptionally insightful treatment in the paper [6], in particular in the section “The first fork in the road: Hamilton” on page 39.

The time-optimal control for linear systems, in particular bang-bang control for a double integrator is described in section 4.4.1 and 4.4.2 in [2]. But the material is quite standard and can be found in many other books and lecture notes.

What is often not emphasized in textbooks, however, is the fact that without any modifications, the bang bang control is rather troublesome from an implementation viewpoint – it leads to chattering. A dedicated research thread has evolved, driven by the needs of hard disk drive industry, which is called (a)proximate time-optimal control (PTOS). Many dozens of papers can be found with this keyword in the title. For instance, [7], and [8].

Among numerous other resources available freely online, the lecture notes [9, Sec. 12.3], and [10] can also be recommended.

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References

[1]
D. E. Kirk, Optimal Control Theory: An Introduction, Reprint of the 1970 edition. Dover Publications, 2004.
[2]
D. Liberzon, Calculus of Variations and Optimal Control Theory: A Concise Introduction. Princeton University Press, 2011. Available: http://liberzon.csl.illinois.edu/teaching/cvoc/cvoc.html
[3]
A. E. Bryson Jr. and Y.-C. Ho, Applied Optimal Control: Optimization, Estimation and Control, Revised edition. CRC Press, 1975.
[4]
M. Athans and P. L. Falb, Optimal Control: An Introduction to the Theory and Its Applications, Reprint of the 1966 edition. Dover Publications, 2006.
[5]
F. L. Lewis, D. Vrabie, and V. L. Syrmo, Optimal Control, 3rd ed. John Wiley & Sons, 2012. Accessed: Mar. 09, 2022. [Online]. Available: https://lewisgroup.uta.edu/FL%20books/Lewis%20optimal%20control%203rd%20edition%202012.pdf
[6]
H. J. Sussmann and J. C. Willems, “300 years of optimal control: From the brachystochrone to the maximum principle,” IEEE Control Systems, vol. 17, no. 3, pp. 32–44, Jun. 1997, doi: 10.1109/37.588098.
[7]
M. L. Workman, R. L. Kosut, and G. F. Franklin, “Adaptive Proximate Time-Optimal Servomechanisms: Continuous Time Case,” in 1987 American Control Conference, Minneapolis, MN, Jun. 1987, pp. 589–594. doi: 10.23919/ACC.1987.4789386.
[8]
L. Y. Pao and G. F. Franklin, “Proximate time-optimal control of third-order servomechanisms,” IEEE Transactions on Automatic Control, vol. 38, no. 4, pp. 560–580, Apr. 1993, doi: 10.1109/9.250524.
[9]
S. Gros and M. Diehl, “Numerical Optimal Control (Draft).” Systems Control; Optimization Laboratory IMTEK, Faculty of Engineering, University of Freiburg, Apr. 2022. Available: https://www.syscop.de/files/2020ss/NOC/book-NOCSE.pdf
[10]
L. C. Evans, “An Introduction to Mathematical Optimal Control Theory,” Department of Mathematics, University of California, Berkeley. Available: https://math.berkeley.edu/~evans/control.course.pdf