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Boston University

1. Sadraddini, Sadra. Formal methods for resilient control.

Degree: PhD, Mechanical Engineering, 2018, Boston University

Many systems operate in uncertain, possibly adversarial environments, and their successful operation is contingent upon satisfying specific requirements, optimal performance, and ability to recover from unexpected situations. Examples are prevalent in many engineering disciplines such as transportation, robotics, energy, and biological systems. This thesis studies designing correct, resilient, and optimal controllers for discrete-time complex systems from elaborate, possibly vague, specifications. The first part of the contributions of this thesis is a framework for optimal control of non-deterministic hybrid systems from specifications described by signal temporal logic (STL), which can express a broad spectrum of interesting properties. The method is optimization-based and has several advantages over the existing techniques. When satisfying the specification is impossible, the degree of violation - characterized by STL quantitative semantics - is minimized. The computational limitations are discussed. The focus of second part is on specific types of systems and specifications for which controllers are synthesized efficiently. A class of monotone systems is introduced for which formal synthesis is scalable and almost complete. It is shown that hybrid macroscopic traffic models fall into this class. Novel techniques in modular verification and synthesis are employed for distributed optimal control, and their usefulness is shown for large-scale traffic management. Apart from monotone systems, a method is introduced for robust constrained control of networked linear systems with communication constraints. Case studies on longitudinal control of vehicular platoons are presented. The third part is about learning-based control with formal guarantees. Two approaches are studied. First, a formal perspective on adaptive control is provided in which the model is represented by a parametric transition system, and the specification is captured by an automaton. A correct-by-construction framework is developed such that the controller infers the actual parameters and plans accordingly for all possible future transitions and inferences. The second approach is based on hybrid model identification using input-output data. By assuming some limited knowledge of the range of system behaviors, theoretical performance guarantees are provided on implementing the controller designed for the identified model on the original unknown system.

Subjects/Keywords: Mechanical engineering; Control theory; Formal methods; Optimal control; Resilient control; Robust control

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sadraddini, S. (2018). Formal methods for resilient control. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/27455

Chicago Manual of Style (16th Edition):

Sadraddini, Sadra. “Formal methods for resilient control.” 2018. Doctoral Dissertation, Boston University. Accessed October 23, 2020. http://hdl.handle.net/2144/27455.

MLA Handbook (7th Edition):

Sadraddini, Sadra. “Formal methods for resilient control.” 2018. Web. 23 Oct 2020.

Vancouver:

Sadraddini S. Formal methods for resilient control. [Internet] [Doctoral dissertation]. Boston University; 2018. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/2144/27455.

Council of Science Editors:

Sadraddini S. Formal methods for resilient control. [Doctoral Dissertation]. Boston University; 2018. Available from: http://hdl.handle.net/2144/27455

2. Ananduta, Wayan Wicak. Non-centralized optimization-based control schemes for large-scale energy systems.

Degree: 2019, TDX

ABSTRAKSI (Indfonesian) Skema kendali yang tidak tersentralisasi untuk sistem berskala besar, seperti sistem aringan energi, lebih fleksibel, skalabel, dan reliabel dibandingkan dengan skema tersentralisasi. Keuntungan ini diperoleh dari terdapatnya satu set pengendali lokal, yang hanya bertanggung jawab terhadap satu partisi dari sistem tersebut, daripada jika hanya terdapat satu entitas yang mengendalikan seluruh sistem. Bahkan dalam beberapa sistem, penerapan struktur kendali yang tidak tersentralisasi menjadi keharusan karena adanya permasalahan intraktabilitas dari metode tersentralisasi. Oleh karena itu, disertasi ini bertujuan untuk melakukan studi pada metode kendali berdasarkan optimisasi dengan struktur yang tidak tersentralisasi untuk sistem energi berskala besar. Khususnya, disertasi ini memfokuskan pada proses komunikasi dan kooperasi pengendali‐pengendali lokal, yang merupakan bagian integral dalam skema yang dimaksud. Pada disertasi ini, sistem kontrol prediktif (model predictive control (MPC)) diterapkan untuk menyelesaikan optimisasi economic dispatch pada sistem energi berskala besar. Dalam arsitektur yang tidak tersentralisasi, pengendali‐pengendali lokal harus menyelesaikan permasalahan economic dispatch secara kooperatif. Permasalahan economic dispatch ini diformulasikan sebagai optimisasi yang konveks dan memiliki konstrain terkopling. Oleh karena itu, pendekatan Lagrange yang teraugmentasi diterapkan untuk mendekomposisi permasalahan optimisasi terkait. Pendekatan ini juga digunakan untuk merancang dua metode optimisasi terdistribusi, yang iteratif dan mengharuskan pengendali‐pengendali lokal bertukar informasi satu sama lain pada setiap iterasi. Sekuensi yang dihasilkan dari kedua metode tersebut akan terkonvergensi pada suatu solusi yang optimal apabila beberapa kondisi, yang meliputi bagaimana pengendali harus berkomunikasi dan berkooperasi, terpenuhi. Namun, pada praktiknya, proses komunikasi yang terjadi mungkin tidak selalu sempurna, dalam hal ini asumsi pada proses komunikasi yang dibutuhkan tidak terpenuhi. Pada kasus kegagalan jaringan komunikasi, metode terdistribusi yang dirancang mungkin tidak dapat menemukan solusinya. Oleh karena itu, suatu protokol untuk pertukaran informasi yang berdasarkan pada konsensus dirancang untuk mengatasi permasalahan ini. Selanjutnya, dua metode terdistribusi yang telah dirancang juga dikembangkan lebih jauh sehingga metode‐metode tersebut dapat bekerja pada jaringan komunikasi stokastik dengan proses yang asinkron, yaitu proses dimana tidak semua pengendali selalu melakukan pembaruan. Dalam hal ini, konvergensi dan laju konvergensi dari metode yang dirancang dipertunjukkan. Selain itu, implementasi dari metode terdistribusi pada sistem economic dispatch berbasis MPC juga dibahas. Diskusi pada bagian ini mencakup beberapa teknik yang dapat digunakan untuk mengurangi jumlah iterasi dan performa dari metode‐metode yang dirancang pada suatu studi numerik. Dengan pertimbangan bahwa metode‐metode yang disebut sebelumnya membutuhkan komunikasi yang… Advisors/Committee Members: [email protected] (authoremail), false (authoremailshow), Ocampo-Martínez, Carlos (director).

Subjects/Keywords: Model predictive control (MPC); Distributed optimization; System partitioning; Large‐scale systems; Economic dispatch; Time‐varying networks; Resilient methods; Control predictivo basado en modelos (MPC); Optimización distribuida; Particionado de sistemas; Àrees temàtiques de la UPC::Informàtica; 68

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ananduta, W. W. (2019). Non-centralized optimization-based control schemes for large-scale energy systems. (Thesis). TDX. Retrieved from http://hdl.handle.net/10803/669263

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ananduta, Wayan Wicak. “Non-centralized optimization-based control schemes for large-scale energy systems.” 2019. Thesis, TDX. Accessed October 23, 2020. http://hdl.handle.net/10803/669263.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ananduta, Wayan Wicak. “Non-centralized optimization-based control schemes for large-scale energy systems.” 2019. Web. 23 Oct 2020.

Vancouver:

Ananduta WW. Non-centralized optimization-based control schemes for large-scale energy systems. [Internet] [Thesis]. TDX; 2019. [cited 2020 Oct 23]. Available from: http://hdl.handle.net/10803/669263.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ananduta WW. Non-centralized optimization-based control schemes for large-scale energy systems. [Thesis]. TDX; 2019. Available from: http://hdl.handle.net/10803/669263

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.