pontryagin maximum principle proof

A widely used proof of the above formulation of the Pontryagin maximum principle, based on needle variations (i.e. Suppose aﬁnaltimeT and control-state pair (bu, bx) on [τ,T] give the minimum in the problem above; assume that ub is piecewise continuous. Features of the Bellman principle and the HJB equation I The Bellman principle is based on the "law of iterated conditional expectations". In this article we derive a strong version of the Pontryagin Maximum Principle for general nonlinear optimal control problems on time scales in nite dimension. Preliminaries. startxref There appear the PMP as a form of the Weiertrass necessary condition of convexity. 0000068249 00000 n 6, 117198, Moscow Russia. 0000010247 00000 n 0000009363 00000 n :�ؽ�0N��zY�8W.�'�٠W{�/E4Y`ڬ��Pւr��)Hm'M/o� %��CQ�[L�q��I�I�� `O�X��L'�g�"��q:ξ��DK��d`��nq��X�އ�]��%�� %�%��ʸ��>��iN��6#��$dԣ��Tk��ҁE��JQd��zS�;��8�C�{Y��Y]94AK�~� %PDF-1.5 %�� Note on Pontryagin maximum principle with running state constraints and smooth dynamics - Proof based on the Ekeland variational principle Lo c Bourdin To cite this version: Lo c Bourdin. The Maximum Principle of Pontryagin in control and in optimal control Andrew D. Lewis1 16/05/2006 Last updated: 23/05/2006 1Professor, Department of Mathematics and Statistics, Queen’s University, Kingston, ON K7L 3N6, Canada 0000001905 00000 n 0000077860 00000 n 0000068686 00000 n 0000080557 00000 n 0000064217 00000 n Theorem (Pontryagin Maximum Principle). %%EOF The Pontryagin Maximum Principle in the Wasserstein Space Beno^ t Bonnet, Francesco Rossi the date of receipt and acceptance should be inserted later Abstract We prove a Pontryagin Maximum Principle for optimal control problems in the space of probability measures, where the dynamics is given by a transport equation with non-local velocity. 0000080670 00000 n 0000002749 00000 n 0000061138 00000 n 0000054897 00000 n 0000082294 00000 n 0000071251 00000 n 0000067788 00000 n 0000017876 00000 n As a result, the new Pontryagin Maximum Principle (PMP in the following) is formulated in the language of subdiﬀerential calculus in … 0000026368 00000 n 0000035310 00000 n Pontryagin’s maximum principle For deterministic dynamics x˙ = f(x,u) we can compute extremal open-loop trajectories (i.e. 0000064605 00000 n x��YXTg�>�#�rT,g��&jcA��(**��t�"(��.�w��,� �K�M1F�јD��!�s��&��x؝��;�3+cL�12��]�i��OKq�L�M!�H� 7 �3m.l�?�C�>8�/#��lV9Z�� The work in Ref. 0000064021 00000 n The PMP is also known as Pontryagin's Maximum Principle. The maximum principle was proved by Pontryagin using the assumption that the controls involved were measurable and bounded functions of time. 0000002113 00000 n Introduction. 0000009846 00000 n Since the second half of the 20th century, Pontryagin's Maximum Principle has been widely discussed and used as a method to solve optimal control problems in medicine, robotics, finance, engineering, astronomy. time scales. 0000074543 00000 n 0000071489 00000 n A simple proof of the discrete time geometric Pontryagin maximum principle on smooth manifolds ☆ 1. 25 0 obj<>stream However, they give a strong maximum principle at right- scatteredpointswhichareleft-denseatthesametime. Note that here we don't use capitals in the middle of sentence. 13 Pontryagin’s Maximum Principle We explain Pontryagin’s maximum principle and give some examples of its use. 0000063736 00000 n See [7] for more historical remarks. 0000025093 00000 n 0000075899 00000 n of Diﬀerential Equations and Functional Analysis Peoples Friendship University of Russia Miklukho-Maklay str. 23 0 obj <> endobj 0000070317 00000 n The classic book by Pontryagin, Boltyanskii, Gamkrelidze, and Mishchenko (1962) gives a proof of the celebrated Pontryagin Maximum Principle (PMP) for control systems on R n. See also Boltyanskii (1971) and Lee and Markus (1967) for another proof of the PMP on R n. trailer It is a good reading. 0000061708 00000 n 0000073033 00000 n �t��o1}��}�=w8�Y�:{��:�|,��wx��M�X��c�N�D��:� ��7׮m��}w�v��wu�cf᪅a~;l��e�”vK��y��_��k�� +B}�7��0n��)oL�>c��^�9{N��̌d�0k��f��1K��hf-cü�Lc�0똥�tf,c�,cf0��rf&��Y��b�3��k�ƁYż�Ld61��"f63��̬f��9��f�2}�aL?�?3�� f0��a�ef�"�[Ƅ��j��V!�)W��5�br�t�� XE�� m��s>��Gu�Ѭ�G��z��^�{=��>�}��ۯ��U��7��:`ր�$�+�۠��V:?��`��郿�f�w�sͯ uzm��a{��[ŏć��!��ygE�M�A�g!>Ds�b�zl��@��T�:Z��3l�?�k��8� �(��Ns��"�� ub|I��uH|��`7pa*��9��*��՜�� n�� ZmZ;��d��d��N��~�Jj8�%w�9�dJ�)��׶3d�^�d��L.Ɖ}x]^Z�E��z��v��)��IV��d?�5�� R�?�� jt�E��1�Q��C��m�@DA�N�R� �>��'(�sk��]k)zw�Rי�e(G:I�8�g�\�!ݬm=x While the proof of Pontryagin (Ref. The initial application of this principle was to the maximization of the terminal speed of a rocket. However, as it was subsequently mostly used for minimization of a performance index it has here been referred to as the minimum principle. 0000036488 00000 n While the proof scheme is close to the classical ﬁnite-dimensional case, each step requires the deﬁnition of tools adapted to Wasserstein spaces. 0000054437 00000 n We establish a geometric Pontryagin maximum principle for discrete time optimal control problems on finite dimensional smooth manifolds under the following three types of constraints: a) constraints on the states pointwise in time, b) constraints on the control actions pointwise in time, c) constraints on the frequency spectrum of the optimal control trajectories. 0000062055 00000 n I It does not apply for dynamics of mean- led type: ��,�'�h�JQ�>��.0�D�?�-�=��?��6��#Vyf��7D�qqn��Y�ſ0�1��;�h��߰8(:N`��)�� M� endstream endobj 24 0 obj<> endobj 26 0 obj<>>> endobj 27 0 obj<> endobj 28 0 obj<> endobj 29 0 obj<> endobj 30 0 obj<>stream The nal time can be xed or not, and in the case of general boundary conditions we derive the corresponding transversality conditions. Many optimization problems in economic analysis, when cast as optimal control problems, are initial-value problems, not two-point boundary-value problems. 0000001496 00000 n First, in subsection 3.1 we make some preliminary comments explaining which obstructions may appear when dealing with That is why the thorough proof of the Maximum Principle given here gives insights into the geometric understanding of the abnormality. Pontryagin Maximum Principle for Optimal Control of Variational Inequalities @article{Bergounioux1999PontryaginMP, title={Pontryagin Maximum Principle for Optimal Control of Variational Inequalities}, author={M. Bergounioux and H. Zidani}, journal={Siam Journal on Control and Optimization}, year={1999}, volume={37}, pages={1273 … 0000001843 00000 n Part 1 of the presentation on "A contact covariant approach to optimal control (...)'' (Math. These hypotheses are unneces-sarily strong and are too strong for many applications. I think we need one article named after that and re-direct it to here. How the necessary conditions of Pontryagin’s Maximum Principle are satisﬁed determines the kind of extremals obtained, in particular, the abnormal ones. The celebrated Pontryagin maximum principle (PMP) is a central tool in optimal control theory that... 2. I Pontryagin’s maximum principle which yields the Hamiltonian system for "the derivative" of the value function. 0000026154 00000 n 0000035908 00000 n 0000025718 00000 n 13.1 Heuristic derivation Pontryagin’s maximum principle (PMP) states a necessary condition that must hold on an optimal trajectory. The approach is illustrated by use of the Pontryagin maximum principle which is then illuminated by reference to a constrained static optimization problem. Pontryagins maximum principle is used in optimal control theory to find the best possible control for taking a dynamical system from one state to another, especially in the presence of constraints for the state or input controls. However in many applications the optimal control is piecewise continuous and bounded. 0000002254 00000 n 0000077436 00000 n 0000036706 00000 n 0000078169 00000 n 0000061522 00000 n 0000046620 00000 n Pontryagin’s Maximum Principle is considered as an outstanding achievement of … 0000053099 00000 n Pontryagin’s principle asks to maximize H as a function of u 2 [0,2] at each ﬁxed time t.SinceH is linear in u, it follows that the maximum occurs at one of the endpoints u = 0 or u = 2, hence the control 2 Oleg Alexandrov 18:51, 15 November 2005 (UTC) BUT IT SHOULD BE MAXIMUM PRINCIPLE. 0000037042 00000 n 23 60 Cϝ��D��_�#�d��x��c��\��.�D�4"٤MbNј�ě�&]o�k-��{��VFARJKC6(�l&.`� v�20f_Җ@� e�c|�ܐ�h�Fⁿ4� Section 3 is devoted to the proof of Theorem 1. Attainable region analysis has been used to solve a large number of previously unsolved optimization problems. 0000052339 00000 n --anon Done, Pontryagin's maximum principle. Keywords: Lagrange multipliers, adjoint equations, dynamic programming, Pontryagin maximum principle, static constrained optimization, heuristic proof. In 2006, Lewis Ref. 0000017250 00000 n Let the admissible process , be optimal in problem – and let be a solution of conjugated problem - calculated on optimal process. A proof of the principle under 0000055234 00000 n Here, we focus on the proof and on the understanding of this Principle, using as much geometric ideas and geometric tools as possible. A Simple ‘Finite Approximations’ Proof of the Pontryagin Maximum Principle, Under Reduced Diﬀerentiability Hypotheses Aram V. Arutyunov Dept. <]>> These two theorems correspond to two different types of interactions: interactions in patch-structured popula- Our proof is based on Ekeland’s variational principle. 0000018287 00000 n 0000053939 00000 n 10 was devoted to a thorough study of general two-person zero-sum linear quadratic games in Hilbert spaces. 0000064960 00000 n 0 0000025192 00000 n In the PM proof, $\lambda_0$ is used to ensure the terminal cone points "upward". pontryagin maximum principle set-valued anal differentiability hypothesis simple finite approximation proof dynamic equation state trajectory pontryagin local minimizer finite approximation lojasiewicz refine-ment lagrange multiplier rule continuous dif-ferentiability traditional proof finite dimension early version local minimizer arbitrary value minimizing control state variable Pontryagin's maximum principle is used in optimal control theory to find the best possible control for taking a dynamical system from one state to another, especially in the presence of constraints for the state or input controls. It is a … It states that it is necessary for any optimal control along with the optimal state trajectory to solve the so-called Hamiltonian system, which is a two-point boundary value problem, plus a maximum condition of the Hamiltonian. ��L�*&��:��I ��@Cϊq��eG�hr��t�J�+�RR�iKR��+7(��h��[L��q�H�NJ��n��u��&E3Qt(��b��GK1�Y��1�/��k��*R Ǒ)d�I\p�j�A{�YaB�ޘ��(c�$�;L�0��G��)@~��돳N�u�^�5d�66r�A[�� 8F/%�SJ:j. DOI: 10.1137/S0363012997328087 Corpus ID: 34660122. Then for all the following equality is fulfilled: Corollary 4. [Other] University of 0000062340 00000 n 0000000016 00000 n The famous proof of the Pontryagin maximum principle for control problems on a finite horizon bases on the needle variation technique, as well as the separability concept of cones created by disturbances of the trajectories. Weierstrass and, eventually, the maximum principle of optimal control theory. 0000003139 00000 n 0000071023 00000 n � ��LU��tpU��6*�\{ҧ��6��"s��Ҡ��[LN��'.E3��h��h��=��M�XN:v6��D�F��(��#�B �|(��!��&au��a*��ȥ��0�h� �Zŧ�>58�'��Xs�I#��vk4Ia�PMp�*E��y�4�7��ꗦI�2N��X��mH�"E��)��S��>3O6b!6��R�/��]=��s��>�_8\~�c��X��?��T�誃7��?��%� �C�q9��t��%�֤��'_��. We establish a variety of results extending the well-known Pontryagin maximum principle of optimal control to discrete-time optimal control problems posed on smooth manifolds. We employ … 2 studied the linear quadratic optimal control problem with method of Pontryagin ’s maximum principle in autonomous systems. 0000052023 00000 n Theorem 3 (maximum principle). 1) is valid also for initial-value problems, it is desirable to present the potential practitioner with a simple proof specially constructed for initial-value problems. It is shown that not all problems that can be solved by attainable region analysis are readily formulated as maximum principle problems. Thispaperisorganizedasfollows.InSection2,weintroducesomepreliminarydef- The following result establishes the validity of Pontryagin’s maximum principle, sub-ject to the existence of a twice continuously di erentiable solution to the Hamilton-Jacobi-Bellman equation, with well-behaved minimizing actions. xref Pontryagin’s maximum principle follows from formula . local minima) by solving a boundary-value ODE problem with given x(0) and λ(T) = ∂ ∂x qT (x), where λ(t) is the gradient of the optimal cost-to-go function (called costate). 0000017377 00000 n Pontryagin and his collaborators managed to state and prove the Maximum Principle, which was published in Russian in 1961 and translated into English [28] the following year. This paper examines its relationship to Pontryagin's maximum principle and highlights the similarities and differences between the methods. The principle was first known as Pontryagin's maximum principle and its proof is historically based on maximizing the Hamiltonian. D' ÖEômßunBÌ_¯ÓMWE¢OQÆ&W46ü$^lv«U77¾ßÂ9íj7Ö=~éÇÑ_9©RqõIÏ×Ù)câÂdÉ-²ô§~¯ø?È\F[xyä¶p:¿Pr%¨â¦fSÆU«piL³¸Ô%óÍÃ8 ¶^Û¯Wûw*Ïã\¥ÐÉ -ÃmGÈâÜºÂ[Ê"Ë3?#%©dIª$ÁHRÅWÃÇ~`\ýiòGÛ2´Fl`ëÛùðÖG^³ø`$I#Xÿ¸ì°;|:2b M1Âßú yõ©ÎçÁ71¦AÈÖ. Pontryagin’s Maximum Principle. If ( x; u) is an optimal solution of the control problem (7)-(8), then there exists a function p solution of the adjoint equation (11) for which u(t) = arg max u2UH( x(t);u;p(t)); 0 t T: (Maximum Principle) This result says that u is not only an extremal for the Hamiltonian H. It is in fact a maximum. Richard B. Vinter Dept. In that paper appears a derivation of the PMP (Pontryagin Maximum Principle) from the calculus of variation. 0000048531 00000 n