Download Adaptive Dynamic Programming for Control: Algorithms and by Huaguang Zhang, Derong Liu, Yanhong Luo, Ding Wang PDF

By Huaguang Zhang, Derong Liu, Yanhong Luo, Ding Wang

There are many equipment of reliable controller layout for nonlinear platforms. In trying to transcend the minimal requirement of balance, Adaptive Dynamic Programming in Discrete Time techniques the tough subject of optimum keep an eye on for nonlinear platforms utilizing the instruments of adaptive dynamic programming (ADP). the variety of platforms handled is huge; affine, switched, singularly perturbed and time-delay nonlinear structures are mentioned as are the makes use of of neural networks and strategies of price and coverage generation. The textual content good points 3 major points of ADP during which the tools proposed for stabilization and for monitoring and video games enjoy the incorporation of optimum regulate tools:
• infinite-horizon keep an eye on for which the trouble of fixing partial differential Hamilton–Jacobi–Bellman equations at once is triumph over, and evidence only if the iterative price functionality updating series converges to the infimum of the entire price capabilities acquired by way of admissible keep an eye on legislation sequences;
• finite-horizon keep an eye on, applied in discrete-time nonlinear platforms displaying the reader tips on how to receive suboptimal regulate strategies inside a hard and fast variety of keep watch over steps and with effects extra simply utilized in genuine structures than these frequently won from infinite-horizon regulate;
• nonlinear video games for which a couple of combined optimum rules are derived for fixing video games either while the saddle element doesn't exist, and, whilst it does, fending off the life stipulations of the saddle aspect.
Non-zero-sum video games are studied within the context of a unmarried community scheme within which regulations are bought making certain procedure balance and minimizing the person functionality functionality yielding a Nash equilibrium.
In order to make the assurance appropriate for the scholar in addition to for the professional reader, Adaptive Dynamic Programming in Discrete Time:
• establishes the basic idea concerned in actual fact with each one bankruptcy dedicated to a essentially identifiable keep an eye on paradigm;
• demonstrates convergence proofs of the ADP algorithms to deepen realizing of the derivation of balance and convergence with the iterative computational equipment used; and
• indicates how ADP equipment might be placed to exploit either in simulation and in actual purposes.
This textual content should be of substantial curiosity to researchers attracted to optimum keep watch over and its purposes in operations learn, utilized arithmetic computational intelligence and engineering. Graduate scholars operating up to the mark and operations study also will locate the information offered the following to be a resource of robust equipment for furthering their study.

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Parisini T, Zoppoli R (1998) Neural approximations for infinite-horizon optimal control of nonlinear stochastic systems. IEEE Trans Neural Netw 9(6):1388–1408 74. Park JW, Harley RG, Venayagamoorthy GK (2003) Adaptive-critic-based optimal neurocontrol for synchronous generators in a power system using MLP/RBF neural networks. IEEE Trans Ind Appl 39:1529–1540 75. Powell WB (2011) Approximate dynamic programming: solving the curses of dimensionality, 2nd edn. Wiley, Princeton 76. Prokhorov DV, Wunsch DC (1997) Adaptive critic designs.

Birkhäser, Boston, pp 379–394 70. Necoara I, Kerrigan EC, Schutter BD, Boom T (2007) Finite-horizon min–max control of max-plus-linear systems. IEEE Trans Autom Control 52(6):1088–1093 71. Owen G (1982) Game theory. Academic Press, New York 72. Padhi R, Unnikrishnan N, Wang X, Balakrishnan SN (2006) A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems. Neural Netw 19(10):1648–1660 73. Parisini T, Zoppoli R (1998) Neural approximations for infinite-horizon optimal control of nonlinear stochastic systems.

Owen G (1982) Game theory. Academic Press, New York 72. Padhi R, Unnikrishnan N, Wang X, Balakrishnan SN (2006) A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems. Neural Netw 19(10):1648–1660 73. Parisini T, Zoppoli R (1998) Neural approximations for infinite-horizon optimal control of nonlinear stochastic systems. IEEE Trans Neural Netw 9(6):1388–1408 74. Park JW, Harley RG, Venayagamoorthy GK (2003) Adaptive-critic-based optimal neurocontrol for synchronous generators in a power system using MLP/RBF neural networks.

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