Adaptive Dynamic Programming with Applications in Optimal by Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li

By Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li

This publication covers the latest advancements in adaptive dynamic programming (ADP). The textual content starts off with an intensive historical past evaluation of ADP to ensure that readers are sufficiently acquainted with the basics. within the middle of the booklet, the authors tackle first discrete- after which continuous-time structures. insurance of discrete-time structures starts off with a extra basic type of worth generation to illustrate its convergence, optimality, and balance with entire and thorough theoretical research. A extra practical type of price new release is studied the place price functionality approximations are assumed to have finite blunders. Adaptive Dynamic Programming additionally information one other street of the ADP technique: coverage generation. either uncomplicated and generalized different types of policy-iteration-based ADP are studied with entire and thorough theoretical research when it comes to convergence, optimality, balance, and mistake bounds. between continuous-time structures, the regulate of affine and nonaffine nonlinear structures is studied utilizing the ADP strategy that's then prolonged to different branches of regulate idea together with decentralized keep watch over, powerful and assured price keep an eye on, and online game concept. within the final a part of the booklet the real-world importance of ADP idea is gifted, concentrating on 3 program examples built from the authors’ work:

• renewable strength scheduling for clever energy grids;• coal gasification procedures; and• water–gas shift reactions.
Researchers learning clever keep watch over equipment and practitioners seeking to follow them within the chemical-process and power-supply industries will locate a lot to curiosity them during this thorough remedy of a complicated method of control.

Show description

Read Online or Download Adaptive Dynamic Programming with Applications in Optimal Control PDF

Similar robotics & automation books

Atomic Force Microscopy Based Nanorobotics: Modelling, Simulation, Setup Building and Experiments

The atomic strength microscope (AFM) has been effectively used to accomplish nanorobotic manipulation operations on nanoscale entities akin to debris, nanotubes, nanowires, nanocrystals, and DNA in view that Nineties. there were many development on modeling, imaging, teleoperated or automatic regulate, human-machine interfacing, instrumentation, and purposes of AFM established nanorobotic manipulation structures in literature.

Robot Hands and Multi-Fingered Haptic Interfaces: Fundamentals and Applications

Robotic fingers and Multi-Fingered Haptic Interfaces is a monograph concentrating on the comparability of human palms with robotic fingers, the basics at the back of designing and growing the latter, and robotics' newest developments in haptic know-how. This paintings discusses the layout of robotic palms; touch types at greedy; kinematic versions of constraint; dynamic types of the multi-fingered hand; the steadiness theorem of non-linear keep watch over platforms; robotic hand keep an eye on; layout and keep watch over of multi-fingered haptic interfaces; software platforms utilizing multi-fingered haptic interfaces; and telecontrol of robotic arms utilizing a multi-fingered haptic interface.

Basic Process Engineering Control

This ebook offers equipment, difficulties and instruments utilized in approach keep watch over engineering. It discusses: procedure wisdom, sensor procedure expertise, actuators, verbal exchange know-how and logistics in addition to layout and building of regulate platforms and their operation. the information is going past the conventional technique engineering box through utilising an analogous ideas to biomedical techniques, power creation and administration of environmental matters.

Additional resources for Adaptive Dynamic Programming with Applications in Optimal Control

Sample text

13) and policy improvement πi+1 (s) = arg max{r(s, a, s ) + γ Vi (s )}. , when |Vi+1 (s) − Vi (s)| ≤ ε, ∀s, to obtain V ∗ (s) ≈ Vi+1 (s), where ε is a small positive number. Then, the optimal policy is approximated as π ∗ (s) ≈ πi+1 (s). The temporal difference (TD) method [97] is developed to estimate the value function for a given policy. 15) or Vi+1 (st ) = Vi (st ) + α rt+1 + γ Vi (st+1 ) − Vi (st ) , i = 0, 1, 2, . . 16) where α > 0 is a step size. This algorithm is also called TD(0) (compared to TD(λ) to be introduced later).

According to Bellman, the optimal cost from time k on is equal to J ∗ (xk ) = min{U(xk , uk ) + γ J ∗ (xk+1 )} = min{U(xk , uk ) + γ J ∗ (F(xk , uk ))}. , uk∗ = arg min{U(xk , uk ) + γ J ∗ (xk+1 )}. 4) is the principle of optimality for discrete-time systems. Its importance lies in the fact that it allows one to optimize over only one control vector at a time by working backward in time. Dynamic programming is a very useful tool in solving optimization and optimal control problems. In particular, it can easily be applied to nonlinear systems with or without constraints on the control and state variables.

Integral reinforcement learning methods are used to learn the solution to the two-player zero-sum games online without knowing the system drift dynamics. The book by Zhang, Liu, Luo, and Wang [139] studies the control algorithms and stability issues of adaptive dynamic programming (ADP). ADP is a biologically inspired and computational method proposed to solve optimization and optimal control problems. It is an efficient scheme to learn to approximate optimal strategy of action in the general case.

Download PDF sample

Rated 4.10 of 5 – based on 17 votes