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020 _a9789811972911
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100 1 _aWang, Ding.
_eauthor.
_0(orcid)0000-0002-7149-5712
_1https://orcid.org/0000-0002-7149-5712
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aAdvanced Optimal Control and Applications Involving Critic Intelligence
_h[electronic resource] /
_cby Ding Wang, Mingming Ha, Mingming Zhao.
250 _a1st ed. 2023.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2023.
300 _aXIV, 274 p. 116 illus., 115 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Control and Learning Systems,
_x2662-5466 ;
_v6
500 _aAcceso multiusuario
505 0 _aA Survey of Robust Adaptive Critic Control Design -- Robust Optimal Control of Nonlinear Systems with Matched Uncertainties -- Observer-Based Online Adaptive Regulation for a Class of Uncertain Nonlinear Systems -- Adaptive Tracking Control of Nonlinear Systems Subject to Matched Uncertainties -- Event-Triggered Robust Stabilization Incorporating an Adaptive Critic Mechanism -- An Improved Adaptive Optimal Regulation Framework with Robust Control Synthesis -- Robust Stabilization and Trajectory Tracking of General Uncertain Nonlinear Systems -- Event-Triggered Nonlinear H∞ Control Design via an Improved Critic Learning Strategy -- Intelligent Critic Control with Disturbance Attenuation for a Micro-Grid System -- Sliding Mode Design for Load Frequency Control with Power System Applications.
520 _aThis book intends to report new optimal control results with critic intelligence for complex discrete-time systems, which covers the novel control theory, advanced control methods, and typical applications for wastewater treatment systems. Therein, combining with artificial intelligence techniques, such as neural networks and reinforcement learning, the novel intelligent critic control theory as well as a series of advanced optimal regulation and trajectory tracking strategies are established for discrete-time nonlinear systems, followed by application verifications to complex wastewater treatment processes. Consequently, developing such kind of critic intelligence approaches is of great significance for nonlinear optimization and wastewater recycling. The book is likely to be of interest to researchers and practitioners as well as graduate students in automation, computer science, and process industry who wish to learn core principles, methods, algorithms, and applications in the field of intelligent optimal control. It is beneficial to promote the development of intelligent optimal control approaches and the construction of high-level intelligent systems.
541 _fUABC ;
_cPerpetuidad
650 0 _aControl engineering.
650 0 _aRobotics.
650 0 _aAutomation.
650 0 _aMachine learning.
650 1 4 _aControl, Robotics, Automation.
650 2 4 _aMachine Learning.
650 2 4 _aAutomation.
700 1 _aHa, Mingming.
_eauthor.
_0(orcid)0000-0002-2901-9608
_1https://orcid.org/0000-0002-2901-9608
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aZhao, Mingming.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811972904
776 0 8 _iPrinted edition:
_z9789811972928
776 0 8 _iPrinted edition:
_z9789811972935
830 0 _aIntelligent Control and Learning Systems,
_x2662-5466 ;
_v6
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-19-7291-1
912 _aZDB-2-INR
912 _aZDB-2-SXIT
942 _cLIBRO_ELEC
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