LEADER 03144nam 2200433 450 001 9910795570303321 005 20230803211623.0 010 $a3-8325-9951-7 035 $a(CKB)4340000000242777 035 $a(MiAaPQ)EBC5219648 035 $a(Au-PeEL)EBL5219648 035 $a(CaPaEBR)ebr11539496 035 $a(OCoLC)1021809345 035 $a58a1c68b-ecd0-4aea-bfbc-3edeb0dd2d03 035 $a(EXLCZ)994340000000242777 100 $a20180521d2014 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDistributed and economic model predictive control $ebeyond setpoint stabilization /$fMatthias A. Mu?ller 210 1$aBerlin :$cLogos Verlag,$d[2014] 210 4$dİ2014 215 $a1 online resource (154 pages) 300 $aPublicationDate: 20141023 311 $a3-8325-3821-6 330 $aLong description: In this thesis, we study model predictive control (MPC) schemes for control tasks which go beyond the classical objective of setpoint stabilization. In particular, we consider two classes of such control problems, namely distributed MPC for cooperative control in networks of multiple interconnected systems, and economic MPC, where the main focus is on the optimization of some general performance criterion which is possibly related to the economics of a system. The contributions of this thesis are to analyze various systems theoretic properties occurring in these type of control problems, and to develop distributed and economic MPC schemes with certain desired (closed-loop) guarantees. To be more precise, in the field of distributed MPC we propose different algorithms which are suitable for general cooperative control tasks in networks of interacting systems. We show that the developed distributed MPC frameworks are such that the desired cooperative goal is achieved, while coupling constraints between the systems are satisfied. Furthermore, we discuss implementation and scalability issues for the derived algorithms, as well as the necessary communication requirements between the systems. In the field of economic MPC, the contributions of this thesis are threefold. Firstly, we analyze a crucial dissipativity condition, in particular its necessity for optimal steady-state operation of a system and its robustness with respect to parameter changes. Secondly, we develop economic MPC schemes which also take average constraints into account. Thirdly, we propose an economic MPC framework with self-tuning terminal cost and a generalized terminal constraint, and we show how self-tuning update rules for the terminal weight can be derived such that desirable closed-loop performance bounds can be established. 606 $aStability$xMathematical models 615 0$aStability$xMathematical models. 676 $a515.392 700 $aMu?ller$b Matthias A.$0236027 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910795570303321 996 $aDistributed and economic model predictive control$93706715 997 $aUNINA