Receding Horizon Control: Model Predictive Control for State by Wook Hyun Kwon, Soo Hee Han

By Wook Hyun Kwon, Soo Hee Han

Easy-to-follow studying constitution makes absorption of complex fabric as pain-free as attainable Introduces whole theories for balance and value monotonicity for restricted and non-linear platforms in addition to for linear structures In co-ordination with MATLAB® records on hand from, routines and examples supply the scholar extra perform within the predictive keep watch over and filtering strategies offered

Show description

Read Online or Download Receding Horizon Control: Model Predictive Control for State Models (Advanced Textbooks in Control and Signal Processing) PDF

Best system theory books

Synergetics: an introduction

This publication is an often-requested reprint of 2 vintage texts by way of H. Haken: "Synergetics. An advent" and "Advanced Synergetics". Synergetics, an interdisciplinary learn software initiated through H. Haken in 1969, bargains with the systematic and methodological method of the speedily transforming into box of complexity.

Robust Design: A Repertoire of Biological, Ecological, and Engineering Case Studies (Santa Fe Institute Studies on the Sciences of Complexity)

Powerful layout brings jointly sixteen chapters through an eminent staff of authors in quite a lot of fields proposing elements of robustness in organic, ecological, and computational platforms. The volme is the 1st to handle robustness in organic, ecological, and computational structures. it's an outgrowth of a brand new examine software on robustness on the Sante Fe Institute based via the David and Lucile Packard origin.

Self-organized biological dynamics & nonlinear control

The turning out to be effect of nonlinear technological know-how on biology and medication is essentially altering our view of residing organisms and ailment techniques. This booklet introduces the applying to biomedicine of a wide diversity of ideas from nonlinear dynamics, corresponding to self-organization, complexity, coherence, stochastic resonance, fractals, and chaos.

Semi-Autonomous Networks: Effective Control of Networked Systems through Protocols, Design, and Modeling

This thesis analyzes and explores the layout of managed networked dynamic structures - dubbed semi-autonomous networks. The paintings methods the matter of potent keep an eye on of semi-autonomous networks from 3 fronts: protocols that are run on person brokers within the community; the community interconnection topology layout; and effective modeling of those frequently large-scale networks.

Extra resources for Receding Horizon Control: Model Predictive Control for State Models (Advanced Textbooks in Control and Signal Processing)

Sample text

142) respectively. The derivation for hi,if is left as an exercise. 149) is nonnegative. To conclude, the solution of the HTC problem can be reduced to finding Mi,if and gi,if for i = i0 , · · · , if − 1. 141). 143). e. 150) look like an LQ solution. 147). 151) It is noted that Mi,if is obtained from Ki,if of the LQ control by replacing BR−1 B T by Π. 156) with Here, Qf must be nonsingular. 157) which is required for the existence of the saddle-point. 136) may not be satisfied. That is why the terminal equality constraint for case of the RH H∞ control does not make sense.

167). We are now in a position to find out the mean of p(xi |Yi ). 168) to zero. 175) Pi+1|i can be obtained recursively from the error dynamic equations. 176) where x ˜i|i = x ˆi|i − xi and x ˜i|i−1 = x ˆi|i−1 − xi . 178) 52 2 Optimal Controls on Finite and Infinite Horizons: A Review The initial values x ˆi0 |i0 −1 and Pi0 |i0 −1 are given by E[xi0 ] and E[(ˆ xi0 − xi0 − xi0 )T ], which are a priori knowledge. 180) with the given initial condition Pi0 . 179) is used instead of Pi|i−1 . Throughout this book, we use the predicted form x ˆi|i−1 instead of filtered ˆi|i−1 will be denoted by x ˆi if necessary.

50). e. 62) Now, we have only to find the boundary value of gi,if and wi,if . J ∗ (xif ) should be equal to the performance criterion for the final state. Thus, wif ,if and gif ,if r r should be chosen as wif ,if = xrT if Qf xif and gif ,if = −Qf xif so that we have J ∗ (xif ) = xTif Kif ,if xif + 2xTif gif ,if + wif ,if r = xTif Qf xif − 2xTif Qf xrif + xrT if Qf xif = (xif − xrif )T Qf (xif − xrif ) This completes the proof. 2 will be utilized only for zero reference signals in subsequent sections.

Download PDF sample

Rated 4.41 of 5 – based on 21 votes