Set-Theoretic Approaches to the Aperiodic Control of Linear Systems.

Αποθηκεύτηκε σε:

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας:	Brunner, Florian D.
Μορφή:	Ηλ. βιβλίο
Γλώσσα:	English
Έκδοση:	Berlin : Logos Verlag Berlin, 2017.
Θέματα:	Information theory-Methodology. Information theory > Methodology
Διαθέσιμο Online:	Click for online access

Πίνακας περιεχομένων:

Intro
1 Introduction
2 Background and Preliminaries
2.1 Dynamical systems and stability
2.2 Discrete-time linear systems
2.3 Event-triggered and self-triggered control
2.4 Set-valued estimation
2.4.1 Set-valued estimates from linear estimator dynamics
2.4.2 Set-valued moving-horizon estimation
2.5 Model predictive control
3 Linear Systems Perturbed by Bounded Disturbances
3.1 Preliminaries
3.2 Lyapunov-based approach
3.2.1 Theoretical results
3.2.2 Output feedback
3.2.3 Computational aspects
3.2.4 Numerical examples
3.3 Set-based approach
3.3.1 State feedback
3.3.2 Analysis of given aperiodic schemes
3.3.3 Output feedback
3.3.4 Computational aspects
3.3.5 Numerical examples
3.4 Summary
4 Stochastic Threshold Design in Event-triggered Control
4.1 Threshold design for arbitrarily distributed disturbances
4.1.1 Probability assigment
4.1.2 Expected value assignment
4.2 Stochastic thresholds for Gau{u02C7}ian noise disturbances
4.2.1 State-Feedback
4.2.2 Output feedback
4.3 Summary
5 Aperiodic Model Predictive Control of Constrained Linear Systems
5.1 Lyapunov-based approach
5.1.1 A Lyapunov function for robust MPC
5.1.2 Relaxing the rate of decrease
5.1.3 Aperiodic control algorithms
5.1.4 Implementation
5.2 Mixed set{Lyapunov approach
5.2.1 Feasibility by value function decrease, stability by set-membership condition
5.2.2 Aperiodic control algorithms
5.2.3 Implementation
5.3 Purely set-based approach
5.3.1 Feasibility from set-membership conditions
5.3.2 Aperiodic control algorithms
5.3.3 Implementation
5.4 Threshold-based event-triggered MPC: analysis and stochastic design
5.5 Numerical example
5.6 Summary
6 Output-feedback Event-triggered Model Predictive Control.
6.1 Set-valued moving horizon estimation in model predictive control
6.1.1 General results
6.1.2 Realization with set-valued moving horizon estimation
6.1.3 Implementation
6.1.4 Numerical example
6.2 Event-triggered output-feedback control
6.2.1 Closed-loop properties
6.2.2 Implementation
6.2.3 Numerical Examples
6.2.4 Outlook: extension to self-triggered control
6.3 Summary
7 Conclusions.

Set-Theoretic Approaches to the Aperiodic Control of Linear Systems.

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