Identification of piecewise affine and hybrid systems

Proceedings of the American Control Conference

Volumn 5, Issue , 2001, Pages 3521-3526

  Ferrari Trecate, Giancmlo ^a   Muselli, Marco ^b   Liberati, Diego ^c   Morari, Manfred ^a  

^a ETH ZURICH   (Switzerland)

^b UNIVERSITY OF GENOA   (Italy)

^c POLITECNICO DI MILANO   (Italy)

Author keywords

Classification; Clustering; Hybrid systems; Linear regression; Nonlinear identification

Indexed keywords

ALGORITHMS; CONTROL SYSTEM ANALYSIS; CONTROL SYSTEM SYNTHESIS; DISCRETE TIME CONTROL SYSTEMS; MATHEMATICAL MODELS; PIECEWISE LINEAR TECHNIQUES; PROBLEM SOLVING;

DISCRETE TIME HYBRID SYSTEM; LINEAR REGRESSION; NONLINEAR IDENTIFICATION; PIECEWISE AFFINE;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 0034848825     PISSN: 07431619     EISSN: None     Source Type: Journal    
DOI: 10.1109/ACC.2001.946178     Document Type: Article

References (15)

1. Observability and controllability of piecewise affine and hybrid systems
2. Control of systems integrating logic, dynamics, and constraints
3. Verification of hybrid systems via mathematical programming
4. MDL principle for robust vector quantisation
5. Hinging hyperplanes for regression, classification, and function approximation
6. Moving horizon estimation for piecewise affine systems
7. Some competitive learning methods
8. Piecewise linear homeomorphisms: The scalar case
9. Training digital circuits with Hamming clustering
10. A structure trainable neural network with embedded gating units and its learning algorithm