Massive parallel robots (MPRs) driven by discrete actuators are force regulated robots that undergo continuous motions despite being commanded through a finite number of states only. Designing a real-time control of such systems requires fast and efficient methods for solving their inverse static analysis (ISA), which is a challenging problem and the subject of this thesis. In particular, five Artificial intelligence methods are proposed to investigate the on-line computation and the generalization error of ISA problem of a class of MPRs featuring three-state force actuators and one degree of revolute motion.
Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:5907 |
Date | 08 May 2013 |
Creators | Pasila, Felix <1974> |
Contributors | Parenti Castelli, Vincenzo |
Publisher | Alma Mater Studiorum - Università di Bologna |
Source Sets | Università di Bologna |
Language | English |
Detected Language | English |
Type | Doctoral Thesis, PeerReviewed |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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