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DC Field | Value | Language |
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dc.contributor.author | Mercieca, Julian | - |
dc.contributor.author | Fabri, Simon G. | - |
dc.date.accessioned | 2022-03-17T07:07:19Z | - |
dc.date.available | 2022-03-17T07:07:19Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Mercieca, J., & Fabri, S. G. (2011). Particle swarm optimization for nonlinear model predictive control. Proc. ADVCOMP, 88-93. | en_GB |
dc.identifier.isbn | 9781612081724 | - |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/91644 | - |
dc.description.abstract | The paper proposes two Nonlinear Model Predictive Control schemes that uncover a synergistic relationship between on-line receding horizon style computation and Particle Swarm Optimization, thus benefiting from both the performance advantages of on-line computation and the desirable properties of Particle Swarm Optimization. After developing these techniques for the unconstrained nonlinear optimal control problem, the entire design methodology is illustrated by a simulated inverted pendulum on a cart, and compared with a particular numerical linearization technique exploiting conventional convex optimization methods. This is then extended to input constrained nonlinear systems, offering a promising new paradigm for nonlinear optimal control design. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | IARIA | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Neural networks (Computer science) | en_GB |
dc.subject | Adaptive control systems | en_GB |
dc.subject | Nonlinear systems | en_GB |
dc.subject | Swarm intelligence | en_GB |
dc.subject | Computational intelligence | en_GB |
dc.subject | Nonlinear control theory | en_GB |
dc.subject | Predictive control | en_GB |
dc.subject | Artificial intelligence | en_GB |
dc.title | Particle swarm optimization for nonlinear model predictive control | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.bibliographicCitation.conferencename | ADVCOMP 2011 : The Fifth International Conference on Advanced Engineering Computing and Applications in Sciences | en_GB |
dc.bibliographicCitation.conferenceplace | Lisbon, Portugal, 20-25/11/2011 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
Appears in Collections: | Scholarly Works - FacEngSCE |
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