3,025 research outputs found
Variance-constrained multiobjective control and filtering for nonlinear stochastic systems: A survey
The multiobjective control and filtering problems for nonlinear stochastic systems with variance constraints are surveyed. First, the concepts of nonlinear stochastic systems are recalled along with the introduction of some recent advances. Then, the covariance control theory, which serves as a practical method for multi-objective control design as well as a foundation for linear system theory, is reviewed comprehensively. The multiple design requirements frequently applied in engineering practice for the use of evaluating system performances are introduced, including robustness, reliability, and dissipativity. Several design techniques suitable for the multi-objective variance-constrained control and filtering problems for nonlinear stochastic systems are discussed. In particular, as a special case for the multi-objective design problems, the mixed H 2 / H ∞ control and filtering problems are reviewed in great detail. Subsequently, some latest results on the variance-constrained multi-objective control and filtering problems for the nonlinear stochastic systems are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out
Nonlinear analysis of dynamical complex networks
Copyright © 2013 Zidong Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Complex networks are composed of a large number of highly interconnected dynamical units and therefore exhibit very complicated dynamics. Examples of such complex networks include the Internet, that is, a network of routers or domains, the World Wide Web (WWW), that is, a network of websites, the brain, that is, a network of neurons, and an organization, that is, a network of people. Since the introduction of the small-world network principle, a great deal of research has been focused on the dependence of the asymptotic behavior of interconnected oscillatory agents on the structural properties of complex networks. It has been found out that the general structure of the interaction network may play a crucial role in the emergence of synchronization phenomena in various fields such as physics, technology, and the life sciences
Computational intelligence approaches to robotics, automation, and control [Volume guest editors]
No abstract available
A GPU-based multi-criteria optimization algorithm for HDR brachytherapy
Currently in HDR brachytherapy planning, a manual fine-tuning of an objective
function is necessary to obtain case-specific valid plans. This study intends
to facilitate this process by proposing a patient-specific inverse planning
algorithm for HDR prostate brachytherapy: GPU-based multi-criteria optimization
(gMCO).
Two GPU-based optimization engines including simulated annealing (gSA) and a
quasi-Newton optimizer (gL-BFGS) were implemented to compute multiple plans in
parallel. After evaluating the equivalence and the computation performance of
these two optimization engines, one preferred optimization engine was selected
for the gMCO algorithm. Five hundred sixty-two previously treated prostate HDR
cases were divided into validation set (100) and test set (462). In the
validation set, the number of Pareto optimal plans to achieve the best plan
quality was determined for the gMCO algorithm. In the test set, gMCO plans were
compared with the physician-approved clinical plans.
Over 462 cases, the number of clinically valid plans was 428 (92.6%) for
clinical plans and 461 (99.8%) for gMCO plans. The number of valid plans with
target V100 coverage greater than 95% was 288 (62.3%) for clinical plans and
414 (89.6%) for gMCO plans. The mean planning time was 9.4 s for the gMCO
algorithm to generate 1000 Pareto optimal plans.
In conclusion, gL-BFGS is able to compute thousands of SA equivalent
treatment plans within a short time frame. Powered by gL-BFGS, an ultra-fast
and robust multi-criteria optimization algorithm was implemented for HDR
prostate brachytherapy. A large-scale comparison against physician approved
clinical plans showed that treatment plan quality could be improved and
planning time could be significantly reduced with the proposed gMCO algorithm.Comment: 18 pages, 7 figure
A survey of diversity-oriented optimization
The concept of diversity plays a crucial role in many optimization approaches: On the one hand, diversity can be formulated as an essential goal, such as in level set approximation or multiobjective optimization where the aim is to find a diverse set of alternative feasible or, respectively, Pareto optimal solutions. On the other hand, diversity maintenance can play an important role in algorithms that ultimately searc
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