The Experts below are selected from a list of 72444 Experts worldwide ranked by ideXlab platform
Jian-qiao Sun - One of the best experts on this subject based on the ideXlab platform.
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defensive driving strategy and control for autonomous ground vehicle in mixed traffic
2018Co-Authors: Jian-qiao SunAbstract:One of the challenges of autonomous ground vehicles (AGVs) is to interact with human driven vehicles in the traffic. This paper develops defensive driving strategies and controls for AGVs to avoid problematic vehicles in the mixed traffic. The multi-objective optimization algorithms for local trajectory planning and adaptive cruise control are proposed. The dynamic predictive control is used to derive optimal trajectories in a rolling horizon. The intelligent driver model and lane-changing rules are employed to predict the movement of the vehicles. Multiple performance objectives are optimized simultaneously, including traffic safety, transportation efficiency, driving comfort, tracking error and path consistency. The multi-objective optimization problems are solved with the Cell Mapping method. Different scenarios are created to test the effectiveness of the defensive driving strategies and adaptive cruise control. Extensive experimental simulations show that the proposed defensive driving strategy and PID-form control are promising and may provide a new tool for designing the intelligent navigation system that helps autonomous vehicles to drive safely in the mixed traffic.
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defensive driving strategy for autonomous ground vehicle in mixed traffic
The interdisciplinary journal of Discontinuity Nonlinearity and Complexity, 2017Co-Authors: Jian-qiao SunAbstract:One of the challenges of autonomous ground vehicles (AGVs) is to interact with human driven vehicles in the traffic. This paper develops defensive driving strategies for AGVs to avoid problematic vehicles in the mixed traffic. A multi-objective optimization algorithm for local trajectory planning is proposed. The dynamic predictive control is used to derive optimal trajectories in a rolling horizon. The intelligent driver model and lanechanging rules are employed to predict the movement of the vehicles. Multiple performance objectives are optimized simultaneously, including traffic safety, transportation efficiency, driving comfort and path consistency. The multi-objective optimization problem is solved with the Cell Mapping method. Different and relatively simple scenarios are created to test the effectiveness of the defensive driving strategies. Extensive experimental simulations show that the proposed defensive driving strategy is promising and may provide a new tool for designing the intelligent navigation system that helps autonomous vehicles to drive safely in the mixed traffic.
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multi objective optimal design of sliding mode control with parallel simple Cell Mapping method
Journal of Vibration and Control, 2017Co-Authors: Zhichang Qin, Carlos Hernández, Jian-qiao Sun, Fu-rui Xiong, Qian Ding, Oliver Schutze, Jesus FernandezAbstract:This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple Cell Mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple Cell Mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.
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stochastic response and bifurcation of periodically driven nonlinear oscillators by the generalized Cell Mapping method
Physica A-statistical Mechanics and Its Applications, 2016Co-Authors: Qun Han, Jian-qiao SunAbstract:The stochastic response of nonlinear oscillators under periodic and Gaussian white noise excitations is studied with the generalized Cell Mapping based on short-time Gaussian approximation (GCM/STGA) method. The solutions of the transition probability density functions over a small fraction of the period are constructed by the STGA scheme in order to construct the GCM over one complete period. Both the transient and steady-state probability density functions (PDFs) of a smooth and discontinuous (SD) oscillator are computed to illustrate the application of the method. The accuracy of the results is verified by direct Monte Carlo simulations. The transient responses show the evolution of the PDFs from being Gaussian to non-Gaussian. The effect of a chaotic saddle on the stochastic response is also studied. The stochastic P-bifurcation in terms of the steady-state PDFs occurs with the decrease of the smoothness parameter, which corresponds to the deterministic pitchfork bifurcation.
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parallel Cell Mapping method for global analysis of high dimensional nonlinear dynamical systems
Journal of Applied Mechanics, 2015Co-Authors: Fu-rui Xiong, Carlos Hernández, Zhichang Qin, Qian Ding, Jesus Ruiz Fernandez, Oliver Schutze, Jian-qiao SunAbstract:The Cell Mapping methods were originated by Hsu in 1980s for global analysis of nonlinear dynamical systems that can have multiple steady-state responses including equilibrium states, periodic motions, and chaotic attractors. The Cell Mapping methods have been applied to deterministic, stochastic, and fuzzy dynamical systems. Two important extensions of the Cell Mapping method have been developed to improve the accuracy of the solutions obtained in the Cell state space: the interpolated Cell Mapping (ICM) and the set-oriented method with subdivision technique. For a long time, the Cell Mapping methods have been applied to dynamical systems with low dimension until now. With the advent of cheap dynamic memory and massively parallel computing technologies, such as the graphical processing units (GPUs), global analysis of moderate- to high-dimensional nonlinear dynamical systems becomes feasible. This paper presents a parallel Cell Mapping method for global analysis of nonlinear dynamical systems. The simple Cell Mapping (SCM) and generalized Cell Mapping (GCM) are implemented in a hybrid manner. The solution process starts with a coarse Cell partition to obtain a covering set of the steady-state responses, followed by the subdivision technique to enhance the accuracy of the steady-state responses. When the Cells are small enough, no further subdivision is necessary. We propose to treat the solutions obtained by the Cell Mapping method on a sufficiently fine grid as a database, which provides a basis for the ICM to generate the pointwise approximation of the solutions without additional numerical integrations of differential equations. A modified global analysis of nonlinear systems with transient states is developed by taking advantage of parallel computing without subdivision. To validate the parallelized Cell Mapping techniques and to demonstrate the effectiveness of the proposed method, a low-dimensional dynamical system governed by implicit Mappings is first presented, followed by the global analysis of a three-dimensional plasma model and a six-dimensional Lorenz system. For the six-dimensional example, an error analysis of the ICM is conducted with the Hausdorff distance as a metric.
Qian Ding - One of the best experts on this subject based on the ideXlab platform.
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multi objective optimal design of sliding mode control with parallel simple Cell Mapping method
Journal of Vibration and Control, 2017Co-Authors: Zhichang Qin, Carlos Hernández, Jian-qiao Sun, Fu-rui Xiong, Qian Ding, Oliver Schutze, Jesus FernandezAbstract:This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple Cell Mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple Cell Mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.
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parallel Cell Mapping method for global analysis of high dimensional nonlinear dynamical systems
Journal of Applied Mechanics, 2015Co-Authors: Fu-rui Xiong, Carlos Hernández, Zhichang Qin, Qian Ding, Jesus Ruiz Fernandez, Oliver Schutze, Jian-qiao SunAbstract:The Cell Mapping methods were originated by Hsu in 1980s for global analysis of nonlinear dynamical systems that can have multiple steady-state responses including equilibrium states, periodic motions, and chaotic attractors. The Cell Mapping methods have been applied to deterministic, stochastic, and fuzzy dynamical systems. Two important extensions of the Cell Mapping method have been developed to improve the accuracy of the solutions obtained in the Cell state space: the interpolated Cell Mapping (ICM) and the set-oriented method with subdivision technique. For a long time, the Cell Mapping methods have been applied to dynamical systems with low dimension until now. With the advent of cheap dynamic memory and massively parallel computing technologies, such as the graphical processing units (GPUs), global analysis of moderate- to high-dimensional nonlinear dynamical systems becomes feasible. This paper presents a parallel Cell Mapping method for global analysis of nonlinear dynamical systems. The simple Cell Mapping (SCM) and generalized Cell Mapping (GCM) are implemented in a hybrid manner. The solution process starts with a coarse Cell partition to obtain a covering set of the steady-state responses, followed by the subdivision technique to enhance the accuracy of the steady-state responses. When the Cells are small enough, no further subdivision is necessary. We propose to treat the solutions obtained by the Cell Mapping method on a sufficiently fine grid as a database, which provides a basis for the ICM to generate the pointwise approximation of the solutions without additional numerical integrations of differential equations. A modified global analysis of nonlinear systems with transient states is developed by taking advantage of parallel computing without subdivision. To validate the parallelized Cell Mapping techniques and to demonstrate the effectiveness of the proposed method, a low-dimensional dynamical system governed by implicit Mappings is first presented, followed by the global analysis of a three-dimensional plasma model and a six-dimensional Lorenz system. For the six-dimensional example, an error analysis of the ICM is conducted with the Hausdorff distance as a metric.
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multi objective optimal design of feedback controls for dynamical systems with hybrid simple Cell Mapping algorithm
Communications in Nonlinear Science and Numerical Simulation, 2014Co-Authors: Fu-rui Xiong, Oliver Schutze, Qian DingAbstract:Abstract This paper presents a study of multi-objective optimal design of full state feedback controls. The goal of the design is to minimize several conflicting performance objective functions at the same time. The simple Cell Mapping method with a hybrid algorithm is used to find the multi-objective optimal design solutions. The multi-objective optimal design comes in a set of gains representing various compromises of the control system. Examples of regulation and tracking controls are presented to validate the control design.
Oliver Schutze - One of the best experts on this subject based on the ideXlab platform.
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multi objective optimal design of sliding mode control with parallel simple Cell Mapping method
Journal of Vibration and Control, 2017Co-Authors: Zhichang Qin, Carlos Hernández, Jian-qiao Sun, Fu-rui Xiong, Qian Ding, Oliver Schutze, Jesus FernandezAbstract:This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple Cell Mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple Cell Mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.
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parallel Cell Mapping method for global analysis of high dimensional nonlinear dynamical systems
Journal of Applied Mechanics, 2015Co-Authors: Fu-rui Xiong, Carlos Hernández, Zhichang Qin, Qian Ding, Jesus Ruiz Fernandez, Oliver Schutze, Jian-qiao SunAbstract:The Cell Mapping methods were originated by Hsu in 1980s for global analysis of nonlinear dynamical systems that can have multiple steady-state responses including equilibrium states, periodic motions, and chaotic attractors. The Cell Mapping methods have been applied to deterministic, stochastic, and fuzzy dynamical systems. Two important extensions of the Cell Mapping method have been developed to improve the accuracy of the solutions obtained in the Cell state space: the interpolated Cell Mapping (ICM) and the set-oriented method with subdivision technique. For a long time, the Cell Mapping methods have been applied to dynamical systems with low dimension until now. With the advent of cheap dynamic memory and massively parallel computing technologies, such as the graphical processing units (GPUs), global analysis of moderate- to high-dimensional nonlinear dynamical systems becomes feasible. This paper presents a parallel Cell Mapping method for global analysis of nonlinear dynamical systems. The simple Cell Mapping (SCM) and generalized Cell Mapping (GCM) are implemented in a hybrid manner. The solution process starts with a coarse Cell partition to obtain a covering set of the steady-state responses, followed by the subdivision technique to enhance the accuracy of the steady-state responses. When the Cells are small enough, no further subdivision is necessary. We propose to treat the solutions obtained by the Cell Mapping method on a sufficiently fine grid as a database, which provides a basis for the ICM to generate the pointwise approximation of the solutions without additional numerical integrations of differential equations. A modified global analysis of nonlinear systems with transient states is developed by taking advantage of parallel computing without subdivision. To validate the parallelized Cell Mapping techniques and to demonstrate the effectiveness of the proposed method, a low-dimensional dynamical system governed by implicit Mappings is first presented, followed by the global analysis of a three-dimensional plasma model and a six-dimensional Lorenz system. For the six-dimensional example, an error analysis of the ICM is conducted with the Hausdorff distance as a metric.
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multi objective optimal design of feedback controls for dynamical systems with hybrid simple Cell Mapping algorithm
Communications in Nonlinear Science and Numerical Simulation, 2014Co-Authors: Fu-rui Xiong, Oliver Schutze, Qian DingAbstract:Abstract This paper presents a study of multi-objective optimal design of full state feedback controls. The goal of the design is to minimize several conflicting performance objective functions at the same time. The simple Cell Mapping method with a hybrid algorithm is used to find the multi-objective optimal design solutions. The multi-objective optimal design comes in a set of gains representing various compromises of the control system. Examples of regulation and tracking controls are presented to validate the control design.
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Simple Cell Mapping method for multi-objective optimal feedback control design
International Journal of Dynamics and Control, 2013Co-Authors: Carlos Hernández, Yousef Naranjani, Yousef Sardahi, Wei Liang, Oliver SchutzeAbstract:This paper introduces the simple Cell Mapping (SCM) method for the multi-objective optimal time domain design of feedback controls for linear systems with or without time delay. The SCM method is originally developed for the global analysis of nonlinear dynamical systems, and is extended to the multi-objective optimal design problem of feedback controls in this paper. We consider two feedback control design problems to demonstrate the method: a linear quadratic regulator based approach with the weighting matrices as design parameters, and a direct optimization with feedback control gains as design parameters. The Pareto set and Pareto front consisting of the peak time, overshoot and integrated absolute tracking error are obtained for two linear control systems, one of which has a control time delay. It is interesting to note that for the second order linear system, we have found a structure of the Pareto front, which has been very difficult to obtain using stochastic search algorithms. This study suggests that the SCM method is an effective method that can provide global and fine-structured solutions of MOPs for complex dynamical systems.
J E Womack - One of the best experts on this subject based on the ideXlab platform.
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assignment of the growth hormone receptor gene to bovine chromosome 20 using linkage analysis and somatic Cell Mapping
Animal Genetics, 2009Co-Authors: D E Moody, Daniel Pomp, W Barendse, J E WomackAbstract:A polymorphism was identified in the bovine growth hormone receptor (GHR) gene by digesting polymerase chain reaction (PCR) products with the restriction enzyme Alul. Two alleles were segregating in cattle of Bos indicus descent, but one allele appears to be fixed in Bos taurus cattle. GHR was localized to bovine chromosome 20 using bovine-rodent hybrid Cell lines and linkage analysis.
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somatic Cell Mapping of the bovine prion protein gene and restriction fragment length polymorphism studies in cattle and sheep
Animal Genetics, 2009Co-Authors: A M Ryan, J E WomackAbstract:Summary Brains affected by the progressive neurological disease bovine spongiform encephalopathy (BSE) contain scrapie-associated fibrils and the protease-resistant isoform of prion protein. The gene encoding the normal host prion protein (PRNP) has been mapped to human chromosome 20 and mouse chromosome 2 with the hamster cDNA probe pEA974. Using this probe and a panel of bovine-rodent hybrid somatic Cells, we have mapped PRNP to bovine syntenic group U11 (100% concordancy). PRNP restriction fragment length polymorphisms (RFLPs) were detected with five of six enzymes (BglII, EcoRI, HindIII, MspI and TaqI) in sheep, in contrast to one of 16 enzymes (HincII) in cattle. Codominant segregation of the bovine HincII RFLP was demonstrated in six backcross pedigrees. While PRNP RFLPs are tightly linked to scrapie incubation period, and consequently susceptibility or resistance to disease in rodents and sheep, the relationship between the PRNP RFLPs and BSE incubation period has not been determined.
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a comparative radiation hybrid map of bovine chromosome 18 and homologous chromosomes in human and mice
Proceedings of the National Academy of Sciences of the United States of America, 2002Co-Authors: Tom Goldammer, Srinivas R Kata, R M Brunner, Ute Dorroch, Hanka Sanftleben, M Schwerin, J E WomackAbstract:A comprehensive radiation hybrid (RH) map and a high resolution comparative map of Bos taurus (BTA) chromosome 18 were constructed, composed of 103 markers and 76 markers, respectively, by using a cattle-hamster somatic hybrid Cell panel and a 5,000 rad whole-genome radiation hybrid (WGRH) panel. These maps include 65 new assignments (56 genes, 3 expressed-sequence tags, 6 microsatellites) and integrate 38 markers from the first generation WGRH5,000 map of BTA18. Fifty-nine assignments of coding sequences were supported by somatic hybrid Cell Mapping to markers on BTA18. The total length of the comprehensive map was 1666 cR5,000. Break-point positions within the chromosome were refined and a new telomeric RH linkage group was established. Conserved synteny between cattle, human, and mouse was found for 76 genes of BTA18 and human chromosomes (HSA) 16 and 19 and for 34 cattle genes and mouse chromosomes (MMU) 7 and 8. The new RH map is potentially useful for the identification of candidate genes for economically important traits, contributes to the expansion of the existing BTA18 gene map, and provides new information about the chromosome evolution in cattle, humans, and mice.
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somatic Cell Mapping and in situ localization of the bovine uridine monophosphate synthase gene umps
Mammalian Genome, 1994Co-Authors: A M Ryan, D S Gallagher, B Schwenger, S Schober, J E WomackAbstract:Uridine monophosphate synthase (UMPS) catalyzes the final two steps of de novo pyrimidine synthesis, converting orotic acid to uridine 5' monophosphate. In Holstein and Red Holstein cattle, deficiency of UMPS (DUMPS) is inherited as a monogenic autosomal recessive trait. Heterozygous animals are phenotypically normal but have decreased UMPS activity in a number of tissues, whereas the homozygous genotype is lethal in utero. The cDNA for UMPS has recently been cloned in cattle (Sch6ber et al. 1993). A C ~ T point mutation in codon 405 results in a premature stop codon in DUMPS cattle (Schwenger et al. 1993), providing a DNA test for the detection of heterozygous bulls prior to entry into artificial insemination programs. UMPS has previously been mapped to human Chromosome (Chr) 3q13 (Qumsiyeh et al. 1989), Chinese hamster Chr 4p2 (Qumsiyeh and Suttle 1990), and sheep Chr lq (Burkin et al. 1993). Using somatic celt hybrid analysis and fluorescence in situ hybridization (FISH), we have assigned UMPS to cattle syntenic group U10 and sublocalized the gene to bovine Chr (BTA) 1 band 31. This represents the first assignment of a U10 marker to cattle chromosomes. BUS 6, a 1.5-kb fragment of the bovine UMPS cDNA representing amino acids 133-480 and the 3' untranslated region, was isolated from the E c o R I site of the plasmid pTZl9R (Sch6ber et al. 1993). The insert was radiolabeled with a-32p-dCTP and hybridized to EcoRI -d iges t ed bovine rodent hybrid somatic Cell DNAs under high strin-
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Somatic Cell Mapping of conglutinin (CGN1) to cattle syntenic group U29 and fluorescence in situ localization to Chromosome 28
Mammalian Genome, 1993Co-Authors: D S Gallagher, A M Ryan, L. S. Liou, K. N. Sastry, J E WomackAbstract:A 260-bp genomic Pst I fragment, which encodes a portion of the carbohydrate recognition domain, was used along with hybrid somatic Cells to map the conglutinin gene ( CGN1 ) to domestic cow ( Bos taurus ) syntenic group U29. In turn, a cosmid containing the entire bovine CGN1 was used with fluorescence in situ hybridization to sublocalize this gene to cattle chromosome (Chr) (BTA) 28 band 18. Since BTA 28 and several of the other small acrocentric autosomes of cattle are difficult to discriminate, we have also chromosomally sublocalized CGN1 to the p arm of the lone biarmed autosome of the gaur ( Bos gaurus ). The use of the gaur 2/28 Robertsonian as a marker chromosome and our assignment of CGN1 to BTA 28 should help resolve some of the nomenclatural questions involving this cattle chromosome.
Fu-rui Xiong - One of the best experts on this subject based on the ideXlab platform.
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multi objective optimal design of sliding mode control with parallel simple Cell Mapping method
Journal of Vibration and Control, 2017Co-Authors: Zhichang Qin, Carlos Hernández, Jian-qiao Sun, Fu-rui Xiong, Qian Ding, Oliver Schutze, Jesus FernandezAbstract:This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple Cell Mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple Cell Mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.
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parallel Cell Mapping method for global analysis of high dimensional nonlinear dynamical systems
Journal of Applied Mechanics, 2015Co-Authors: Fu-rui Xiong, Carlos Hernández, Zhichang Qin, Qian Ding, Jesus Ruiz Fernandez, Oliver Schutze, Jian-qiao SunAbstract:The Cell Mapping methods were originated by Hsu in 1980s for global analysis of nonlinear dynamical systems that can have multiple steady-state responses including equilibrium states, periodic motions, and chaotic attractors. The Cell Mapping methods have been applied to deterministic, stochastic, and fuzzy dynamical systems. Two important extensions of the Cell Mapping method have been developed to improve the accuracy of the solutions obtained in the Cell state space: the interpolated Cell Mapping (ICM) and the set-oriented method with subdivision technique. For a long time, the Cell Mapping methods have been applied to dynamical systems with low dimension until now. With the advent of cheap dynamic memory and massively parallel computing technologies, such as the graphical processing units (GPUs), global analysis of moderate- to high-dimensional nonlinear dynamical systems becomes feasible. This paper presents a parallel Cell Mapping method for global analysis of nonlinear dynamical systems. The simple Cell Mapping (SCM) and generalized Cell Mapping (GCM) are implemented in a hybrid manner. The solution process starts with a coarse Cell partition to obtain a covering set of the steady-state responses, followed by the subdivision technique to enhance the accuracy of the steady-state responses. When the Cells are small enough, no further subdivision is necessary. We propose to treat the solutions obtained by the Cell Mapping method on a sufficiently fine grid as a database, which provides a basis for the ICM to generate the pointwise approximation of the solutions without additional numerical integrations of differential equations. A modified global analysis of nonlinear systems with transient states is developed by taking advantage of parallel computing without subdivision. To validate the parallelized Cell Mapping techniques and to demonstrate the effectiveness of the proposed method, a low-dimensional dynamical system governed by implicit Mappings is first presented, followed by the global analysis of a three-dimensional plasma model and a six-dimensional Lorenz system. For the six-dimensional example, an error analysis of the ICM is conducted with the Hausdorff distance as a metric.
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multi objective optimal design of feedback controls for dynamical systems with hybrid simple Cell Mapping algorithm
Communications in Nonlinear Science and Numerical Simulation, 2014Co-Authors: Fu-rui Xiong, Oliver Schutze, Qian DingAbstract:Abstract This paper presents a study of multi-objective optimal design of full state feedback controls. The goal of the design is to minimize several conflicting performance objective functions at the same time. The simple Cell Mapping method with a hybrid algorithm is used to find the multi-objective optimal design solutions. The multi-objective optimal design comes in a set of gains representing various compromises of the control system. Examples of regulation and tracking controls are presented to validate the control design.