The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Raul Ordonez - One of the best experts on this subject based on the ideXlab platform.
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robust and adaptive design of Numerical Optimization based extremum seeking control
Automatica, 2009Co-Authors: Chunlei Zhang, Raul OrdonezAbstract:We consider the employment of Numerical Optimization and state regulation to solve the extremum seeking control (ESC) problem, which does not assume the time scale separation between the plant dynamics and the extremum seeking loop. Extremum seeking is realized via a state regulator that drives the state traveling along a convergent set point sequence generated by a Numerical Optimization algorithm. In this paper, we propose a novel design of an asymptotic state regulator via output tracking for state feedback linearizable systems, where we trade off finite time state regulation to obtain flexibility in designing a robust extremum seeking controller. Existing techniques such as nonlinear damping and nonlinear adaptive control are then used to deal with input disturbance and unmodeled plant dynamics. Simulation examples illustrate the effectiveness of the basic and robust extremum seeking schemes, and some design guidelines are provided for engineering applications.
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Numerical Optimization based extremum seeking control with application to abs design
IEEE Transactions on Automatic Control, 2007Co-Authors: Chunlei Zhang, Raul OrdonezAbstract:Extremum seeking control (ESC) schemes based on Numerical Optimization are proposed in this paper. The extremum seeking problem is treated as an Optimization with dynamic system constraints. The Numerical Optimization-based extremum seeking control scheme is first applied to linear time-invariant (LTI) systems, then it is extended to a class of feedback linearizable systems. The convergence of the ESC scheme is guaranteed by the Numerical Optimization algorithm and state regulation. The robustness of line search methods and trust region methods is studied, which provides further flexibility for the design of robust extremum seeking controller. Simulation study of antilock braking systems (ABS) design via extremum seeking control is addressed
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Numerical Optimization-based Extremum Seeking Control of LTI Systems
Proceedings of the 44th IEEE Conference on Decision and Control, 2005Co-Authors: Chunlei Zhang, Raul OrdonezAbstract:An extremum seeking control scheme of LTI systems is introduced in this paper. The extremum seeking problem is treated as a Numerical Optimization with dynamic system constraints. The convergence and robustness of the extremum seeking scheme is guaranteed by the Numerical Optimization algorithm, where a detailed analysis based on the line search method is addressed. A simulation example is given to show the effectiveness of the proposed scheme with and without input disturbance.
Chunlei Zhang - One of the best experts on this subject based on the ideXlab platform.
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robust and adaptive design of Numerical Optimization based extremum seeking control
Automatica, 2009Co-Authors: Chunlei Zhang, Raul OrdonezAbstract:We consider the employment of Numerical Optimization and state regulation to solve the extremum seeking control (ESC) problem, which does not assume the time scale separation between the plant dynamics and the extremum seeking loop. Extremum seeking is realized via a state regulator that drives the state traveling along a convergent set point sequence generated by a Numerical Optimization algorithm. In this paper, we propose a novel design of an asymptotic state regulator via output tracking for state feedback linearizable systems, where we trade off finite time state regulation to obtain flexibility in designing a robust extremum seeking controller. Existing techniques such as nonlinear damping and nonlinear adaptive control are then used to deal with input disturbance and unmodeled plant dynamics. Simulation examples illustrate the effectiveness of the basic and robust extremum seeking schemes, and some design guidelines are provided for engineering applications.
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Numerical Optimization based extremum seeking control with application to abs design
IEEE Transactions on Automatic Control, 2007Co-Authors: Chunlei Zhang, Raul OrdonezAbstract:Extremum seeking control (ESC) schemes based on Numerical Optimization are proposed in this paper. The extremum seeking problem is treated as an Optimization with dynamic system constraints. The Numerical Optimization-based extremum seeking control scheme is first applied to linear time-invariant (LTI) systems, then it is extended to a class of feedback linearizable systems. The convergence of the ESC scheme is guaranteed by the Numerical Optimization algorithm and state regulation. The robustness of line search methods and trust region methods is studied, which provides further flexibility for the design of robust extremum seeking controller. Simulation study of antilock braking systems (ABS) design via extremum seeking control is addressed
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Numerical Optimization-based Extremum Seeking Control of LTI Systems
Proceedings of the 44th IEEE Conference on Decision and Control, 2005Co-Authors: Chunlei Zhang, Raul OrdonezAbstract:An extremum seeking control scheme of LTI systems is introduced in this paper. The extremum seeking problem is treated as a Numerical Optimization with dynamic system constraints. The convergence and robustness of the extremum seeking scheme is guaranteed by the Numerical Optimization algorithm, where a detailed analysis based on the line search method is addressed. A simulation example is given to show the effectiveness of the proposed scheme with and without input disturbance.
D. C. Harding - One of the best experts on this subject based on the ideXlab platform.
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Radioactive material transportation package design using Numerical Optimization techniques
1995Co-Authors: D. C. Harding, EldredAbstract:Increasing computational speed has led to the development and use of sophisticated Numerical methods in radioactive material (RAM) transportation container design. The design of a RAM container often involves a complex coupling of structural, thermal, and radioactive shielding analyses. Sandia National Laboratories has integrated automatic mesh generation, explicit structural finite element analysis, transient thermal finite element analysis, and Numerical Optimization techniques into a unified RAM container design tool to increase the efficiency of both the design process and the resultant design through coupled analyses. Although development of this technique has progressed significantly, inaccurate Numerical gradients due to design space nonsmoothness and excessive computational time have hampered successful implementation of Numerical Optimization as a ``black box`` design tool. This paper presents the details of analysis tool integration, simplified model development, constraint boundary nonsmoothness difficulties, and Numerical Optimization results for a lightweight composite-overpack Type B RAM package subject to dynamic crush and fuel fire accident condition constraints.
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Numerical Optimization schemes for the design of transportation packages
1992Co-Authors: W. R. Witkowski, D. C. HardingAbstract:Numerical Optimization has been successfully used to obtain optimal designs in a more efficient and structured manner in many industries. Optimization of sizing variables is already a widely used design tool and even though shape Optimization is still an active research topic, significant successes have been achieved for many structural analysis problems. The transportation cask design problem seems to have the formulation and requirements to benefit from Numerical Optimization. Complex structural, thermal and radiation shielding analyses associated with cask design constraints can be integrated and automated through Numerical Optimization to help meet the growing needs for safe and reliable shipping containers. Improved overall package safety and efficiency with cost savings in the design and fabrication can also be realized. Sandia National Laboratories (SNL) has the opportunity to be a significant contributor in the development of new sophisticated transportation cask design tools. Current state-of-the-art technology at SNL in the areas of structural mechanics, thermal mechanics, Numerical analysis, adaptive finite element analysis, automatic mesh generation, and transportation cask design can be combined to enhance current industry-standard cask design and analysis techniques through Numerical Optimization.
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Transportation package design using Numerical Optimization
1991Co-Authors: D. C. Harding, W. R. WitkowskiAbstract:The purpose of this overview is twofold: first, to outline the theory and basic elements of Numerical Optimization; and second, to show how Numerical Optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of Numerical Optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using Numerical Optimization in the design process.
W. R. Witkowski - One of the best experts on this subject based on the ideXlab platform.
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Numerical Optimization schemes for the design of transportation packages
1992Co-Authors: W. R. Witkowski, D. C. HardingAbstract:Numerical Optimization has been successfully used to obtain optimal designs in a more efficient and structured manner in many industries. Optimization of sizing variables is already a widely used design tool and even though shape Optimization is still an active research topic, significant successes have been achieved for many structural analysis problems. The transportation cask design problem seems to have the formulation and requirements to benefit from Numerical Optimization. Complex structural, thermal and radiation shielding analyses associated with cask design constraints can be integrated and automated through Numerical Optimization to help meet the growing needs for safe and reliable shipping containers. Improved overall package safety and efficiency with cost savings in the design and fabrication can also be realized. Sandia National Laboratories (SNL) has the opportunity to be a significant contributor in the development of new sophisticated transportation cask design tools. Current state-of-the-art technology at SNL in the areas of structural mechanics, thermal mechanics, Numerical analysis, adaptive finite element analysis, automatic mesh generation, and transportation cask design can be combined to enhance current industry-standard cask design and analysis techniques through Numerical Optimization.
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Transportation package design using Numerical Optimization
1991Co-Authors: D. C. Harding, W. R. WitkowskiAbstract:The purpose of this overview is twofold: first, to outline the theory and basic elements of Numerical Optimization; and second, to show how Numerical Optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of Numerical Optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using Numerical Optimization in the design process.
Jurij Šilc - One of the best experts on this subject based on the ideXlab platform.
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USING STIGMERGY TO SOLVE Numerical Optimization PROBLEMS
Computing and Informatics \ Computers and Artificial Intelligence, 2020Co-Authors: Peter Korošec, Jurij ŠilcAbstract:The current methodology for designing highly efficient technological systems needs to choose the best combination of the parameters that affect the performance. In this paper we propose a promising Optimization algorithm, referred to as the Multilevel Ant Stigmergy Algorithm (MASA), which exploits stigmergy in order to optimize multi-parameter functions. We evaluate the performance of the MASA and Differential Evolution -- one of the leading stochastic method for Numerical Optimization -- in terms of their applicability as Numerical Optimization techniques. The comparison is performed using several widely used benchmark functions with added noise.
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The multilevel ant stigmergy algorithm for Numerical Optimization
Facta universitatis. Series electronics and energetics, 2020Co-Authors: Peter Korošec, Jurij ŠilcAbstract:The Multilevel Ant Stigmergy Algorithm (MASA) is a new approach to solving multi-parameter problems based on stigmergy, a type of collective work that can be observed in nature. In this paper we evaluate the performance of MASA regarding its applicability as Numerical Optimization techniques. The evaluation is performed with several widely used benchmarks functions, as well as on an industrial case study. We also compare the MASA with Differential Evolution, well-known Numerical Optimization algorithm. The average solution obtained with the MASA was better than a solution recently found using Differential Evolution.
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Multi-core implementation of the differential ant-stigmergy algorithm for Numerical Optimization
The Journal of Supercomputing, 2012Co-Authors: Peter Korošec, Jurij Šilc, Marián Vajteršic, Rade KutilAbstract:Numerical Optimization techniques are applied to a variety of engineering problems. The cost-function evaluation is an important part of any Numerical Optimization and is usually realized as a black-box simulator. For the efficient solving of the Numerical Optimization problem on multi-core systems, new shared-memory and distributed-memory approaches are proposed. The algorithms are based on an ant-stigmergy meta-heuristics, where indirect coordination between the ants drives the search procedure toward the optimal solution. Indirect coordination offers a high degree of parallelism and therefore relatively straightforward shared-memory and distributed-memory implementations. The Intel-OpenMP 3.0 and MPICH2 libraries are used for the inter-thread and inter-process communications, respectively. It is shown that speed-up strongly depends on the simulation time. This is especially evident in a distributed-memory implementation. Therefore, the algorithms' performances, according to the simulator's time complexity, are experimentally evaluated and discussed.
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BADS@ICAC - A distributed ant-based algorithm for Numerical Optimization
Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems - BADS '09, 2009Co-Authors: Peter Korošec, Jurij ŠilcAbstract:This paper presents a new, distributed approach to the Numerical Optimization problem. The algorithm is based on ant-stigmergy metaheuristics, where indirect coordination between the ants drives the search procedure towards the optimal solution. Indirect coordination offers a high degree of parallelism and therefore a straightforward distributed implementation. For the communication between processes a MPICH2 for Windows library is used. The cost-function evaluation is an important part of the Numerical Optimization and is usually realized as a black-box simulator. Therefore, an algorithm analysis according to the simulator's time complexity is discussed.
