Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control prot...Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields （APF） which could guarantee the connectivity maintenance, col ision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved, and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that al robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.展开更多
This paper presents a MATLAB implementation of the material-field series-expansion(MFSE)topology optimization method.The MFSE method uses a bounded material field with specified spatial correlation to represent the st...This paper presents a MATLAB implementation of the material-field series-expansion(MFSE)topology optimization method.The MFSE method uses a bounded material field with specified spatial correlation to represent the structural topology.With the series-expansion method for bounded fields,this material field is described with the characteristic base functions and the corresponding coefficients.Compared with the conventional density-based method,the MFSE method decouples the topological description and the finite element discretization,and greatly reduces the number of design variables after dimensionality reduction.Other features of this method include inherent control on structural topological complexity,crisp structural boundary description,mesh independence,and being free from the checkerboard pattern.With the focus on the implementation of the MFSE method,the present MATLAB code uses the maximum stiffness optimization problems solved with a gradientbased optimizer as examples.The MATLAB code consists of three parts,namely,the main program and two subroutines(one for aggregating the optimization constraints and the other about the method of moving asymptotes optimizer).The implementation of the code and its extensions to topology optimization problems with multiple load cases and passive elements are discussed in detail.The code is intended for researchers who are interested in this method and want to get started with it quickly.It can also be used as a basis for handling complex engineering optimization problems by combining the MFSE topology optimization method with non-gradient optimization algorithms without sensitivity information because only a few design variables are required to describe relatively complex structural topology and smooth structural boundaries using the MFSE method.展开更多
基金supported by the National Natural Science Foundation of China(61175112)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(G61321002)+3 种基金the Projects of Major International(Regional)Joint Research Program(61120106010)the Beijing Education Committee Cooperation Building Foundationthe Program for Changjiang Scholars and Innovative Research Team in University(IRT1208)the ChangJiang Scholars Program and the Beijing Outstanding Ph.D.Program Mentor Grant(20131000704)
文摘Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields （APF） which could guarantee the connectivity maintenance, col ision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved, and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that al robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.
基金Supported by National Natural Science Foundation of China(11701322)Natural Science Foundation of Yunnan Provincial Department of Science and Technology(2019FH001-078)+1 种基金Natural Science Foundation of Yunnan Provincial Department of Education(2019J0556)Natural Science Foundation of Guangxi Provincial Department of Science and Technology(2017GXNSFBA198130).
基金The authors acknowledge the support of the National Key R&D Program of China(Grant No.2017YFB0203604)the National Natural Science Foundation of China(Grant Nos.11902064 and 11772077)the Liaoning Revitalization Talents Program,China(Grant No.XLYC1807187).
文摘This paper presents a MATLAB implementation of the material-field series-expansion(MFSE)topology optimization method.The MFSE method uses a bounded material field with specified spatial correlation to represent the structural topology.With the series-expansion method for bounded fields,this material field is described with the characteristic base functions and the corresponding coefficients.Compared with the conventional density-based method,the MFSE method decouples the topological description and the finite element discretization,and greatly reduces the number of design variables after dimensionality reduction.Other features of this method include inherent control on structural topological complexity,crisp structural boundary description,mesh independence,and being free from the checkerboard pattern.With the focus on the implementation of the MFSE method,the present MATLAB code uses the maximum stiffness optimization problems solved with a gradientbased optimizer as examples.The MATLAB code consists of three parts,namely,the main program and two subroutines(one for aggregating the optimization constraints and the other about the method of moving asymptotes optimizer).The implementation of the code and its extensions to topology optimization problems with multiple load cases and passive elements are discussed in detail.The code is intended for researchers who are interested in this method and want to get started with it quickly.It can also be used as a basis for handling complex engineering optimization problems by combining the MFSE topology optimization method with non-gradient optimization algorithms without sensitivity information because only a few design variables are required to describe relatively complex structural topology and smooth structural boundaries using the MFSE method.
