In order to overcome the system non-linearity and uncertainty inherent in magnetic bearing systems, a GA（genetic algnrithm）-based PID neural network controller is designed and trained tO emulate the operation of a c...In order to overcome the system non-linearity and uncertainty inherent in magnetic bearing systems, a GA（genetic algnrithm）-based PID neural network controller is designed and trained tO emulate the operation of a complete system （magnetic bearing, controller, and power amplifiers）. The feasibility of using a neural network to control nonlinear magnetic bearing systems with unknown dynamics is demonstrated. The key concept of the control scheme is to use GA to evaluate the candidate solutions （chromosomes）, increase the generalization ability of PID neural network and avoid suffering from the local minima problem in network learning due to the use of gradient descent learning method. The simulation results show that the proposed architecture provides well robust performance and better reinforcement learning capability in controlling magnetic bearing systems.展开更多
Myxobacteria are well known for multicellular social behaviors and valued for biosynthesis of natural products.Myxobacteria social behaviors such as clumping growth severely hamper strain cultivation and genetic manip...Myxobacteria are well known for multicellular social behaviors and valued for biosynthesis of natural products.Myxobacteria social behaviors such as clumping growth severely hamper strain cultivation and genetic manip-ulation.Using Myxococcus xanthus DK1622,we engineered Hu04,which is deficient in multicellular behavior and pigmentation.Hu04,while maintaining nutritional growth and a similar metabolic background,exhibits improved dispersed growth,streamlining operational procedures.It achieves high cell densities in culture and is promising for synthetic biology applications.展开更多
基金This project is supported by National Natural Science Foundation of China (No. 5880203).
文摘In order to overcome the system non-linearity and uncertainty inherent in magnetic bearing systems, a GA（genetic algnrithm）-based PID neural network controller is designed and trained tO emulate the operation of a complete system （magnetic bearing, controller, and power amplifiers）. The feasibility of using a neural network to control nonlinear magnetic bearing systems with unknown dynamics is demonstrated. The key concept of the control scheme is to use GA to evaluate the candidate solutions （chromosomes）, increase the generalization ability of PID neural network and avoid suffering from the local minima problem in network learning due to the use of gradient descent learning method. The simulation results show that the proposed architecture provides well robust performance and better reinforcement learning capability in controlling magnetic bearing systems.
基金supported by the National Key Research and Development Program of China (2021YFC2101000)the Na-tional Natural Science Foundation of China (32070030 and 32301220).
文摘Myxobacteria are well known for multicellular social behaviors and valued for biosynthesis of natural products.Myxobacteria social behaviors such as clumping growth severely hamper strain cultivation and genetic manip-ulation.Using Myxococcus xanthus DK1622,we engineered Hu04,which is deficient in multicellular behavior and pigmentation.Hu04,while maintaining nutritional growth and a similar metabolic background,exhibits improved dispersed growth,streamlining operational procedures.It achieves high cell densities in culture and is promising for synthetic biology applications.
