Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinea...Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.展开更多
This paper proposes a novel reinforcement-learning-based intelligent fault-tolerant assistance control framework for Air-breathing Hypersonic Vehicles(AHVs).Considering that Reinforcement Learning(RL)has the advantage...This paper proposes a novel reinforcement-learning-based intelligent fault-tolerant assistance control framework for Air-breathing Hypersonic Vehicles(AHVs).Considering that Reinforcement Learning(RL)has the advantage of exploring approximate optimal strategies,an RL-based assistance controller parallel to the fundamental controller is introduced to generate the assistance control signal.Specifically,the Incremental model-based Dual Heuristic Programming(IDHP)method is adopted to design the RL-based assistance control law.In order to extend the IDHP method to the assistance control scenario,a novel linear time-varying incremental model of the closed-loop augmented system is constructed and identified in real time,which consists of the AHV plant,the fundamental controller,and the command generator.The RL agent continuously updates its neural-network weights according to the real-time identification information,and adjusts its control policy,i.e.,the assistance control signal,after detecting sudden model changes.Simulation results have validated the effectiveness of the proposed intelligent fault-tolerant control scheme under various types of elevator faults and aerodynamic/configuration parameter uncertainties.The fault-tolerant ability of the whole control system with the proposed RL-based assistance controller is validated in both inner-loop attitude and outer-loop altitude tracking tasks.展开更多
The capacity of mobile communication system is improved by using Voice Activity Detection (VAD) technology. In this letter, a novel VAD algorithm, SVAD algorithm based on Fuzzy Neural Network Knowledge Discovery (FNNK...The capacity of mobile communication system is improved by using Voice Activity Detection (VAD) technology. In this letter, a novel VAD algorithm, SVAD algorithm based on Fuzzy Neural Network Knowledge Discovery (FNNKD) method is proposed. The performance of SVAD algorithm is discussed and compared with traditional algorithm recommended by ITU G.729B in different situations. The simulation results show that the SVAD algorithm performs better.展开更多
基金Supported by the National Natural Science Foundation of China(61573052)
文摘Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.
基金co-supported by the Aeronautical Science Foundation of China(Nos.20220048051001,20230013051002)the“1912 Project”of China。
文摘This paper proposes a novel reinforcement-learning-based intelligent fault-tolerant assistance control framework for Air-breathing Hypersonic Vehicles(AHVs).Considering that Reinforcement Learning(RL)has the advantage of exploring approximate optimal strategies,an RL-based assistance controller parallel to the fundamental controller is introduced to generate the assistance control signal.Specifically,the Incremental model-based Dual Heuristic Programming(IDHP)method is adopted to design the RL-based assistance control law.In order to extend the IDHP method to the assistance control scenario,a novel linear time-varying incremental model of the closed-loop augmented system is constructed and identified in real time,which consists of the AHV plant,the fundamental controller,and the command generator.The RL agent continuously updates its neural-network weights according to the real-time identification information,and adjusts its control policy,i.e.,the assistance control signal,after detecting sudden model changes.Simulation results have validated the effectiveness of the proposed intelligent fault-tolerant control scheme under various types of elevator faults and aerodynamic/configuration parameter uncertainties.The fault-tolerant ability of the whole control system with the proposed RL-based assistance controller is validated in both inner-loop attitude and outer-loop altitude tracking tasks.
文摘The capacity of mobile communication system is improved by using Voice Activity Detection (VAD) technology. In this letter, a novel VAD algorithm, SVAD algorithm based on Fuzzy Neural Network Knowledge Discovery (FNNKD) method is proposed. The performance of SVAD algorithm is discussed and compared with traditional algorithm recommended by ITU G.729B in different situations. The simulation results show that the SVAD algorithm performs better.
