A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and...A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and magnetometer are introduced to construct an error equation with the gyros,thus the drifting characteristics of gyroscope can be compensated by solving the error equation utilized by the gradient descent algorithm.Performance of the presented algorithm is evaluated using a self-proposed micro-electro-mechanical system(MEMS)based attitude heading reference system which is mounted on a tri-axis turntable.The on-ground,turntable and flight experiments indicate that the estimation attitude has a good accuracy.Also,the presented system is compared with an open-source flight control system which runs extended Kalman filter(EKF),and the results show that the attitude control system using the gradient descent method can estimate the attitudes for UAV effectively.展开更多
With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rej...With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.展开更多
The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks,which is an optimization algorithm for finding a local minimum of an objective function.The quantum vers...The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks,which is an optimization algorithm for finding a local minimum of an objective function.The quantum versions of gradient descent have been investigated and implemented in calculating molecular ground states and optimizing polynomial functions.Based on the quantum gradient descent algorithm and Choi-Jamiolkowski isomorphism,we present approaches to simulate efficiently the nonequilibrium steady states of Markovian open quantum many-body systems.Two strategies are developed to evaluate the expectation values of physical observables on the nonequilibrium steady states.Moreover,we adapt the quantum gradient descent algorithm to solve linear algebra problems including linear systems of equations and matrix-vector multiplications,by converting these algebraic problems into the simulations of closed quantum systems with well-defined Hamiltonians.Detailed examples are given to test numerically the effectiveness of the proposed algorithms for the dissipative quantum transverse Ising models and matrix-vector multiplications.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
针对直流微电网系统中双有源桥(Dual active bridge,DAB)变换器存在的直流母线电压和负载波动大、传输功率不稳定等问题,提出一种基于遗传算法的自抗扰控制与梯度下降算法优化回流功率的混合优化控制策略。首先,分析拓展移相调制下DAB...针对直流微电网系统中双有源桥(Dual active bridge,DAB)变换器存在的直流母线电压和负载波动大、传输功率不稳定等问题,提出一种基于遗传算法的自抗扰控制与梯度下降算法优化回流功率的混合优化控制策略。首先,分析拓展移相调制下DAB变换器的拓扑结构和功率特性,以回流功率为损失函数,引入梯度下降算法迭代寻找最优内移相比。随后,在DAB变换器小信号建模的基础上,设计线性自抗扰控制器,通过扩张状态观测器对输出电压和系统内外部扰动进行观测估计。同时,考虑到复杂环境下自抗扰控制器参数整定的不确定性,引入遗传算法对自抗扰控制器进行参数自整定。最后,搭建以TMS320F28335为控制器的试验平台对提出的混合优化控制策略(Hybrid optimal control strategy under extended phase shift modulation,EPS-HOCS)和传统PI控制(PI control strategy under extended phase shift modulation,EPS-PI)和自适应梯度下降算法控制(Adaptive gradient descent algorithm under extended phase shift modulation,EPS-AGDA)进行分析对比,验证了所提策略在回流功率和动态性能方面的优越性。展开更多
We extend a results presented by Y.F. Hu and C.Storey (1991) [1] on the global convergence result for conjugate gradient methods with different choices for the parameter β k . In this note, the condit...We extend a results presented by Y.F. Hu and C.Storey (1991) [1] on the global convergence result for conjugate gradient methods with different choices for the parameter β k . In this note, the conditions given on β k are milder than that used by Y.F. Hu and C. Storey.展开更多
The Water Cloud Model(WCM)plays a crucial role in active microwave soil moisture inversion applications.Empirical parameters are important factors affecting the accuracy of WCM simulation,but the current evaluation of...The Water Cloud Model(WCM)plays a crucial role in active microwave soil moisture inversion applications.Empirical parameters are important factors affecting the accuracy of WCM simulation,but the current evaluation of empirical parameters only considers the forward simulation process,and insufficient consideration is given to the model inversion problem.This study proposes a new estimation method for vegetation parameters in the WCM by combining the soil backscattering model and the objective function.The effectiveness of the method is then verified using measured data.Simultaneously,this study also analyzes the factors influencing the evaluation of vegetation parameters in the WCM,resulting in the following conclusions.First,blindly utilizing vegetation parameters recommended by previous model studies is not advisable.To ensure the accuracy of the simulation,it is necessary to adjust the vegetation parameters appropriately.Second,to ensure the ability of the WCM solving both forward and inverse problems,it is advisable to consider both soil backscatter and surface backscatter simulations in the construction of the cost function.Third,soil backscatter simulations have an impact on the solution of vegetation parameters,and more accurate soil scattering models provide a better representation of the modeled vegetation.This study presents a dependable method for resolving the vegetation parameters of the WCM,thereby offering a valuable reference for the application of the model in surface parameter inversion research.展开更多
提出了一种基于有效性分析的自组织模糊神经网络(self-organizingfuzzyneural network based on effectiveness analysis, SOEFNN)建模方法。首先,提出了一种针对模糊规则的有效性评价指标,利用样本与规则层输出之间的映射关系进行网络...提出了一种基于有效性分析的自组织模糊神经网络(self-organizingfuzzyneural network based on effectiveness analysis, SOEFNN)建模方法。首先,提出了一种针对模糊规则的有效性评价指标,利用样本与规则层输出之间的映射关系进行网络模型的有效性分析,通过累积触发的方式实现相应模糊规则的增加或删减,使网络模型在能够处理复杂非线性问题的同时降低其冗余性,使模型更为紧凑。采用梯度下降算法对网络模型进行训练。然后,对所提出的SOEFNN模型进行非线性系统仿真实验和污水处理过程中的出水生化需氧量预测建模,并与其他自组织模糊神经网络模型进行对比。仿真结果表明,所提出的SOEFNN模型能够很好地实现结构和参数的自适应调整,并且具有较好的逼近能力。展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.56XAA17075)
文摘A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and magnetometer are introduced to construct an error equation with the gyros,thus the drifting characteristics of gyroscope can be compensated by solving the error equation utilized by the gradient descent algorithm.Performance of the presented algorithm is evaluated using a self-proposed micro-electro-mechanical system(MEMS)based attitude heading reference system which is mounted on a tri-axis turntable.The on-ground,turntable and flight experiments indicate that the estimation attitude has a good accuracy.Also,the presented system is compared with an open-source flight control system which runs extended Kalman filter(EKF),and the results show that the attitude control system using the gradient descent method can estimate the attitudes for UAV effectively.
基金the 2021 Key Project of Natural Science and Technology of Yangzhou Polytechnic Institute,Active Disturbance Rejection and Fault-Tolerant Control of Multi-Rotor Plant ProtectionUAV Based on QBall-X4(Grant Number 2021xjzk002).
文摘With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.12075159,12171044,and 12005015)Beijing Natural Science Foundation(Grant No.Z190005)Academy for Multidisciplinary Studies,Capital Normal University,Academician Innovation Platform of Hainan Province,and Shenzhen Institute for Quantum Science and Engineering,Southern University of Science and Technology(Grant No.SIQSE202001)。
文摘The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks,which is an optimization algorithm for finding a local minimum of an objective function.The quantum versions of gradient descent have been investigated and implemented in calculating molecular ground states and optimizing polynomial functions.Based on the quantum gradient descent algorithm and Choi-Jamiolkowski isomorphism,we present approaches to simulate efficiently the nonequilibrium steady states of Markovian open quantum many-body systems.Two strategies are developed to evaluate the expectation values of physical observables on the nonequilibrium steady states.Moreover,we adapt the quantum gradient descent algorithm to solve linear algebra problems including linear systems of equations and matrix-vector multiplications,by converting these algebraic problems into the simulations of closed quantum systems with well-defined Hamiltonians.Detailed examples are given to test numerically the effectiveness of the proposed algorithms for the dissipative quantum transverse Ising models and matrix-vector multiplications.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
文摘针对直流微电网系统中双有源桥(Dual active bridge,DAB)变换器存在的直流母线电压和负载波动大、传输功率不稳定等问题,提出一种基于遗传算法的自抗扰控制与梯度下降算法优化回流功率的混合优化控制策略。首先,分析拓展移相调制下DAB变换器的拓扑结构和功率特性,以回流功率为损失函数,引入梯度下降算法迭代寻找最优内移相比。随后,在DAB变换器小信号建模的基础上,设计线性自抗扰控制器,通过扩张状态观测器对输出电压和系统内外部扰动进行观测估计。同时,考虑到复杂环境下自抗扰控制器参数整定的不确定性,引入遗传算法对自抗扰控制器进行参数自整定。最后,搭建以TMS320F28335为控制器的试验平台对提出的混合优化控制策略(Hybrid optimal control strategy under extended phase shift modulation,EPS-HOCS)和传统PI控制(PI control strategy under extended phase shift modulation,EPS-PI)和自适应梯度下降算法控制(Adaptive gradient descent algorithm under extended phase shift modulation,EPS-AGDA)进行分析对比,验证了所提策略在回流功率和动态性能方面的优越性。
文摘We extend a results presented by Y.F. Hu and C.Storey (1991) [1] on the global convergence result for conjugate gradient methods with different choices for the parameter β k . In this note, the conditions given on β k are milder than that used by Y.F. Hu and C. Storey.
基金National Natural Science Foundation of China,Grant/Award Number:51779269。
文摘The Water Cloud Model(WCM)plays a crucial role in active microwave soil moisture inversion applications.Empirical parameters are important factors affecting the accuracy of WCM simulation,but the current evaluation of empirical parameters only considers the forward simulation process,and insufficient consideration is given to the model inversion problem.This study proposes a new estimation method for vegetation parameters in the WCM by combining the soil backscattering model and the objective function.The effectiveness of the method is then verified using measured data.Simultaneously,this study also analyzes the factors influencing the evaluation of vegetation parameters in the WCM,resulting in the following conclusions.First,blindly utilizing vegetation parameters recommended by previous model studies is not advisable.To ensure the accuracy of the simulation,it is necessary to adjust the vegetation parameters appropriately.Second,to ensure the ability of the WCM solving both forward and inverse problems,it is advisable to consider both soil backscatter and surface backscatter simulations in the construction of the cost function.Third,soil backscatter simulations have an impact on the solution of vegetation parameters,and more accurate soil scattering models provide a better representation of the modeled vegetation.This study presents a dependable method for resolving the vegetation parameters of the WCM,thereby offering a valuable reference for the application of the model in surface parameter inversion research.
文摘提出了一种基于有效性分析的自组织模糊神经网络(self-organizingfuzzyneural network based on effectiveness analysis, SOEFNN)建模方法。首先,提出了一种针对模糊规则的有效性评价指标,利用样本与规则层输出之间的映射关系进行网络模型的有效性分析,通过累积触发的方式实现相应模糊规则的增加或删减,使网络模型在能够处理复杂非线性问题的同时降低其冗余性,使模型更为紧凑。采用梯度下降算法对网络模型进行训练。然后,对所提出的SOEFNN模型进行非线性系统仿真实验和污水处理过程中的出水生化需氧量预测建模,并与其他自组织模糊神经网络模型进行对比。仿真结果表明,所提出的SOEFNN模型能够很好地实现结构和参数的自适应调整,并且具有较好的逼近能力。
