Recently, switched control systems have been attracting much attention m the control community because the problems are not only academically challenging for the inherent complexity, but also of practical importance d...Recently, switched control systems have been attracting much attention m the control community because the problems are not only academically challenging for the inherent complexity, but also of practical importance due to its wide ranges of applications in nature, engineering, and social sciences.展开更多
In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression ...In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.展开更多
A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is fir...A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.展开更多
文摘Recently, switched control systems have been attracting much attention m the control community because the problems are not only academically challenging for the inherent complexity, but also of practical importance due to its wide ranges of applications in nature, engineering, and social sciences.
基金the 973 Program of China (No.2002CB312200)the National Science Foundation of China (No.60574019)
文摘In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.
基金the National Natural Science Foundation of China(No.51579201)。
文摘A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.
文摘根据三相电压型脉宽调制(pulse width modulation,PWM)整流器的瞬时功率数学模型,在矢量空间中分别研究每个开关矢量对瞬时功率的不同影响,给出相应的作用图,并由此将整个空间重新划分为18个非固定扇区,提出一种新的具有通用性的开关矢量表,在此过程中探究直接功率(direct power control,DPC)控制的调制机制。这种新的开关矢量表不仅可以克服传统开关表对无功功率控制上的缺陷,获得更好的稳态和动态控制效果,而且可以对其他开关表的不足进行一定的解释。文中通过不同开关表的控制系统对比仿真与实验,验证了各项结论的正确性和实用性。
