A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved b...A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved by the invariant eigenvalues and the gradually varying eigenvectors. A sufficient stability criterion is given by constructing a series of Lyapunov functions based on the selected discrete characteristic points. An important contribution is that it provides a simple and feasible approach for the design of gain-scheduled controllers for linear time-varying systems, which can guarantee both the global stability and the desired closed-loop performance of the resulted system. The method is applied to the design of a BTT missile autopilot and the simulation results show that the method is superior to the traditional one in sense of either global stability or system performance.展开更多
A global fast convergent integrated guidance and control design approach is proposed. A disturbance observer is utilized to estimate the uncertainties of integrated guidance and control model in finite time. According...A global fast convergent integrated guidance and control design approach is proposed. A disturbance observer is utilized to estimate the uncertainties of integrated guidance and control model in finite time. According to the multiple sliding-mode surface control, the independent nonsingular terminal sliding functions are presented in each step, and all the sliding-mode surfaces run parallel. These presented sliding-mode surfaces keep zero value from a certain time, and the system states converge quickly in sliding phase. Therefore, the system response speed is increased. The proposed method offers the global convergent time analytically, which is useful to optimize the transient performance of system. Simulation results are used to verify the proposed method.展开更多
This paper proposes an optimization algorithm based on a multi-loop control system with a neural network controller,in which the objective function that is used is the control plant of each sub-control system.To obtai...This paper proposes an optimization algorithm based on a multi-loop control system with a neural network controller,in which the objective function that is used is the control plant of each sub-control system.To obtain the global optimization solution from a control plant that has many local minimum points,a transformation function is presented.On the one hand,this approach changes a complex objective function into a simple function under the condition of an unchanged globally optimal solution,to find the global optimization solution more easily by using a multi-loop control system.On the other hand,a special neural network(in which the node function can be simply positioned locally)that is composed of multiple transformation functions is used as the controller,which reduces the possibility of falling into local minimum points.At the same time,a filled function is presented as a control law;it can jump out of a local minimum point and move to another local minimum point that has a smaller value of the objective function.Finally,18 simulation examples are provided to show the effectiveness of the proposed method.展开更多
Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic...Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.展开更多
In this paper, the global controllability for a class of high dimensional polynomial systems has been investigated and a constructive algebraic criterion algorithm for their global controllability has been obtained. B...In this paper, the global controllability for a class of high dimensional polynomial systems has been investigated and a constructive algebraic criterion algorithm for their global controllability has been obtained. By the criterion algorithm, the global controllability can be determined in finite steps of arithmetic operations. The algorithm is imposed on the coefficients of the polynomials only and the analysis technique is based on Sturm Theorem in real algebraic geometry and its modern progress. Finally, the authors will give some examples to show the application of our results.展开更多
基金supported by the National Natural Science Foundation of China (60474015)Program for Changjiang Scholars and Innovative Research Team in University
文摘A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved by the invariant eigenvalues and the gradually varying eigenvectors. A sufficient stability criterion is given by constructing a series of Lyapunov functions based on the selected discrete characteristic points. An important contribution is that it provides a simple and feasible approach for the design of gain-scheduled controllers for linear time-varying systems, which can guarantee both the global stability and the desired closed-loop performance of the resulted system. The method is applied to the design of a BTT missile autopilot and the simulation results show that the method is superior to the traditional one in sense of either global stability or system performance.
基金Project(61673386)supported by the National Natural Science Foundation of ChinaProject(2018QNJJ006)supported by the High-Tech Institute of Xi’an,China
文摘A global fast convergent integrated guidance and control design approach is proposed. A disturbance observer is utilized to estimate the uncertainties of integrated guidance and control model in finite time. According to the multiple sliding-mode surface control, the independent nonsingular terminal sliding functions are presented in each step, and all the sliding-mode surfaces run parallel. These presented sliding-mode surfaces keep zero value from a certain time, and the system states converge quickly in sliding phase. Therefore, the system response speed is increased. The proposed method offers the global convergent time analytically, which is useful to optimize the transient performance of system. Simulation results are used to verify the proposed method.
基金supported by the National Natural Science Foundation of China(61273190)
文摘This paper proposes an optimization algorithm based on a multi-loop control system with a neural network controller,in which the objective function that is used is the control plant of each sub-control system.To obtain the global optimization solution from a control plant that has many local minimum points,a transformation function is presented.On the one hand,this approach changes a complex objective function into a simple function under the condition of an unchanged globally optimal solution,to find the global optimization solution more easily by using a multi-loop control system.On the other hand,a special neural network(in which the node function can be simply positioned locally)that is composed of multiple transformation functions is used as the controller,which reduces the possibility of falling into local minimum points.At the same time,a filled function is presented as a control law;it can jump out of a local minimum point and move to another local minimum point that has a smaller value of the objective function.Finally,18 simulation examples are provided to show the effectiveness of the proposed method.
基金This project was supported by the National Natural Science Foundation of China (60174021) Tianjin Advanced School Science and Technology Development Foundation (01 - 20403) .
文摘Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.
基金supported by the Natural Science Foundation of China under Grant Nos.60804008,61174048and 11071263the Fundamental Research Funds for the Central Universities and Guangdong Province Key Laboratory of Computational Science at Sun Yat-Sen University
文摘In this paper, the global controllability for a class of high dimensional polynomial systems has been investigated and a constructive algebraic criterion algorithm for their global controllability has been obtained. By the criterion algorithm, the global controllability can be determined in finite steps of arithmetic operations. The algorithm is imposed on the coefficients of the polynomials only and the analysis technique is based on Sturm Theorem in real algebraic geometry and its modern progress. Finally, the authors will give some examples to show the application of our results.
基金Supported by National Natural Science Foundation of China （10771101） and Science Research and Development Foundation of Changchun University of Technology （2008A29）
