The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers...The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.展开更多
Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar park...Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.展开更多
Robust discrete quasi-sliding mode tracking controller is developed with discrete reaching law for trajectory tracking in the presence of modeling uncertainty and unknown disturbance. The conventional prior knowledge ...Robust discrete quasi-sliding mode tracking controller is developed with discrete reaching law for trajectory tracking in the presence of modeling uncertainty and unknown disturbance. The conventional prior knowledge of uncertainty upper bounds being replaced by an on-line estimation used in the controller to cancel the slowly varying uncertainties by the mechanism of time delay. This method reduces the feedback gain substantially and improves tracking accuracy. The system behavior in the vicinity of the sliding surface is examined for the existence and bandwidth of quasi-sliding mode. Simulation results show the effectiveness of the strategy.展开更多
In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and suf...In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.展开更多
For the dynamic property in the control system, in this paper we advance dynamic logic to analyze and synthesize the control problems. This approach is similar to the way in which people always resolve such problems, ...For the dynamic property in the control system, in this paper we advance dynamic logic to analyze and synthesize the control problems. This approach is similar to the way in which people always resolve such problems, and it can reflect the nature of the system. The dynamic logic combines the people's logic analysis with the dynamic property of the control system. On the basis of the dynamic logic qualitative model, the analyzing process and synthesizing process may go on. So there are many of the non-linear and logic factors which can be directly taken into consideration in the analyzing and designing process. The combination of the human intelligence and artificial intelligent techniques with the conventional methods of analysis and design, has provide an effective tool for the qualitative analysis and the qualitative design of the intelligent control system. We have successfully resolved the stabilizing problem of the inverted pendulum with dynamic logic.展开更多
In this paper, the stabilization of a linear SISO plant with variable operating condition is considered. The plant is described by a linear interpolation of proper stable co-prime factorizations of the transfer functi...In this paper, the stabilization of a linear SISO plant with variable operating condition is considered. The plant is described by a linear interpolation of proper stable co-prime factorizations of the transfer functions at two representative operating points. An interpolation of the stabilizing controllers for the representative models is designed to stabilize the plant, and the necessary and sufficient condition for the plant to be stabilized by the proposed controller is presented using the Nevanlinna-Pick interpolation theory. It is shown that the class of stabilization plants via the proposed controller in the paper is larger than that by the controller in reference. An example is also given to illustrate this fact.展开更多
基金This project was supported by the fundation of the Academy of Finland (201353)
文摘The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.
基金supported by the National Nature Science Foundation of China(61304223)the Aeronautical Science Foundation of China(2016ZA52009)the Research Fund for the Doctoral Program of Higher Education of China(20123218120015)
文摘Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.
文摘Robust discrete quasi-sliding mode tracking controller is developed with discrete reaching law for trajectory tracking in the presence of modeling uncertainty and unknown disturbance. The conventional prior knowledge of uncertainty upper bounds being replaced by an on-line estimation used in the controller to cancel the slowly varying uncertainties by the mechanism of time delay. This method reduces the feedback gain substantially and improves tracking accuracy. The system behavior in the vicinity of the sliding surface is examined for the existence and bandwidth of quasi-sliding mode. Simulation results show the effectiveness of the strategy.
文摘In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.
文摘For the dynamic property in the control system, in this paper we advance dynamic logic to analyze and synthesize the control problems. This approach is similar to the way in which people always resolve such problems, and it can reflect the nature of the system. The dynamic logic combines the people's logic analysis with the dynamic property of the control system. On the basis of the dynamic logic qualitative model, the analyzing process and synthesizing process may go on. So there are many of the non-linear and logic factors which can be directly taken into consideration in the analyzing and designing process. The combination of the human intelligence and artificial intelligent techniques with the conventional methods of analysis and design, has provide an effective tool for the qualitative analysis and the qualitative design of the intelligent control system. We have successfully resolved the stabilizing problem of the inverted pendulum with dynamic logic.
文摘In this paper, the stabilization of a linear SISO plant with variable operating condition is considered. The plant is described by a linear interpolation of proper stable co-prime factorizations of the transfer functions at two representative operating points. An interpolation of the stabilizing controllers for the representative models is designed to stabilize the plant, and the necessary and sufficient condition for the plant to be stabilized by the proposed controller is presented using the Nevanlinna-Pick interpolation theory. It is shown that the class of stabilization plants via the proposed controller in the paper is larger than that by the controller in reference. An example is also given to illustrate this fact.
