RBF Neural Network-Based Terminal Sliding Mode Control for Reentry Warhead

2011 ◽  
Vol 63-64 ◽  
pp. 381-384
Author(s):  
Hong Chao Zhao ◽  
Jie Chen ◽  
Hua Zhang Liu

The existing moving mass control system of a nonspinning reentry warhead could not drive the system error to reach zero in finite time. In order to settle the finite time reach issue, an RBF neural network-based terminal sliding mode controller was presented to design the moving mass control system. It used a terminal sliding mode to ensure that the error reaches zero in finite time. The disturbance and coupled terms of the warhead were treated as uncertainties. An RBF neural network was used to estimate the uncertainties. A nonspinning warhead was taken in the simulation to test the performance of the presented controller. The simulation results show the presented controller has faster tracking speed and higher tracking precision than the former research result.

2020 ◽  
Vol 42 (9) ◽  
pp. 1632-1640
Author(s):  
Wenwu Zhu ◽  
Dongbo Chen ◽  
Haibo Du ◽  
Xiangyu Wang

A finite-time control strategy is proposed to solve the problem of position tracking control for a permanent magnet synchronous motor servo system. It can guarantee that the motor’s desired position can be tracked in a finite time. Firstly, for the d-axis voltage, a first-order finite-time controller is designed based on the vector control principle. Then, for the q-axis voltage, based on a radial basis function (RBF) neural network, an integral high-order terminal sliding mode controller is designed. Theoretical analysis shows that under the proposed controller, the desired position can be tracked by the motor position in a finite time. Simulation results are given to show that the proposed control method has a strong anti-disturbance ability and a fast convergence performance.


2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Gang Wu ◽  
Ke Zhang

Given the resolution of the guidance for intercepting highly maneuvering targets, a novel finite-time convergent guidance law is proposed, which takes the following conditions into consideration, including the impact angle constraint, the guidance command input saturation constraint, and the autopilot second-order dynamic characteristics. Firstly, based on the nonsingular terminal sliding mode control theory, a finite-time convergent nonsingular terminal sliding mode surface is designed. On the back of the backstepping control method, the virtual control law appears. A nonlinear first-order filter is constructed so as to address the “differential expansion” problem in traditional backstepping control. By designing an adaptive auxiliary system, the guidance command input saturation problem is dealt with. The RBF neural network disturbance observer is used for estimating the unknown boundary external disturbances of the guidance system caused by the target acceleration. The parameters of the RBF neural network are adjusted online in real time, for the purpose of improving the estimation accuracy of the RBF neural network disturbance observer and accelerating its convergence characteristics. At the same time, an adaptive law is designed to compensate the estimation error of the RBF neural network disturbance observer. Then, the Lyapunov stability theory is used to prove the finite-time stability of the guidance law. Finally, numerical simulations verify the effectiveness and superiority of the proposed guidance law.


2020 ◽  
pp. 107754632098244
Author(s):  
Hamid Razmjooei ◽  
Mohammad Hossein Shafiei ◽  
Elahe Abdi ◽  
Chenguang Yang

In this article, an innovative technique to design a robust finite-time state feedback controller for a class of uncertain robotic manipulators is proposed. This controller aims to converge the state variables of the system to a small bound around the origin in a finite time. The main innovation of this article is transforming the model of an uncertain robotic manipulator into a new time-varying form to achieve the finite-time boundedness criteria using asymptotic stability methods. First, based on prior knowledge about the upper bound of uncertainties and disturbances, an innovative finite-time sliding mode controller is designed. Then, the innovative finite-time sliding mode controller is developed for finite-time tracking of time-varying reference signals by the outputs of the system. Finally, the efficiency of the proposed control laws is illustrated for serial robotic manipulators with any number of links through numerical simulations, and it is compared with the nonsingular terminal sliding mode control method as one of the most powerful finite-time techniques.


Author(s):  
Chao Han ◽  
Zhen Liu ◽  
Jianqiang Yi

In this paper, a novel adaptive finite-time control of air-breathing hypersonic vehicles is proposed. Based on the immersion and invariance theory, an adaptive finite-time control method for general second-order systems is first derived, using nonsingular terminal sliding mode scheme. Then the method is applied to the control system design of a flexible air-breathing vehicle model, whose dynamics can be decoupled into first-order and second-order subsystems by time-scale separation principle. The main features of this hypersonic vehicle control system lie in the design flexibility of the parameter adaptive laws and the rapid convergence to the equilibrium point. Finally, simulations are conducted, which demonstrate that the control system has the features of fast and accurate tracking to command trajectories and strong robustness to parametric and non-parametric uncertainties.


2020 ◽  
pp. 107754632092526
Author(s):  
Amir Razzaghian ◽  
Reihaneh Kardehi Moghaddam ◽  
Naser Pariz

This study investigates a novel fractional-order nonsingular terminal sliding mode controller via a finite-time disturbance observer for a class of mismatched uncertain nonlinear systems. For this purpose, a finite-time disturbance observer–based fractional-order nonsingular terminal sliding surface is proposed, and the corresponding control law is designed using the Lyapunov stability theory to satisfy the sliding condition in finite time. The proposed fractional-order nonsingular terminal sliding mode control based on a finite-time disturbance observer exhibits better control performance; guarantees finite-time convergence, robust stability of the closed-loop system, and mismatched disturbance rejection; and alleviates the chattering problem. Finally, the effectiveness of the proposed fractional-order robust controller is illustrated via simulation results of both the numerical and application examples which are compared with the fractional-order nonsingular terminal sliding mode controller, sliding mode controller based on a disturbance observer, and integral sliding mode controller methods.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xing Fang ◽  
Fei Liu

A novel full-order terminal sliding-mode controller (FOTSMC) based on the finite-time disturbance observer (FTDO) is proposed for the “JIAOLONG” manned submersible with lumped disturbances. First, a finite-time disturbance observer (FTDO) is developed to estimate the lumped disturbances including the external disturbances and model uncertainties. Second, a full-order terminal sliding-mode surface is designed for the manned submersible, whose sliding-mode motion behaves as full-order dynamics rather than reduced-order dynamics in conventional sliding-mode control systems. Then, a continuous sliding-mode control law is developed to avoid chattering phenomenon, as well as to drive the system outputs to the desired reference trajectory in finite time. Furthermore, the closed-loop system stability analysis is given by Lyapunov theory. Finally, the simulation results demonstrate the satisfactory tracking performance and excellent disturbance rejection capability of the proposed finite-time disturbance observer based full-order terminal sliding-mode control (FTDO-FOTSMC) method.


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