scholarly journals Study on Fuzzy Neural Sliding Mode Guidance Law with Terminal Angle Constraint for Maneuvering Target

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xin Wang ◽  
Xue Qiu
Keyword(s):  
Neural Network ◽  
Embedded System ◽  
Optimization Design ◽  
Control Method ◽  
Sliding Mode ◽  
Variable Structure ◽  
Maneuvering Target ◽  
Guidance Law ◽  
Fuzzy Neural ◽  
Terminal Angle Constraint

Aiming at the requirement that the guidance law should meet the minimum miss distance and the desired terminal angle at the same time, a sliding mode variable structure control method is introduced. In order to improve the fuzzy variable structure guidance law for maneuvering target attack effect, a neural network to the optimization design is carried out on the guidance law. The neural network is trained by the samples, which is under the condition of different error coefficient of angle, the coefficient of reaching law, and the coefficient of on-off item about target. Fuzzy neural sliding mode guidance law with terminal angle constraint can increase the performance of the large maneuvering target. In addition, on the basis of the traditional PC platform visual simulation system, a new guidance law simulation platform based on embedded system and virtual reality technology is formed. The platform can verify the validity of the guidance law.

scholarly journals Adaptive Fuzzy Sliding Mode Guidance Law considering Available Acceleration and Autopilot Dynamics

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yulin Wang ◽  
Shengjing Tang ◽  
Wei Shang ◽  
Jie Guo
Keyword(s):  
Sliding Mode ◽  
Variable Structure ◽  
Adaptive Sliding Mode Control ◽  
Maneuvering Target ◽  
Guidance Law ◽  
Target Acceleration ◽  
Neural Network System ◽  
Fuzzy Sliding Mode ◽  
Miss Distance ◽  
Terminal Guidance

Terminal guidance law for missiles intercepting high maneuvering targets considering the limited available acceleration and autopilot dynamics of interceptor is investigated. Conventional guidance laws based on adaptive sliding mode control theory were designed to intercept a maneuvering target. However, they demand a large acceleration for interceptor at the end of the terminal guidance, which may have acceleration saturation especially when the target acceleration is close to the available acceleration of interceptor. In this paper, a terminal guidance law considering the available acceleration and autopilot dynamics of interceptor is proposed. Then, a fuzzy system is utilized to approximate and replace the variable structure term, which can handle the unknown target acceleration. And an adaptive neural network system is adopted to compensate the effects caused by the designed overlarge acceleration of interceptor such that the interceptor with small available acceleration can intercept the high maneuvering target. Simulation results show that the guidance law with available acceleration and autopilot dynamics (AAADG) is highly effective for reducing the acceleration command and achieving a small final miss distance.

scholarly journals Fault-Tolerant Aircraft Control Based on Self-Constructing Fuzzy Neural Network for Quadcopter

2021 ◽  
Vol 15 (1) ◽  
pp. 109-122
Author(s):  
Dejie Li ◽  
◽  
Pu Yang ◽  
Zhangxi Liu ◽  
Zixin Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Failure Model ◽  
Aircraft Control ◽  
Actuator Failure ◽  
Fuzzy Neural ◽  
The Stability

This paper proposes a fault-tolerant aircraft control method based on a self-constructed fuzzy neural network for quadcopters with multiple actuator faults. We first introduce the actuator failure model and the model uncertainty. Subsequently, we establish a framework for a self-constructed fuzzy neural network observer with an adaptive rate to obtain the estimated value of the nonlinear term of the module uncertainty. We also design a multivariable sliding mode fault-tolerant controller to ensure the stability of the aircraft under this fault condition. Finally, we conduct experiments using the Pixhawk 4 flight controller installed on the QBall-X4 UAV experimental platform, such that the use of the flight controller’s fault coprocessor and redundant sensor design reduces the crash that occurs during the debugging of the control algorithm. Compared to the existing intelligent fault-tolerant control technology, our proposed method employs fewer fuzzy rules, and the number of these rules can be adaptively adjusted when the system model changes. In the experimental test, the aircraft was still able to fly stably under multi-actuator failure and interference conditions, thereby proving the stability of the proposed controller.

A robust hybrid nonlinear guidance law for intercepting a non-cooperative maneuvering target

2019 ◽  
Vol 124 (1273) ◽  
pp. 429-445
Author(s):  
Xiaodong Yan ◽  
Shi Lyu
Keyword(s):  
Control Method ◽  
Sliding Mode ◽  
Fixed Time ◽  
Small Region ◽  
Lower Sensitivity ◽  
Prescribed Performance ◽  
Maneuvering Target ◽  
Guidance Law ◽  
Delay Control ◽  
Two Phases

ABSTRACTThis paper has proposed a new robust hybrid nonlinear guidance law, which accounts for a missile’s terminal line-of-sight (LOS) angle constraint, in order to intercept a non-cooperative maneuvering target. The proposed hybrid nonlinear guidance strategy consists of two phases; in the first phase, a guidance law named PIGL is derived from prescribed performance control and the inertial delay control method. In PIGL, a revised prescribed performance function is put forward, and a prescribed performance controller with unknown uncertainties is then derived. The controller smoothly drives both the LOS angle and its rate to a predesigned small region under unknown uncertainties that are induced by target’s maneuvers within a fixed time. Then, a guidance law named SIGL is activated, which is derived from sliding mode control and inertial delay control. By driving the desired sliding mode variable to zero within a finite time, the SIGL guidance law is able to achieve high terminal interception accuracy. The robustness of both of the proposed sub-guidance laws has been proved explicitly in this paper. The hybrid guidance law has the advantage of a tunable convergence rate of the LOS angle and the rate of the LOS angle at the beginning period, by which an excessive large initial maneuver can be avoided. Meanwhile, the hybrid guidance law also has the advantage of lower sensitivity to errors in the estimation of the time-to-go.

scholarly journals Picking Robot Visual Servo Control Based on Modified Fuzzy Neural Network Sliding Mode Algorithms

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 605 ◽  
Author(s):  
Wei Chen ◽  
Tongqing Xu ◽  
Junjie Liu ◽  
Mo Wang ◽  
Dean Zhao
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Control Algorithm ◽  
Fuzzy Neural Network ◽  
Sliding Mode ◽  
Variable Structure ◽  
Network Control ◽  
Servo Control ◽  
Mode Control ◽  
Fuzzy Neural

Through an analysis of the kinematics and dynamics relations between the target positioning of manipulator joint angles of an apple-picking robot, the sliding-mode control (SMC) method is introduced into robot servo control according to the characteristics of servo control. However, the biggest problem of the sliding-mode variable structure control is chattering, and the speed, inertia, acceleration, switching surface, and other factors are also considered when approaching the sliding die surface. Meanwhile, neural network has the characteristics of approaching non-linear function and not depending on the mechanism model of the system. Therefore, the fuzzy neural network control algorithm can effectively solve the chattering problem caused by the variable structure of the sliding mode and improve the dynamic and static performances of the control system. The comparison experiment is carried out through the application of the PID algorithm, the sliding mode control algorithm, and the improved fuzzy neural network sliding mode control algorithm on the picking robot system in the laboratory environment. The result verified that the intelligent algorithm can reduce the complexity of parameter adjustments and improve the control accuracy to a certain extent.

Finite Time Convergence Guidance Law Accounting for Missile Autopilot

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Pingping Qu ◽  
Chuntao Shao ◽  
Di Zhou
Keyword(s):  
Finite Time ◽  
Control Method ◽  
Sliding Mode ◽  
Line Of Sight ◽  
Practical Applications ◽  
Maneuvering Target ◽  
Finite Time Convergence ◽  
Guidance Law ◽  
Convergence Control ◽  
Derivatives Of

A guidance law with finite time convergence is designed using the sliding mode control method and finite time convergence control theory, accounting for the missile autopilot as second-order dynamics. The high-order derivatives of the line of sight (LOS) angle are avoided in the expression of guidance law such that it can be implemented in practical applications. The designed guidance law is effective in compensating the bad influence of the autopilot dynamics on guidance accuracy. In simulations of intercepting a non maneuvering target or a maneuvering target, respectively, the designed guidance law is compared with the adaptive sliding mode guidance (ASMG) law in the presence of missile autopilot lag. Simulation results show that the designed guidance law is able to guide a missile to accurately intercept a nonmaneuvering target or a maneuvering target with finite time, even if it escapes in a great and fast maneuver and the autopilot has a relatively large lag.

Sign in / Sign up

Export Citation Format

Share Document