scholarly journals Adaptive Fault-Tolerant Control for Stratospheric Airships with Full-State Constraints, Input Saturation, and External Disturbances

2021 ◽  
Author(s):  
Huabei Gou ◽  
Ming Zhu ◽  
Zewei Zheng ◽  
Xiao Guo ◽  
Wenjie Lou ◽  
...  
Keyword(s):  
State Constraints ◽  
Fault Tolerant ◽  
Input Saturation ◽  
Fault Tolerant Control ◽  
External Disturbances ◽  
Full State ◽  
Full State Constraints

scholarly journals Distributed Robust Tracking Control for Multiple Euler–lagrange Systems With Full-state Constraints and Input Saturation via Event-triggered Control

2021 ◽  
Author(s):  
Haitao liu ◽  
Guangshuo Du ◽  
Xuehong Tian ◽  
Lanping Zou
Keyword(s):  
Tracking Control ◽  
State Constraints ◽  
Input Saturation ◽  
Communication Delay ◽  
External Disturbances ◽  
Position Information ◽  
Delay Function ◽  
Full State ◽  
Full State Constraints ◽  
Event Triggered

Abstract In this paper, the issue of distributed tracking control is studied for multiple Euler–Lagrange systems in presence of external disturbances and input saturation. Specifically, the full-state constraints, input saturation, communication delay, and unmeasured velocity are also considered simultaneously. Firstly, an adaptive distributed state observer is introduced to obtain the leader's time-varying position information, at the same time, a delay function is employed to compensate the communication delay. Moreover, the event-triggered control scheme is developed to reduce communication source and computation load, and the anti-saturation compensation algorithm is exploited to compensate for the influence of system saturation. Thirdly, an adaptive law is designed to offset external disturbances. What’s more, the high-gain observer is used to estimate the unmeasured velocities. Theorem analysis shows that the system errors can converge to zero. Finally, numerical simulations are present to verify the effectiveness of the proposed control strategy.

scholarly journals Adaptive Neural Fault-Tolerant Control for the Yaw Control of UAV Helicopters with Input Saturation and Full-State Constraints

2020 ◽  
Vol 10 (4) ◽  
pp. 1404 ◽  
Author(s):  
Qiang Zhang ◽  
Xia Chen ◽  
Dezhi Xu
Keyword(s):  
Nonlinear System ◽  
State Constraints ◽  
Fault Tolerant ◽  
Input Saturation ◽  
Robust Adaptive Control ◽  
Lyapunov Theory ◽  
Parameter Uncertainties ◽  
Yaw Control ◽  
Full State ◽  
Full State Constraints

In this paper, an adaptive neural fault-tolerant tracking control scheme is presented for the yaw control of an unmanned-aerial-vehicle helicopter. The scheme incorporates a non-affine nonlinear system that manages actuator faults, input saturation, full-state constraints, and external disturbances. Firstly, by using a Taylor series expansion technique, the non-affine nonlinear system is transformed into an affine-form expression to facilitate the desired control design. In comparison with previous techniques, the actuator efficiency is explicit. Then, a neural network is considered to approximate unknown nonlinear functions, and a time-varying barrier Lyapunov function is employed to prevent transgression of the full-state variables using a backstepping technique. Robust adaptive control laws are designed to handle parameter uncertainties and unknown bounded disturbances to cut down the number of learning parameters and simplify the computational burden. Moreover, an auxiliary system is constructed to guarantee the pitch angle of the UAV helicopter yaw control system to satisfy the input constraint. Uniform boundedness of all signals in a closed-loop system is ensured via Lyapunov theory; the tracking error converges to a small neighborhood near zero. Finally, when the numerical simulations are applied to a yaw control of helicopter, the adaptive neural controller demonstrates the effectiveness of the proposed technique.

scholarly journals Prescribed Performance Control of Marine Surface Vessel Trajectory Tracking in Finite-Time with Full-State Constraints and Input Saturation

2021 ◽  
Vol 9 (8) ◽  
pp. 866
Author(s):  
Xiyun Jiang ◽  
Yuanhui Wang
Keyword(s):  
Finite Time ◽  
State Constraints ◽  
Tracking Error ◽  
Input Saturation ◽  
Prescribed Performance ◽  
Full State ◽  
Marine Surface ◽  
Surface Vessel ◽  
Full State Constraints ◽  
Function Matrix

This manuscript mainly solves a fully actuated marine surface vessel prescribed performance trajectory tracking control problem with full-state constraints and input saturation. The entire control design process is based on a backstepping technique. The prescribed performance control is introduced to embody the analytical relationship between the transient performance and steady-state performance of the system and the parameters. Meanwhile, a new finite time performance function is introduced to ensure that the performance of the system tracking error is constrained within the preset constraints in finite time, and the full-state constraints problem of the system can be solved simultaneously in the entire control design, at the same time without introducing additional theory and parameters. To solve the non-smooth input saturation function matrix is not differentiable, the smooth function matrix is introduced to replace the non-smooth characteristics. Combining the Moore-Penrose generalized inverse matrix to design the virtual control law, the dynamic surface control is introduced to avoid the complicated virtual control derivation process, and finally the actual control law is designed using the properties of Nussbaum function. In addition, in view of the uncertainties in the system, a fractional disturbance observer is designed to estimate it. With the proposed control, the full-state will never be violated constraints, and the system tracking error satisfies transient and steady-state performance. Compared with other methods, the simulation results show the effectiveness and advantages of the proposed method.

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