Sliding Mode Controller and Filter Applied to an Electrohydraulic Actuator System

Author(s):  
Shu Wang ◽  
Richard Burton ◽  
Saeid Habibi

A common problem pertaining to linear or nonlinear systems is the design of a combined robust control and estimation strategy that can effectively deal with noise and uncertainties. The variable structure control (VSC) and its special form of sliding mode control (SMC) demonstrate robustness with regard to uncertainties, although their performance can be severely degraded by noise. As such they can benefit from using state estimates obtained from filters. In this regard, this paper considers the use of a recently proposed robust state and parameter estimation strategy referred to as the variable structure filter (VSF) in conjunction with SMC. The contribution of this paper is a new strategy that combines sliding mode control with the variable structure filter. In the presence of bounded parametric uncertainties and noise, this combined method demonstrates robust stability both in terms of control and state estimation. Furthermore, the combined strategy can be used to achieve high regulation rates or short settling time. The combined VSF and SMC strategy is demonstrated by its application to a high precision hydrostatic system, referred to as the electrohydraulic actuator system.

Author(s):  
Shu Wang ◽  
Richard Burton ◽  
Saeid Habibi

A new robust state and parameter estimation strategy called the Variable Structure Filter (VSF) has recently been proposed and used for state and parameter estimation. A very common problem of linear stochastic systems is to design a combined robust control and estimation strategy, given system and noise uncertainties. Variable Structure Control (VSC) and its special form of Sliding Mode Control (SMC) show superb robustness. This paper proposes a new strategy involving the Sliding Mode Control and the Variable Structure Filter. Both the estimator and controller are based on the concepts of Variable Structure Systems (VSS). In the presence of bounded parametric uncertainties and noise, a robust stability is guaranteed. Further more, the combined strategy can be used to achieve high regulation rates or short settling times. The object of this paper is to introduce this combined VSF and SMC strategy and to demonstrate its application to a third order model of a high precision hydrostatic system, referred to as the Electrohydraulic Actuator System (EHA).


2014 ◽  
Vol 596 ◽  
pp. 584-589
Author(s):  
Xi Jie Yin ◽  
Jian Guo Xu

The sliding mode variable structure control method for brushless DC motors with uncertain external disturbances and unknown loads is studied. A neural sliding mode control scheme is proposed for reducing chattering of sliding mode control. A global sliding mode manifold is designed in this approach, which guarantees that the system states can be on the sliding mode manifold at initial time and the system robustness is increased. A radial basis function neural network (RBFNN) is applied to learn the maximum of unknown loads and external disturbances. Based on the neural networks, the switching control parameters of sliding mode control can be adaptively adjusted with uncertain external disturbances and unknown loads. Therefore, the chattering of the sliding mode controller is reduced. Simulation results proved that this control scheme is valid.


2010 ◽  
Vol 29-32 ◽  
pp. 2164-2169
Author(s):  
Ling Fei Xiao ◽  
Shao Dong Duan ◽  
Tao Shen

In this paper, a novel time-varying sliding mode control (SMC) algorithm based on sliding mode prediction for a class of discrete-time nonlinear uncertain coupled systems is presented. After giving a kind of time-varying sliding mode function, a sliding mode prediction model is used to predict the future information of sliding mode. By employing feedback correction and receding horizon optimization approaches which are extensively applied in predictive control strategy, the desired discrete-time variable structure control law is obtained. Under the influence of uncertainties whose boundaries are unknown, the closed-loop systems are proofed to be robustly stable. Numerical simulation results illustrate that compared with conventional SMC method, under the algorithm proposed in this paper, chattering is eliminated, the control signals have smaller peak values, and the closed-loop system possesses stronger robustness.


2014 ◽  
Vol 915-916 ◽  
pp. 439-443
Author(s):  
Sheng Yi Xuan ◽  
Chuan Xue Song ◽  
Guang Wei Meng

ABS(antilock brake system) is one of the most important active safety technology for modern vehicles which could enhance vehicle active safety. In this paper, an improved sliding mode control method based on reaching law has been proposed to solve the vibration problem in traditional sliding mode control. The ABS control strategy has been designed based on the sliding mode variable structure control. On this basis, the ABS single wheel depending on control strategy has been designed to ensure the braking stability. By hardware-in-loop simulation, the results demonstrate that ABS sliding mode variable structure control could enhance braking stability performance and improve the control effect on high friction and low friction road.


Actuators ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 154
Author(s):  
Bin Wang ◽  
Pengda Ren ◽  
Xinhao Huang

A piston piezoelectric (PZT) pump has many advantages for the use of light actuators. How to deal with the contradiction between the intermittent oil supplying and position control precision is essential when designing the controller. In order to accurately control the output of the actuator, a backstepping sliding-mode control method based on the Lyapunov function is introduced, and the controller is designed on the basis of establishing the mathematical model of the system. The simulation results show that, compared with fuzzy PID and ordinary sliding-mode control, backstepping sliding-mode control has a stronger anti-jamming ability and tracking performance, and improves the control accuracy and stability of the piezoelectric pump-controlled actuator system.


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