Robust Control Law for Pneumatic Artificial Muscles

Author(s):  
Jonathon E. Slightam ◽  
Mark L. Nagurka

This paper presents a modified integral sliding surface, sliding mode control law for pneumatic artificial muscles. The cutoff frequency tuning parameter λ is squared to increase the gradient from absement (integral of position) to position and higher derivatives to reflect the more dominant terms in the actuator dynamics. The sliding mode controller is coupled with proportional and integral action compensation. The control system is sufficiently robust so that use of an observer and input-output feedback linearization are not required. Closed-loop control experiments are compared with traditional sliding mode controller designs presented in the literature for pneumatic artificial muscles. Experiments include the tracking of sinusoidal waves at 0.5 and 1 Hz, tracking of square-like waves with seventh-order trajectory transitions at a rate of 0.2 Hz without and with a steady-state period of 10 seconds, as well as a step input response. These experiments indicate that the control law provides similar bandwidth, tracking, and steady-state performance as approaches requiring nonlinear feedback and model observation for pneumatic artificial muscles. Experiments demonstrate an accuracy of 50 μm at steady-state with no overshoot and maximum tracking errors less than 0.4 mm for smooth square-like trajectories.

2021 ◽  
Vol 233 ◽  
pp. 01051
Author(s):  
Tianze Miao ◽  
Xiaona Liu ◽  
Siyuan Liu ◽  
Lihua Wang

The bi-directional DC / DC converter in DC microgrid is a typical nonlinear system which has large voltage disturbance during lead accumulator charging and discharging. In order to solve the problem of voltage disturbance, the linearization of the converter is realized by exact feedback linearization, and the sliding mode controller is designed by using exponential approximation law. The simulation results show that the method has fast response speed, strong anti-interference ability and good steady-state characteristics.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
P. Ahmadi ◽  
M. Golestani ◽  
S. Nasrollahi ◽  
A. R. Vali

A combination of two nonlinear control techniques, fractional order sliding mode and feedback linearization control methods, is applied to 3-DOF helicopter model. Increasing of the convergence rate is obtained by using proposed controller without increasing control effort. Because the proposed control law is robust against disturbance, so we only use the upper bound information of disturbance and estimation or measurement of the disturbance is not required. The performance of the proposed control scheme is compared with integer order sliding mode controller and results are justified by the simulation.


2020 ◽  
Vol 14 ◽  
Author(s):  
Gang Liu ◽  
Dong Qiu ◽  
Xiuru Wang ◽  
Ke Zhang ◽  
Huafeng Huang ◽  
...  

Background: The PWM Boost converter is a strongly nonlinear discrete system, especially when the input voltage or load varies widely, therefore, tuning the control parameters of which is a challenge work. Objective: In order to overcome the issues, particle swarm optimization (PSO) is employed for tuning the parameters of a sliding mode controller of a boost converter. Methods: Based on the analysis of the Boost converter model and its non-linear characteristics, a mathematic model of a boost converter with a sliding mode controller is built firstly. Then, the parameters of the Boost controller are adjusted based on the integrated time and absolute error (ITAE), integral square error (ISE) and integrated absolute error (IAE) indexes by PSO. Results: Simulation verification was performed, and the results show that the controllers tuned by the three indexes all have excellent robust stability. Conclusion: The controllers tuned by ITAE and ISE indexes have excellent steady-state performance, but the overshoot is large during the startup. The controller tuned by IAE index has better startup performance and slightly worse steady-state performance.


Sign in / Sign up

Export Citation Format

Share Document