scholarly journals Controller design for inverted pendulum stabilizing on equilibrium manifold based on vector field

2020 ◽  
Vol 86 (884) ◽  
pp. 19-00167-19-00167
Author(s):  
Masafumi OKADA ◽  
Yutaka OKAMOTO
2014 ◽  
Vol 71 (1) ◽  
Author(s):  
Hazem I. Ali

In this paper the design of robust stabilizing state feedback controller for inverted pendulum system is presented. The Ant Colony Optimization (ACO) method is used to tune the state feedback gains subject to different proposed cost functions comprise of H-infinity constraints and time domain specifications. The steady state and dynamic characteristics of the proposed controller are investigated by simulations and experiments. The results show the effectiveness of the proposed controller which offers a satisfactory robustness and a desirable time response specifications. Finally, the robustness of the controller is tested in the presence of system uncertainties and disturbance.


Author(s):  
Dan Boghiu ◽  
S. C. Sinha ◽  
Dan B. Marghitu

Abstract The fuzzy logic control of mechanical systems with periodic coefficients is considered. The controller design is illustrated through two examples, which include linear as well as nonlinear systems. For the linear case, a controller is designed such that a single inverted pendulum with a time periodic follower force is stabilized in the vertical position. As an example of the nonlinear system, the flap motion of a parametrically excited rotating elastic beam is considered. The controller is designed such that the deflection of the beam tip vanishes in a short period of time.


2011 ◽  
Vol 128-129 ◽  
pp. 50-53
Author(s):  
Qing He ◽  
Jin Kun Liu

In this paper, an adaptive sliding mode control (ASMC) method for a single inverted pendulum (IP) is proposed. The physical parameters are transformed into the model information, thus adaptive law for the IP can be designed with unknown physical parameters. By simulation and experiments, we found that the ASMC method can keep the IP in the upright position, with quick parameters adjustment and high degree of system robustness.


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