scholarly journals Comparison Of Sliding Mode Controller And State Feedback Controller Having Linear Quadratic Regulator (Lqr) On A Two-Wheel Inverted Pendulum Robot: Design And Experiments

Author(s):  
Mikail S. Arani ◽  
Hamid Ebrahimi Orimi ◽  
Wen-Fang Xie ◽  
Henry Hong
2021 ◽  
Vol 2111 (1) ◽  
pp. 012006
Author(s):  
N Setiawan ◽  
G N P Pratama

Abstract The rotational inverted pendulum is an interesting subject for some researchers, especially control engineers. Its nonlinear and underactuated characteristic make it quite challenging to stabilize it. Hence, a proper control law is a must to make it stable. Here, in this paper, we present a control law using LQR (Linear-Quadratic Regulator) to stabilize the rotational inverted pendulum. The experiments are carried out by linearizing the model and simulate the response in MATLAB. The results show that the controller succeeds to stabilize the states of rotational inverted pendulum to their respective equilibrium points. Even more, it provides zero settling errors.


Author(s):  
Ishan Chawla ◽  
Vikram Chopra ◽  
Ashish Singla

AbstractFrom the last few decades, inverted pendulums have become a benchmark problem in dynamics and control theory. Due to their inherit nature of nonlinearity, instability and underactuation, these are widely used to verify and implement emerging control techniques. Moreover, the dynamics of inverted pendulum systems resemble many real-world systems such as segways, humanoid robots etc. In the literature, a wide range of controllers had been tested on this problem, out of which, the most robust being the sliding mode controller while the most optimal being the linear quadratic regulator (LQR) controller. The former has a problem of non-robust reachability phase while the later lacks the property of robustness. To address these issues in both the controllers, this paper presents the novel implementation of integral sliding mode controller (ISMC) for stabilization of a spatial inverted pendulum (SIP), also known as an x-y-z inverted pendulum. The structure has three control inputs and five controlled outputs. Mathematical modeling of the system is done using Euler Lagrange approach. ISMC has an advantage of eliminating non-robust reachability phase along with enhancing the robustness of the nominal controller (LQR Controller). To validate the robustness of ISMC to matched uncertainties, an input disturbance is added to the nonlinear model of the system. Simulation results on two different case studies demonstrate that the proposed controller is more robust as compared to conventional LQR controller. Furthermore, the problem of chattering in the controller is dealt by smoothening the controller inputs to the system with insignificant loss in robustness.


2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668427 ◽  
Author(s):  
Te-Jen Su ◽  
Shih-Ming Wang ◽  
Tsung-Ying Li ◽  
Sung-Tsun Shih ◽  
Van-Manh Hoang

The objective of this article is to optimize parameters of a hybrid sliding mode controller based on fireworks algorithm for a nonlinear inverted pendulum system. The proposed controller is a combination of two modified types of the classical sliding mode controller, namely, baseline sliding mode controller and fast output sampling discrete sliding mode controller. The simulation process is carried out with MATLAB/Simulink. The results are compared with a published hybrid method using proportional–integral–derivative and linear quadratic regulator controllers. The simulation results show a better performance of the proposed controller.


Author(s):  
Ishan Chawla ◽  
Ashish Singla

AbstractFrom the last five decades, inverted pendulum (IP) has been considered as a benchmark problem in the control literature due to its inherit nature of instability, non-linearity and underactuation. Its applicability in wide range of practical systems, demands the need of a robust controller. It is found in the literature that wide range of controllers had been tested on this problem, out of which the most robust being sliding mode controller while the most optimal being linear quadratic regulator (LQR) controller. The former has a problem of discontinuity and chattering, while the latter lacks the property of robustness. To address the robustness issue in LQR controller, this paper proposes a novel robust LQR-based adaptive neural based fuzzy inference system controller, which is a hybrid of LQR and fuzzy inference system. The proposed controller is designed and implemented on rotary inverted pendulum. Further, to validate the robustness of proposed controller to parametric uncertainties, pendulum mass is varied. Simulation and experimental results show that as compared to LQR controller, the proposed controller is robust to variations in pendulum mass and has shown satisfactory performance.


Author(s):  
Hossein Komijani ◽  
Saeed Masoumi Kazraji ◽  
Ehsan Baneshi ◽  
Milad Janghorban Lariche

In this paper a state feedback controller for tubular linear permanent magnet synchronous motor (TLPMSM) containing two gas springs, is presented. The proposed TLPMSM controller is used to control reciprocating motions of TLPMSM. The analytical plant model of TLPMSM is a multi-input multi-output (MIMO) system which is decoupled to some sub single-input single-output (SISO) systems, then, the sub SISO systems are converted to sub-state space models. Indeed, the TLPMSM state space model is decoupled to some sub-state spaces, and then, the gains of state feedback are calculated by linear quadratic regulation (LQR) method for each sub-state space separately. The controller decreases the distortions of the waveforms. The simulation results indicate the validity of the controller.


2018 ◽  
Vol 51 (4) ◽  
pp. 346-351 ◽  
Author(s):  
Rahman Bitirgen ◽  
Muhsin Hancer ◽  
Ismail Bayezit

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