Design and application of models reference adaptive control  (MRAC) on ball and beam

Romdlony, Muhammad Zakiyullah; Rosa, Muhammad Ridho; Syamsudin, Edwin Muhammad Puji; Trilaksono, Bambang Riyanto; Wibowo, Agung Surya

doi:10.14203/j.mev.2022.v13.15-23

Cited by 2 publications

(1 citation statement)

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“…While an adaptive control was implemented in Ref. [19] for the BBS. Linear state-feedback model reference adaptive control (MRAC) was used in synchronizing the states of the BBS with the given reference model.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of the Ball and Beam System using Linear Quadratic Regulator Controller

Umar¹,

Mu’azu²,

Haruna³

et al. 2023

PID Control for Linear and Nonlinear Industrial Processes

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This paper proposes the performance comparison of a linear quadratic regulator (LQR) controller for the ball and beam system (BBS). The BBS is a standard benchmark control system, which has two degree-of-freedom (2 DOF). It is an open loop and a highly nonlinear unstable system. This makes its parameter difficult to be estimated accurately, hence designing a controller for it is a challenging task. MatheThe BBS was modelled using Euler–Lagrange modeling technique, while the LQR controller was used for the stabilization of the ball on the beam. Simulation was done in MATLAB/Simulink 2022b environment, and the results simulated showed that for the two weighting matrices (Q and R), the state weighting matrix had a higher penalty on the ball displacement, ball velocity, beam angle, and beam angular velocity at lower values of Q. For the state weighting matrix had a better effect of penalty performance on the BBS with lower values. Also, as the diagonal element of the state weighting matrix Q increases from 0.1 to 20, the values of the optimal controller K increase, the reduced Ricatti matrix P increases, and the estimated eigenvalues E reduce. This implies that the ball displacement, ball velocity, beam angle, and beam angular velocity are better at lower values of Q.

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Section: Introductionmentioning

confidence: 99%