2021
DOI: 10.3390/s22010243
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Stabilization of the Cart–Inverted-Pendulum System Using State-Feedback Pole-Independent MPC Controllers

Abstract: In this paper, a pole-independent, single-input, multi-output explicit linear MPC controller is proposed to stabilize the fourth-order cart–inverted-pendulum system around the desired equilibrium points. To circumvent an obvious stability problem, a generalized prediction model is proposed that yields an MPC controller with four tuning parameters. The first two parameters, namely the horizon time and the relative cart–pendulum weight factor, are automatically adjusted to ensure a priori prescribed system gain … Show more

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Cited by 9 publications
(4 citation statements)
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“…After one day of running, the indoor temperature returned to around 18℃. The four operation optimization schemes are electricity price operation scheme, coefficient of performance operation scheme [6], fixed period operation scheme, and electricity price/coefficient of performance operation scheme. The four optimized operation schemes are shown in When the electricity price/coefficient of performance is less than 0.2, improve the heating intensity; when the electricity price/coefficient of performance is greater than 0.2, reduce the heating intensity…”
Section: Optimization Of Indoor Heating Scheme Based On Time Of Use E...mentioning
confidence: 99%
“…After one day of running, the indoor temperature returned to around 18℃. The four operation optimization schemes are electricity price operation scheme, coefficient of performance operation scheme [6], fixed period operation scheme, and electricity price/coefficient of performance operation scheme. The four optimized operation schemes are shown in When the electricity price/coefficient of performance is less than 0.2, improve the heating intensity; when the electricity price/coefficient of performance is greater than 0.2, reduce the heating intensity…”
Section: Optimization Of Indoor Heating Scheme Based On Time Of Use E...mentioning
confidence: 99%
“…Among all underactuated systems, cartpole system has been a classic benchmark model that absorbs uncertainty, coupling, nonlinearity, non-minimum phase, multivariable and instability, which encompasses a majority of other underactuated systems. Therefore, the research into cartpole system has a fundamental significance to gain insight into other system dynamics [4].…”
Section: Introductionmentioning
confidence: 99%
“…Due to the use of multi-step prediction, rolling optimization, feedback correction, and other control strategies, the model predictive control algorithm has advantages such as good control effects and strong robustness [43,44]. In [45], a single MPC is designed to stabilize the CIPS. However, in the design of this single MPC, the dynamic equation of the CIPS is overly simplified as a linearized system around the upright position of the SIP.…”
Section: Introductionmentioning
confidence: 99%