Swing up and stabilization control experiments for a rotary inverted pendulum&amp;#x2014; An educational comparison

Özbek, Necdet Sinan; Efe, Mehmet Önder

doi:10.1109/icsmc.2010.5641962

Cited by 14 publications

(5 citation statements)

References 12 publications

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“…The fuzzy control technique, which has a simple design and robust performance characteristics, has been successfully applied in the control of various systems, particularly those with model uncertainty, unknown disturbance and nonlinear dynamics (Eker and Torun, 2006;Özbek and Efe, 2010). Up to now various applications have been reported (Bai et al, 2016;Rajaraajeswari et al, 2017;Xiao et al, 2017).…”

Section: Design Technique 3: Sp-based Fractional Fuzzy Pi Controlmentioning

confidence: 99%

Experimental evaluation of various modified Smith predictor-based fractional order control design strategies in control of a thermal process with time delay

Özbek

�°

Eker

2019

IJES

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In this study, a number of modified Smith predictor (SP)-based fractional order control strategies are investigated experimentally on a thermal process. Controller design methods and tuning strategies are elaborated step by step. Further, control strategies are discussed in relation to design specifications, control cost, implementation issues, and operating modes encountered in practice. Performance comparison is presented via several illustrations and numerical measures. Particular attention is paid to the tracking precision, quality of the control signal, robustness against disturbances and energy efficiency. Complementary comments are addressed based on merits and demerits of the each control technique.

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Section: Design Technique 3: Sp-based Fractional Fuzzy Pi Controlmentioning

confidence: 99%

Experimental evaluation of various modified Smith predictor-based fractional order control design strategies in control of a thermal process with time delay

Özbek

�°

Eker

2019

IJES

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“…Over the past few decades, it has witnessed the development of various controllers for the stabilization and tracking control of RIP systems, such as proportional–integral–derivative (PID) controller (Hassanzadeh and Mobayen, 2011), sliding mode controller (SMC) (Khanesar et al, 2007; Özbek and Efe, 2010), fuzzy logic controller (FLC) (Dominik, 2011), linear–quadratic regulator (LQR) controller (Abdullah et al, 2021; Artale et al, 2017) and model reference adaptive control PID (MRAC-PID) controller (Bejarbaneh et al, 2020). The common feature of these controllers is that their derivation relies entirely on the nonlinear transformation of the system’s integer-order state variables or on the integer-order gradient-based optimization of the system’s energy function.…”

Section: Introductionmentioning

confidence: 99%

Optimal fractional-order proportional–integral–derivative control enabling full actuation of decomposed rotary inverted pendulum system

Yang

Zhang

Voyles

2023

Transactions of the Institute of Measurement and Control

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Allowing for a “virtual” full actuation of a rotary inverted pendulum (RIP) system with only a single physical actuator has been a challenging problem. In this paper, a hybrid control scheme that involves a pole-placement feedback controller and an optimal proportional–integral–derivative (PID) or fractional-order PID (FOPID) controller is proposed to simultaneously enable the tracking control of the rotary arm and the stabilization of the pendulum arm in an input–output feedback linearized RIP system. The PID controller is optimized first with the particle swarm optimization (PSO) to obtain three optimal gains, and then the other two parameters of the FOPID controller are optimized with the PSO. Compared to the optimized PID controller, the optimized FOPID controller improves the tracking and stabilizing accuracy by 53% and 29%, respectively, and demonstrates better adaptability for tracking different reference signals. Moreover, the hybrid FOPID controller exhibits 74.8% and 53% higher tracking accuracy than previous optimized model reference adaptive control PID (MRAC-PID) and linear–quadratic regulator (LQR) controllers, respectively. The proposed hybrid controllers are also digitized with different rules and sampling times, showing a closer performance between the discrete-time and continuous-time hybrid controllers under smaller sampling times.

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“…Nowadays, there are many configurations of inverted pendulums. The most common pendulums are linear, rotational (Ahangar-Asr et al, 2011), (Ozbek et al, 2010), single (Astrom et al, 2000), double (Sang et al, 2011) or triple (Zhangn et al, 2017) and pendulums on a cart (Hui et al, 2016). Many analyses on inverted pendulums are conducted because of similarity to such objects as robots and rockets (Boubaker, 2012), (Hovingh et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Electro Pneumatic Control System for Inverted Pendulum

Popławski

Ambroziak

Kondratiuk

2020

Acta Mechanica Et Automatica

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The paper concerns the inverted pendulum control system with using pneumatic cylinder. A mathematical model of the pendulum used to derive the LQG controller was presented. Prepared laboratory stand was presented and described in detail. The main purpose of the work was experimental researches. A number of control process tests were conducted with variable model parameters such as additional mass, injected disturbances and so on. The results were shown on the time plots of the control object states.

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Swing up and stabilization control experiments for a rotary inverted pendulum— An educational comparison

Cited by 14 publications

References 12 publications

Experimental evaluation of various modified Smith predictor-based fractional order control design strategies in control of a thermal process with time delay

Experimental evaluation of various modified Smith predictor-based fractional order control design strategies in control of a thermal process with time delay

Optimal fractional-order proportional–integral–derivative control enabling full actuation of decomposed rotary inverted pendulum system

Electro Pneumatic Control System for Inverted Pendulum

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