Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

Saleem, Omer; Rizwan, Mohsin; Mahmood-ul-Hasan, Khalid

doi:10.1080/00051144.2020.1864186

Cited by 8 publications

(11 citation statements)

References 27 publications

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“…The modified Riccati equation (expressed in Eq 24 ) uses the updated values of β to re-compute its solution after every sampling interval, and thus, yield a time-varying state-feedback gain vector. The structure of the STR employing the aforementioned adjustable-DoS (ADoS-STR) mechanism is illustrated in Fig 2 [ 64 ].…”

Section: Hierarchical Self-tuning-regulator Designmentioning

confidence: 99%

“…The online adaptation law for β is formulated by using a pre-calibrated continuous Hyperbolic-Secant-Function (HSF) that depends on the weighted sum of state-error variables [ 64 ]. The HSF is chosen because its waveform is continuous, bounded, and even-symmetric.…”

Section: Hierarchical Self-tuning-regulator Designmentioning

confidence: 99%

“…The HSF is chosen because its waveform is continuous, bounded, and even-symmetric. The shape of HSF’s waveform is calibrated according to the following rationale [ 64 ].…”

Section: Hierarchical Self-tuning-regulator Designmentioning

confidence: 99%

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An experimental comparison of different hierarchical self-tuning regulatory control procedures for under-actuated mechatronic systems

2021

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This paper presents an experimental comparison of four different hierarchical self-tuning regulatory control procedures in enhancing the robustness of the under-actuated systems against bounded exogenous disturbances. The proposed hierarchical control procedure augments the ubiquitous Linear-Quadratic-Regulator (LQR) with an online reconfiguration block that acts as a superior regulator to dynamically adjust the critical weighting-factors of LQR’s quadratic-performance-index (QPI). The Algebraic-Riccati-Equation (ARE) uses these updated weighting-factors to re-compute the optimal control problem, after every sampling interval, to deliver time-varying state-feedback gains. This article experimentally compares four state-of-the-art rule-based online adaptation mechanisms that dynamically restructure the constituent blocks of the ARE. The proposed hierarchical control procedures are synthesized by self-adjusting the (i) controller’s degree-of-stability, (ii) the control-weighting-factor of QPI, (iii) the state-weighting-factors of QPI as a function of “state-error-phases”, and (iv) the state-weighting-factors of QPI as a function of “state-error-magnitudes”. Each adaptation mechanism is formulated via pre-calibrated hyperbolic scaling functions that are driven by state-error-variations. The implications of each mechanism on the controller’s behaviour are analyzed in real-time by conducting credible hardware-in-the-loop experiments on the QNET Rotary-Pendulum setup. The rotary pendulum is chosen as the benchmark platform owing to its under-actuated configuration and kinematic instability. The experimental outcomes indicate that the latter self-adaptive controller demonstrates superior adaptability and disturbances-rejection capability throughout the operating regime.

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Section: Hierarchical Self-tuning-regulator Designmentioning

confidence: 99%

Section: Hierarchical Self-tuning-regulator Designmentioning

confidence: 99%

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An experimental comparison of different hierarchical self-tuning regulatory control procedures for under-actuated mechatronic systems

2021

Self Cite

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“…Theorem 1: Assume that the dynamical equation of rotary inverted pendulum be as ( 11)-( 14) and the PID sliding surface and control input are designed as (17) and (21). Then, the finitetime convergence of the planned sliding surface to the origin is proved and the stability control of the system is performed.…”

Section: Adaptive Super-twisting Pid Sliding Mode Controlmentioning

confidence: 99%

“…In addition, in the second subsystem, the main goal of control is the balancing of pendulum to be stand up-right [17][18][19][20]. Therefore, some control methods including proportional-integral-derivative (PID), linear quadratic regulator (LQR), linear quadratic Gaussian (LQG), sliding mode control (SMC), adaptive control, fuzzy logic and neural network techniques have been applied for both stability and balancing control of RIP systems [21][22][23][24][25]. In [26], LOR and LQG methods based on the fuzzy logic control 1 Corresponding author: Saleh Mobayen (mobayens@yuntech.edu.tw) technique has been proposed aimed at stability control of double-RIP system under perturbation.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Super-twisting Sliding Mode Stability Control for Underactuated Rotary Inverted Pendulum with Experimental Validation

Mofid

Alattas

Mobayen

2021

Preprint

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In this paper, an adaptive proportional-integral-derivative (PID) sliding mode control method combined with super-twisting algorithm is designed for the stabilization control of rotary inverted pendulum system in the appearance of exterior perturbation. The state-space model of rotary inverted pendulum in the presence of exterior disturbance is obtained. Then, the super-twisting PID sliding mode controller is designed for finite time stability control of this underactuated control system. The upper bounds of perturbation are presumed to be unknown; accordingly, the adaptive control procedure is taken to approximate the uncertain bound of the external disturbances. The stability control of rotary inverted pendulum system is proved by means of the Lyapunov stability theory. In order to validate accuracy and efficiency of the recommended control technique, some simulation outcomes are prepared and compared with other existing method. Moreover, experimental results are implemented to show the success of the proposed method.

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Design of Online Fuzzy Tuning LQR Controller Applied to Rotary Single Inverted Pendulum: Experimental Validation

Bekkar

Ferkous

2022

Arab J Sci Eng

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Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

Cited by 8 publications

References 27 publications

An experimental comparison of different hierarchical self-tuning regulatory control procedures for under-actuated mechatronic systems

An experimental comparison of different hierarchical self-tuning regulatory control procedures for under-actuated mechatronic systems

Robust Adaptive Super-twisting Sliding Mode Stability Control for Underactuated Rotary Inverted Pendulum with Experimental Validation

Design of Online Fuzzy Tuning LQR Controller Applied to Rotary Single Inverted Pendulum: Experimental Validation

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