Synergistic speed control strategy for PMDC motor

Saleem, Omer; Omer, Urwa

doi:10.1109/inmic.2017.8289465

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…The integral control tend to improve the pendulum's position-regulation accuracy and robustness against state fluctuations [26]. The integral control law is expressed as,…”

Section: Plos Onementioning

confidence: 99%

A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights

2023

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This article presents flexible online adaptation strategies for the performance-index weights to constitute a variable structure Linear-Quadratic-Integral (LQI) controller for an under-actuated rotary pendulum system. The proposed control procedure undertakes to improve the controller’s adaptability, allowing it to flexibly manipulate the control stiffness which aids in efficiently rejecting the bounded exogenous disturbances while preserving the system’s closed-loop stability and economizing the overall control energy expenditure. The proposed scheme is realized by augmenting the ubiquitous LQI controller with an innovative online weight adaptation law that adaptively modulates the state-weighting factors of the internal performance index. The weight adaptation law is formulated as a pre-calibrated function of dissipative terms, anti-dissipative terms, and model-reference tracking terms to achieve the desired flexibility in the controller design. The adjusted state weighting factors are used by the Riccati equation to yield the time-varying state-compensator gains.

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“…The integral control tend to improve the pendulum's position-regulation accuracy and robustness against state fluctuations [26]. The integral control law is expressed as,…”

Section: Plos Onementioning

confidence: 99%

A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights

2023

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“…The fixed Kalman gain vector calculated offline in this research is K = −6.18 137.42 −4.42 18.81 . The linear control law in (11) is also retrofitted with additional control terms associated with the integral-of-error in α and θ, in order to damp the angular fluctuations while tracking the reference [37]. The consolidated integral controller is expressed in (12)…”

Section: Primary State-feedback Controllermentioning

confidence: 99%

Indirect Adaptive State-Feedback Control of Rotary Inverted Pendulum Using Self-Mutating Hyperbolic-Functions for Online Cost Variation

Saleem

Mahmood-ul-Hasan

2020

IEEE Access

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This paper presents the development of an indirect adaptive state-feedback controller to improve the disturbance-rejection capability of under-actuated multivariable systems. The ubiquitous Linear-Quadratic-Regulator (LQR) is employed as the baseline state-feedback controller. Despite its optimality, the LQR lacks robustness against parametric uncertainties. Hence, the main contribution of this paper is to devise and retrofit the LQR with a stable online gain-adjustment mechanism that dynamically adjusts the state weighting-coefficients of LQR's quadratic cost-function via state-error dependent nonlinear-scaling functions. An original self-mutating phase-based adaptive modulation scheme is systematically formulated in this paper to self-adjust the state weighting-coefficients. The scheme employs pre-calibrated secanthyperbolic-functions whose waveforms are dynamically reconfigured online based on the variations in magnitude and polarity of state-error variables. This augmentation dynamically alters the solution of the Riccati-Equation which modifies the state-feedback gains online. The proposed adaptation flexibly manipulates the system's control effort as the response converges to or diverges from the reference. The efficacy of proposed adaptive controller is validated by conducting hardware-in-the-loop experiments to vertically stabilize the QNET 2.0 Rotary Pendulum system. As compared to the standard LQR, the proposed adaptive controller renders rapid transits in system's response with improved damping against oscillations, while maintaining its asymptotic-stability, under bounded exogenous disturbances. INDEX TERMS Hyperbolic functions, linear quadratic regulator, cost-function, rotary inverted pendulum, self-tuning control, state weighting-coefficients.

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“…where K c is the adaptive state-feedback gain vector that is adjusted online with respect to variations in the state-trajectories. The closed-loop representation of the actual as well as the reference system can be expressed according to (17) and (18).…”

Section: Model Reference Adaptive Lqi Controllermentioning

confidence: 99%

“…The numerical integration causes the accumulation of noise which leads to actuator saturation or wind-up. Moreover, the performance of statespace controllers gets degraded by modelling errors [16,17]. The self-tuning adaptive linear controllers tend to improve the robustness of dynamical systems against the problems mentioned above [18].…”

Section: Introductionmentioning

confidence: 99%

Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions

et al. 2019

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The main contribution of this paper is to formulate a robust-adaptive and stable state-space speed control strategy for DC motors. The linear-quadratic-integral (LQI) controller is utilized as the baseline controller for optimal speed-regulation, accurate reference-tracking and elimination of steady-state fluctuations in the motor's response. To reject the influence of modelling errors, the LQI controller is augmented with a Lyapunov-based model reference adaptation system (MRAS) that adaptively modulates the controller gains while maintaining the asymptotic stability of the controller. To further enhance the system's robustness against parametric uncertainties, the adaptation gains of MRAS online gain-adjustment law are dynamically adjusted, after every sampling interval, using smooth hyperbolic functions of motor's speed-error. This modification significantly improves the system's response-speed and damping against oscillations, while ensuring its stability under all operating conditions. It dynamically re-configures the control-input trajectory to enhance the system's immunity against the detrimental effects of random faults occurring in practical motorized systems such as bounded impulsive-disturbances, modelling errors, and abrupt load-torque variations. The efficacy of the proposed control strategy is validated by conducting credible hardware-in-the-loop experiments on QNET 2.0 DC Motor Board. The experimental results successfully validate the superior tracking accuracy and disturbance-rejection capability of the proposed control strategy as compared to other controller variants benchmarked in this article.

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Synergistic speed control strategy for PMDC motor

Cited by 3 publications

References 20 publications

A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights

A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights

Indirect Adaptive State-Feedback Control of Rotary Inverted Pendulum Using Self-Mutating Hyperbolic-Functions for Online Cost Variation

Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions

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