Optimization of Model Reference Adaptive Controller for the Inverted Pendulum System Using CCPSO and DE Algorithms

Bejarbaneh, Elham Yazdani; Bagheri, Ahmad; Bejarbaneh, Behnam Yazdani; Buyamin, Salinda

doi:10.3103/s0146411618040041

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…The output of each controller is added and given as control input to the RIP system where the design parameters of both controllers are properly tuned by intelligent algorithms, that is, PSOSCALF, PSO and WOA. It should be noted that two MRAC-PID controllers are not used in this paper since the robustness of the system is not as good as when one PID and one MRAC-PID controllers are used (Bejarbaneh et al, 2018). The initial angular position between the pendulum, θ 2 , and a vertical line are assumed 0.5 rad, and for other variable the initial conditions are considered as zero.…”

Section: Mrac-pid and Pid Design Strategymentioning

confidence: 99%

“…However, none of the above-mentioned controllers is able to precisely tune adaptation gains, especially for the high nonlinear plants. Generally, the performance of these adaptive controllers depends highly on the proper determination of adaptation gains that are usually tuned in an experimental way (Bejarbaneh et al, 2018; Zhao et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…One of these cases is to provide a tuning capability of MRAC controllers systematically. Bejarbaneh et al (2018) succeeded in optimizing the MRAC using the particle swarm optimization (PSO) and differential evolution (DE) algorithms and reported that the optimal design of adaptive controller using DE can more effectively improve the transient response of the inverted pendulum system against PSO-based adaptive controller.…”

Section: Introductionmentioning

confidence: 99%

“…Although, it suffers from two main deficiencies such as premature convergence and getting stuck in the local minima. During recent decades, many studies have indicated that extending of PSO algorithm can improve the efficiency of control systems (Bejarbaneh et al, 2018, 2019). In a recently published work, Chegini et al (2018), introduced a new hybrid PSO based on sine cosine algorithm and levy flight (PSOSCALF).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal design of adaptive and proportional integral derivative controllers using a novel hybrid particle swarm optimization algorithm

Bejarbaneh

Ahangarnejad

Bagheri

et al. 2020

Transactions of the Institute of Measurement and Control

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Controlling of a rotational inverted pendulum is considered as a challenging problem, mainly due to the system’s inherent nonlinear and unstable dynamics. In fact, the goal of this control is to maintain the pendulum vertically upward regardless of external disturbances. This paper aims to optimally design a model reference adaptive proportional integral derivative (PID) control for rotary inverted pendulum system based on a novel hybrid particle swarm optimization algorithm, combining sine cosine algorithm and levy flight distribution. Evaluation of the performance quality of the proposed adaptive controller is accomplished based on the stabilization and tracking control of rotary inverted pendulum system. In addition, two other PID controllers are designed to get a better understanding of the performance and robustness of the proposed controller. To make a complete comparison, the performance of the hybrid particle swarm optimization algorithm is examined against two other optimization techniques known as simple particle swarm optimization and whale optimization algorithm. Finally, the obtained simulation results demonstrate that the proposed optimal adaptive controller is superior to the other controllers, especially in terms of the transient response characteristics and the magnitude of control output signal.

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Section: Mrac-pid and Pid Design Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal design of adaptive and proportional integral derivative controllers using a novel hybrid particle swarm optimization algorithm

Bejarbaneh

Ahangarnejad

Bagheri

et al. 2020

Transactions of the Institute of Measurement and Control

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consequently, there is a need to employ the nature-inspired metaheuristic techniques (Okwu and Tartibu, 2021) to obtain optimal design parameters for the ISMC schemes. Among metaheuristic algorithms, PSO is gaining a lot of attention in the control community because of its simplicity, ease of implementation, and fast convergence in finding high-quality solutions (Bejarbaneh et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

PSO-Based Integral Sliding Mode Controller for Optimal Swing-Up and Stabilization of the Cart-Inverted Pendulum System

Shima

Bashir

2021

Nig. J. Technol. Dev.

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An integral sliding mode controller (ISMC) which employs particle swarm optimization (PSO) algorithm to search for optimal values of the parameters of the integral sliding manifold as well as the gains of the controller is proposed in this work. We considered the swing-up and stabilization of the cart-inverted pendulum system which is assumed to be affected by uncertainties. First, we determined the swing-up and stabilization conditions of the control system by using the internal dynamics of the cart-inverted pendulum system and sliding mode dynamics. A PSO algorithm is then used to search for the optimal values of the ISMC design parameters that satisfy the stabilization condition with the aim of improving the transient performance of the control system. To mitigate the chattering phenomenon, a saturation function of the integral sliding variable was used in the discontinuous control law. Simulation results on swing-up and stabilization of the cart-inverted pendulum system revealed improvement in transient behaviour by reducing settling time (by 52.61%), overshoots (by 45.56%) and required track length for cart movement (by 68.34%).

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ANN Based ANFIS controller Design Using Hybrid Meta-Heuristic Tuning Approach for Cart Inverted Pendulum System

Verma,

Valluru

2023

Multimed Tools Appl

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Optimization of Model Reference Adaptive Controller for the Inverted Pendulum System Using CCPSO and DE Algorithms

Cited by 7 publications

References 13 publications

Optimal design of adaptive and proportional integral derivative controllers using a novel hybrid particle swarm optimization algorithm

Optimal design of adaptive and proportional integral derivative controllers using a novel hybrid particle swarm optimization algorithm

PSO-Based Integral Sliding Mode Controller for Optimal Swing-Up and Stabilization of the Cart-Inverted Pendulum System

ANN Based ANFIS controller Design Using Hybrid Meta-Heuristic Tuning Approach for Cart Inverted Pendulum System

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