Optimal adaptive guaranteed-cost H-infinity model reference controller design for nonlinear systems

Mhmood, Ali H.; Ali, Hazem I.

doi:10.1007/s40435-021-00846-9

Cited by 6 publications

(16 citation statements)

References 26 publications

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“…Thus, it exerts a strong gravitational pull on the nearby objects. In this instance, all matters, even light, are impotent to escape the gravity of the black hole, and they would disappear from existence [18,19].…”

Section: Black Hole Optimization (Bho) Algorithmmentioning

confidence: 97%

“…( 11) shows that the system has mismatched perturbations in the two upper subsystems (𝑅 ̇𝑟(𝑡) and 𝐼 ̇𝑟(𝑡)). Such perturbations cannot be directly compensated by the control input unless the system model is rewritten in an equivalent controllable structure, where the matching conditions are relaxed, and the nonlinearity and uncertainty (system perturbations) appear in the same subsystem channel of 𝛽(𝑢(𝑡)) [18][19][20]. Thus, a state variable transformation is applied using the following diffeomorphism mapping [12,[18][19][20]:…”

Section: Optimal Nonlinear Robust Controller Designmentioning

confidence: 99%

“…After initialization, the following steps for every iteration outline the BHO procedure, as shown in Fig. 1 [18,19]:…”

Section: Black Hole Optimization (Bho) Algorithmmentioning

confidence: 99%

“…Firstly, it has a straightforward framework that makes it simpler to formulate. Secondly, it is devoid of parameter tuning perplexities [18,19].…”

Section: Black Hole Optimization (Bho) Algorithmmentioning

confidence: 99%

“…Since the end of 2019, the planet has been witnessing an outbreak of coronavirus disease (COVID- 19), which was first detected on 31 December 2019 in Wuhan, China. According to reports, the disease is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can spread widely in crowded places and gatherings, where individuals devote most of their time [1].…”

Section: Introductionmentioning

confidence: 99%

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WITHDRAWN: Control of the COVID-19 System by Vaccination Using a New Control Engineering Technique

Ali

Mhmood

2022

Preprint

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In this work, a novel control engineering method is proposed to achieve a control strategy by vaccination for the COVID-19 epidemic. A proper mathematical model with vaccination control is developed for the COVID-19 system based on the Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiological model after conducting some analyses and assumptions that reflect the COVID-19 features. Then, the proposed control law is designed using the feedback linearization approach and the H-infinity control framework. In addition, a model reference control is incorporated to ensure that satisfactory time responses are obtained. The Black Hole Optimization (BHO) technique is used to attain the optimality of the proposed control method. Following that, the reported statistics and vaccination plan of the Lombardy region of Italy are utilized to assess the effectiveness of the proposed control law. Ultimately, the simulation results illustrate that the proposed control law can effectively control the COVID-19 system and correctly perform the vaccination plan by tackling the system’s nonlinearity and uncertainty and realizing elegant asymptotic tracking characteristics with reasonable control effort.

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Section: Black Hole Optimization (Bho) Algorithmmentioning

confidence: 97%

Section: Optimal Nonlinear Robust Controller Designmentioning

confidence: 99%

“…After initialization, the following steps for every iteration outline the BHO procedure, as shown in Fig. 1 [18,19]:…”

Section: Black Hole Optimization (Bho) Algorithmmentioning

confidence: 99%

“…Firstly, it has a straightforward framework that makes it simpler to formulate. Secondly, it is devoid of parameter tuning perplexities [18,19].…”

Section: Black Hole Optimization (Bho) Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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WITHDRAWN: Control of the COVID-19 System by Vaccination Using a New Control Engineering Technique

Ali

Mhmood

2022

Preprint

Self Cite

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Adaptive nonlinear robust lead compensator design for a class of uncertain nonlinear systems

Mhmood,

Rakan

2024

Int. J. Dynam. Control

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Advanced Flowrate Control of Petroleum Products in Transportation: An Optimized Modified Model Reference PID Approach

Yaseen,

Mhmood,

Subhi

et al. 2023

Journal of Robotics and Control

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Efficient flowrate control is paramount for the seamless operation and reliability of petroleum transportation systems, where precise control of fluid movement ensures not only operational efficiency but also safety and cost-effectiveness. The main aim of this paper is to develop a highly effective modified model reference PID controller, tailored to ensure optimal flowrate control of petroleum products throughout their transportation. Initially, the petrol transportation process is analyzed to establish a suitable mathematical model based on vital factors like pipeline diameter, length, and pump attributes. However, using a basic first-order time delay model for petrol transportation systems is limiting due to inaccuracies, variable delay issues, safety oversights, and real-time control complexities. To improve this, the delay portion is approximated as a third-order transfer function to better reflect complex physical conditions. Subsequently, the PID controller is synthesized by modifying its structure to address flowrate control issues. These modifications primarily focus on the controller’s derivative component, involving the addition of a first-order filter and alterations to its structure. To optimize the proposed controller, the genetic, black hole, and zebra optimization techniques are employed, aiming to minimize an integral time absolute error cost function and ensure that the outlet flow of the controlled system closely follows the response of an appropriate reference model. They are chosen for their proficiency in complex optimization to enhance the controller's effectiveness by optimizing parameters within constraints, adapting to system dynamics, and ensuring optimal conditions. Through simulations, it is demonstrated that the proposed controller significantly enhances the stability and efficiency of the control system, while maintaining practical control signals. Moreover, the proposed modifications and intelligent tuning of the PID controller yield remarkable improvements compared to previous related work, resulting in a 36% reduction in rise time, a 63% reduction in settling time, an 80% reduction in overshoot, and a 98% reduction in cost value.

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Optimal adaptive guaranteed-cost H-infinity model reference controller design for nonlinear systems

Cited by 6 publications

References 26 publications

WITHDRAWN: Control of the COVID-19 System by Vaccination Using a New Control Engineering Technique

WITHDRAWN: Control of the COVID-19 System by Vaccination Using a New Control Engineering Technique

Adaptive nonlinear robust lead compensator design for a class of uncertain nonlinear systems

Advanced Flowrate Control of Petroleum Products in Transportation: An Optimized Modified Model Reference PID Approach

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