Design and implementation of a Model-Free Fractional Order Intelligent PI Fractional Order Sliding Mode Controller for water level tank system

Ardjal, Aghiles; Bettayeb, Maâmar; Mansouri, Rachid; Zouak, Belkacem

doi:10.1016/j.isatra.2021.08.042

Cited by 12 publications

(5 citation statements)

References 46 publications

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“…In [10], the topic of tuning FO controllers for industrial use was examined. However, for complicated nonlinear systems, these approaches require a precise dynamic model, which is not accessible [11,12]. Conversely, no model or process identification is present in model-free tuning techniques [11].…”

Section: Introductionmentioning

confidence: 99%

Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization

Hamza

2024

Algorithms

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Due to increased complexity and interactions between various subsystems, higher-order MIMO systems present difficulties in terms of stability and control performance. This study effort provides a novel, all-encompassing method for creating a decentralized fractional-order control technique for higher-order systems. Given the greater number of variables that needed to be optimized for fractional order control in higher-order, multi-input, multi-output systems, the modified flower pollination optimization algorithm (MFPOA) optimization technique was chosen due to its rapid convergence speed and minimal computational effort. The goal of the design is to improve control performance. Maximum overshoot (Mp), rising time (tr), and settling time (ts) are the performance factors taken into consideration. The MFPOA approach is used to improve the settings of the proposed decentralized fractional-order proportional-integral-derivative (FOPID) controller. By exploring the parameter space and converging on the best controller settings, the MFPOA examines the parameter space and satisfies the imposed constraints by maintaining system stability. To evaluate the suggested approach, simulation studies on two systems are carried out. The results show that by decreasing the loop interactions between subsystems with improved stability, the decentralized control with the MFPOA-based FOPID controller provides better control performance.

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Section: Introductionmentioning

confidence: 99%

Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization

Hamza

2024

Algorithms

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“…Several studies have investigated the use of FOSMC for chemical processes. In general, these studies have shown that FOSMC can improve the performance and robustness of control systems for chemical processes; from them, we can highlight. − Therefore, the future of FOSMC for chemical processes is promising, and it is becoming a more widely used control technique for chemical processes as the theory of fractional calculus and sliding mode control continues to develop.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Control Framework for Chemical Processes with Long Time Delay: Theory and Experiments

Di Teodoro,

Herrera,

Rincon

et al. 2024

ACS Omega

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This paper proposes a hybrid control framework based on internal model concepts, sliding mode control methodology, and fractional-order calculus theory. As a result, a modified Smith predictor (SP) is proposed for nonlinear systems with significant delays. The particular predictive approach enhances the sliding mode control (SMC) controller's transient responses for dead-time processes, and the SMC gives the predictive structure robustness for model mismatches by combining the previous methods with fractional order concepts; the result is a dynamical sliding mode controller. A numerical example is considered to evaluate the performance of the proposed approach, where a step change, external disturbance, and parametric uncertainty test are performed. A real application in the TCLab Arduino kit is presented; the proposed method presented good performance with a little amount of chattering, and in the disturbance rejection case, the overshoot increased with an aggressive response; in both cases, better tuning parameters can improve the process response and the controller action.

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“…In earlier days, industries used to regulate the pressure through traditional control techniques, for example, proportional integral (PI) or proportional integral derivative (PID). Ardjal et al [28] proposed a combination of control methods, which are model free controller, Fractional-order proportional integral controller, and fractional order sliding mode controller, which uplift the MFC algorithm with the term MF-FOiPI-FOSMC called Model Free-Fractional Order Intelligent Proportional Integral-Fractional Order Sliding Mode Controller. However, results of the traditional control plans are only appropriate for simple systems with a definite operating interval and not appropriate for disturbance in load and constant variations in set points [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Construction and Evaluation of a Control Mechanism for Fuzzy Fractional-Order PID

Al‐Dhaifallah

2022

Applied Sciences

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In this research, a control mechanism for fuzzy fractional-order proportional integral derivatives was suggested (FFOPID). The fractional calculus application has been used in different fields of engineering and science and showed to be improved in the past few years. However, there are few studies on the implementation of the fuzzy fractional-order controller for control in real time. Therefore, for an experimental pressure control model, a fractional order PID controller with intelligent fuzzy tuning was constructed and its results were calculated through simulation. To highlight proposed control scheme advantages, the performances of the controller were inspected under load disturbances and variations in set-point conditions. Furthermore, with classical PID control schemes and fractional order proportional integral derivative (FOPID), a comparative study was made. It is revealed from the results that the suggested control scheme outclasses other categories of the control schemes.

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Design and implementation of a Model-Free Fractional Order Intelligent PI Fractional Order Sliding Mode Controller for water level tank system

Cited by 12 publications

References 46 publications

Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization

Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization

A Hybrid Control Framework for Chemical Processes with Long Time Delay: Theory and Experiments

Construction and Evaluation of a Control Mechanism for Fuzzy Fractional-Order PID

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