Control of nonlinear two-tank hybrid system using sliding mode controller with fractional-order PI-D sliding surface

Kumar, E. Govinda; Arunshankar, J.

doi:10.1016/j.compeleceng.2017.10.005

Cited by 35 publications

(3 citation statements)

References 14 publications

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“…Tank systems have proven to be a typical class of HDSs, and many kinds of research have been conducted in this field [22]- [26]. The TTHS depicted in Figure 6 consists of two cylindrical tanks 𝑇 1 and 𝑇 2 connected by a pipe located at the bottom and by another located at a height ℎ 𝑣 from the bottom.…”

Section: Description Of the Tthsmentioning

confidence: 99%

Modeling and simulation of the two-tank system within a hybrid framework

Yaakoubi

Haggège

2023

IJECE

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<p><span lang="EN-US">Most real-world dynamical systems are often involving continuous behaviors and discrete events, in this case, they are called hybrid dynamical systems (HDSs). To properly model this kind of systems, it is necessary to consider both the continuous and the discrete aspects of its dynamics. In this paper, a modeling framework based on the hybrid automata (HA) approach is proposed. This hybrid modeling framework allows combining the multi-state models of the system, described by nonlinear diﬀerential equations, with the system’s discrete dynamics described by ﬁnite state machines. To attest to the efficiency of the proposed modeling framework, its application to a two-tank hybrid system (TTHS) is presented. The TTHS studied is a typical benchmark for HDSs with four operating modes. The MATLAB Simulink and Stateflow tools are used to implement and simulate the hybrid model of the TTHS. Different simulations results demonstrate the efficiency of the proposed modeling framework, which allows us to appropriately have a complete model of an HDS.</span></p>

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Section: Description Of the Tthsmentioning

confidence: 99%

Modeling and simulation of the two-tank system within a hybrid framework

Yaakoubi

Haggège

2023

IJECE

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“…Based on simulation results, the suggested SMC with FOPID sliding surface outperforms the traditional SMC, SMC-FOPID and SMC-FOPD sliding surface. Furthermore, the performance of set point tracking is not very remarkable, and it has not been subjected to testing for the resilience of the controller in the presence of model uncertainty [29]. For the purpose of water level control of the nuclear steam generator, a gainscheduled equivalent-cascade internal-model-control (IMC) tuning approach is introduced.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Bi-Level Assessment and Adaptive Control Mechanism for Two-Tank Interacting System

Manna,

Singh,

Ghadi

et al. 2023

IEEE Access

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Liquid level control is a fundamental aspect employed across various industries, where the precise regulation of liquid levels and flow rates is of utmost importance. The Proportional-integral-derivative (PID)controller is widely employed but in practice, the operation of a PID may not always align with the desired outcome due to various factors such as system dynamic behavior, model uncertainties, time-varying parameters, and disturbances. To effectively address these challenges, the article proposes model reference adaptive control (MRAC) based on the Massachusetts Institute of technology (MIT) law feedback PID technique for a two-tank interacting system. The detailed comparative analysis is carried out in MATLAB/Simulink with open loop, PID, and MRAC in respect of time domain specifications. The proposed approach stability is verified using the Lyapunov approach. The robustness of the control mechanism is validated through probabilistic assessment by introducing a bi-level uncertainty framework such as gain mistuning and dynamic system behavior. In the first level, the gain mistuning is accomplished in three aspects i.e., fine-tuned, increased, and decrease gain. In the second level, it is considered that system behavior is dynamic in nature. Based on the findings, the MRAC-PID exhibits superior performance against uncertainties as compared to PID and MRAC with enhanced tracking rapidity, accuracy, and robustness.INDEX TERMS Two-tank interacting system, PID, Model reference adaptive controller (MRAC), MIT law, MRAC-PID.

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“…There are numerous other researches on introducing integral action to the SMC. [12][13][14][15][16][17][18][19][20] Although using integral compensation is beneficial in terms of tracking precision, it often results in output overshoot. Overshoot can be alleviated by tuning or assigning controller parameters.…”

Section: Introductionmentioning

confidence: 99%

An integral variable structure control scheme for non-overshooting responses

Liu

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article presents an improved integral variable structure control scheme to avoid overshooting responses for a class of second-order plants. The proposed sliding dynamics have two integral state variables. One integral state variable is initially specified to enable existence of a sliding mode throughout an entire response. The other's initial value is assigned to avoid overshooting output responses. It is shown that the integral state is initially chosen to be a nonlinear function of the plant's initial state to avoid an overshooting response. This article also reports the experimental results for controlling the position of a screw-driven actuator with various payloads and initial velocities, in order to show the effectiveness of the proposed scheme.

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Control of nonlinear two-tank hybrid system using sliding mode controller with fractional-order PI-D sliding surface

Cited by 35 publications

References 14 publications

Modeling and simulation of the two-tank system within a hybrid framework

Modeling and simulation of the two-tank system within a hybrid framework

Probabilistic Bi-Level Assessment and Adaptive Control Mechanism for Two-Tank Interacting System

An integral variable structure control scheme for non-overshooting responses

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