A new method for control of nonlinear state-dependent switched systems

Khodadadi, Mohsen; Markazi, Amir H.D.

doi:10.1016/j.nahs.2022.101190

Cited by 8 publications

(13 citation statements)

References 26 publications

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“…Considering the above system, following two examples are used to show the effectiveness of the proposed method. In Example 1, the closed‐loop performance is studied for different values of the time‐delay τ, and in Example 2, the closed‐loop performance with the proposed control method is compared with the previously proposed algorithm in [27] for no‐delay systems. Example Simulation studies are performed for different time‐delays, namely,

\tau =0.1 \sec

and

\tau =0.5 \sec

.…”

Section: Simulation Studiesmentioning

confidence: 99%

“…Example In this example, the proposed AFSMC method is compared with a previous AFSMC method proposed for no‐delay systems in [27]. Consider system (76) with

\tau =6

s. Simulations are performed, and the results are shown in Figure 7, where the superior performance of the proposed method is clearly shown.…”

Section: Simulation Studiesmentioning

confidence: 99%

“…Consider system (76) with

\tau =6

s. Simulations are performed, and the results are shown in Figure 7, where the superior performance of the proposed method is clearly shown. Furthermore, the control efforts for the proposed AFSMC and the method of [27] are compared in Figure 8. It can be seen that the previous no‐delay approach generates an excessively erratic and chattered control effort that diverges to infinity!…”

Section: Simulation Studiesmentioning

confidence: 99%

“…proposed AFSMC for under‐actuated nonlinear systems [26]. The unique feature of this paper is that it extends the method of [27] to the case of delayed‐state switched systems with delayed‐state‐dependent switching laws by interpreting the delayed switched dynamic changes as a bounded uncertainty. The assumption is that the uncertainties due to the time‐delay and switching effects could be bounded by a polynomial of states with to‐be‐determined coefficients.…”

Section: Introductionmentioning

confidence: 99%

“…Innovations of this research can be summarized as below: The proposed method is an expanded version of a previously method proposed by the authors to control no‐delay switched systems in [27]. The key concept is to think of the dynamic changes brought on by switching between sub‐systems as an uncertainty constrained by a polynomial of the delayed‐state norms with unknown coefficients.…”

Section: Introductionmentioning

confidence: 99%

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Control of switched systems with delayed states: A direct AFSMC approach

Markazi

Khodadadi

2022

IET Control Theory & Appl

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This research focuses on controlling a class of MIMO state‐delayed nonlinear systems with switching conditions that depend on the delayed states. The key concept is to consider the dynamic changes brought by switching between sub‐systems as an uncertainty bounded by a certain polynomial of the delayed states norm. The challenge of managing a delayed switched system is changed to the simpler problem of controlling a delayed non‐switched system via an extended AFSMC approach with just one sliding surface. New adaptation laws are proposed within the general framework of the direct AFSMC scheme to estimate unknown coefficients of the uncertainty bound polynomial and parameters of a central fuzzy controller, which mimics the behavior of a feedback linearized controller in the conventional SMC approach. Using the method of multiple lyapunov‐krasovskii functions (MLKF), closed‐loop stability is proven. Several examples are elaborated to show the effectiveness of the method compared to the previously proposed no‐delay AFSMC method and also to the conventional feedback linearization approach. In particular, the proposed control scheme is applied to a benchmark high‐speed super cavitation underwater vehicle. The efficacy of the proposed method is depicted, while minimal information about the plant dynamics is needed in the control design stage.

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\tau =0.1 \sec

and

\tau =0.5 \sec

.…”

Section: Simulation Studiesmentioning

confidence: 99%

“…Example In this example, the proposed AFSMC method is compared with a previous AFSMC method proposed for no‐delay systems in [27]. Consider system (76) with

\tau =6

s. Simulations are performed, and the results are shown in Figure 7, where the superior performance of the proposed method is clearly shown.…”

Section: Simulation Studiesmentioning

confidence: 99%

“…Consider system (76) with

\tau =6

Section: Simulation Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Control of switched systems with delayed states: A direct AFSMC approach

Markazi

Khodadadi

2022

IET Control Theory & Appl

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Task space control of the robot manipulators with adaptive fuzzy global fast terminal sliding mode control in presence of dynamic and kinematic uncertainties

Soltanpour,

Zaare

2023

Adaptive Control & Signal

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SummaryBasic features such as convergence time and speed, number‐action control coefficients, free chattering, and proof of stability are significant in the design process and sliding mode control (SMC) efficiency. In this article, we propose an adaptive fuzzy global fast terminal SMC (AFGFTSMC) to handle the mentioned features in the task space control of the robot manipulator in the presence of dynamic and kinematic uncertainties. First, perturbed joint space dynamic equations of the system are transferred to task space, and a broad range of uncertainties are considered there. Then, a global fast terminal SMC (GFTSMC) is proposed for robot manipulators in task space, in which a flexible sliding surface improves the convergence time. Next, to have an intelligent adjustment of the sliding surface coefficients, which leads to a much faster convergence rate, a fuzzy approximator with just seven fuzzy rules is presented. In the following, to access the boundaries of the existing uncertainties, an adaptive fuzzy approximator is proposed, which has five fuzzy rules and only one adaptive law, increases the system's robustness, and eliminates the effect of chattering. Mathematical proof shows that the task space closed‐loop control system under the proposed AFGFTSMC and in the presence of dynamic and kinematic uncertainties has a finite‐time global asymptotic stability. The theoretical evidence and simulation results, which are conducted on a 2‐link robot manipulator, confirm the good efficiency of the proposed controller.

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Dynamic event‐triggered‐based anti‐disturbance control for uncertain LPV systems

Gao,

Zhao,

Sang

et al. 2023

Intl J Robust & Nonlinear

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SummaryThis investigation proposes a dynamic event‐triggered‐based anti‐disturbance control technique for the uncertain linear parameter varying (LPV) systems subject to multiple disturbances. First, an observer is constructed to capture the unavailable modeled disturbances. Then, a feedback controller is proposed. Further, sufficient conditions are presented for the uncertain LPV systems to achieve the multiple disturbances suppression and communication transmission resources saving. In the end, the reasonability of the proposed control scheme is verified by an example of a turbofan.

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A new method for control of nonlinear state-dependent switched systems

Cited by 8 publications

References 26 publications

Control of switched systems with delayed states: A direct AFSMC approach

Control of switched systems with delayed states: A direct AFSMC approach

Task space control of the robot manipulators with adaptive fuzzy global fast terminal sliding mode control in presence of dynamic and kinematic uncertainties

Dynamic event‐triggered‐based anti‐disturbance control for uncertain LPV systems

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