Less conservative output‐feedback tracking control design for polynomial fuzzy systems

Pakkhesal, Sajjad; Mohammadzaman, Iman

doi:10.1049/iet-cta.2017.1271

Cited by 8 publications

(6 citation statements)

References 41 publications

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“…In this case, assuming that D i | i�1,..,r � 0, we defne the H 2 -performance output tracking error as 􏽥 z(t) � z(t) − z d (t), where z d (t) represents the desired H 2 -performance output vector. Te output tracking error dynamics is then changed as (77) to evaluate the disturbance attenuation supplied for the system dynamic given in (32).…”

Section: ℵ Are Then Guaranteed and The Resulting Reduced-order Slidin...mentioning

confidence: 99%

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Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems

Soltanian,

Valadbeigi,

Tavoosi

et al. 2024

Complexity

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This study utilizes the Takagi–Sugeno fuzzy model to represent a subset of nonlinear systems and presents an innovative adaptive approach for optimal dynamic terminal sliding mode control (TSMC). The systems under consideration encompass bounded uncertainties in parameters and actuators, as well as susceptibility to external disturbances. Performance evaluation entails the design of an adaptive terminal sliding surface through a two-step process. Initially, a state feedback gain and controller are developed using Linear Matrix Inequality (LMI) techniques, grounded on H2-performance and partial eigenstructure assignment. Dynamic sliding gain is subsequently attained via convex optimization, leveraging the derived state feedback gain and the designed terminal sliding mode (TSM) controller. This approach diverges from conventional methods by incorporating control effort and estimating actuator uncertainty bounds, while also addressing sliding surface and TSM controller design intricacies. The TSM controller is redefined into a strict feedback form, rendering it suitable for addressing output-tracking challenges in nonlinear systems. Comparative simulations validate the effectiveness of the proposed TSM controller, emphasizing its practical applicability.

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Section: ℵ Are Then Guaranteed and The Resulting Reduced-order Slidin...mentioning

confidence: 99%

“…Conversely, addressing output tracking control in nonlinear systems has long been a challenge [30][31][32]. Output signal convergence to reference signal was achieved in [33][34][35] through output feedback control.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems

Soltanian,

Valadbeigi,

Tavoosi

et al. 2024

Complexity

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“…Design of stabilizer polynomial fuzzy controller using Lyapunov stability analysis method is one of the problems that have been considered by researchers [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Tracker polynomial fuzzy controller design is another problem where researchers have used the concept of H ∞ control when solving the equation [20][21][22][23][24][25]. The structures selected for tracking polynomial fuzzy control law generally fall into two categories: static output feedback [20,21,23,26] and dynamic output feedback [13,17,19,27].…”

Section: Introductionmentioning

confidence: 99%

“…Tracker polynomial fuzzy controller design is another problem where researchers have used the concept of H ∞ control when solving the equation [20][21][22][23][24][25]. The structures selected for tracking polynomial fuzzy control law generally fall into two categories: static output feedback [20,21,23,26] and dynamic output feedback [13,17,19,27]. The design of controllers based on dynamic output feedback can be divided into two categories: observer-based output feedback [13,17,27] and explicit dynamic output feedback [19,28].…”

Section: Introductionmentioning

confidence: 99%

“…The main difference between the present research and Lam and Li [23] is that in this research the output feedback dynamic controller is designed based on a PI controller structure, while in Lam and Li [23], the output feedback dynamic controller has a general state space structure. Although previous studies [20,21,23,26] have addressed the tracking control problem for polynomial fuzzy systems, it has solved only the tracking problem for disturbance free polynomial fuzzy systems.…”

Section: Introductionmentioning

confidence: 99%

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Design of output feedback proportional–integral controller for polynomial fuzzy systems

Radmanesh

Moarefianpour

Jahed‐Motlagh

2022

Asian Journal of Control

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In this paper, the design of dynamic output feedback control law for polynomial fuzzy systems is studied. The main purpose is to design a tracker control law for fuzzy polynomial systems that are subject to external bounded disturbances. The structure of the control law is considered as fuzzy proportional–integral control. The conditions for deriving the control law are formulated in the form of a sum of square (SOS) feasibility problem. The designed control law will be able to force the system state vector to follow the state vector of a stable reference model in addition to guaranteeing the H∞ performance measure. The simulation results show the efficiency of the proposed method exposed to external disturbance.

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An improved sum‐of‐squares based approach to fuzzy tracking control design of nonlinear systems

Pakkhesal

Mohammadzaman

2019

Asian Journal of Control

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In this paper, using a more general Lyapunov function, less conservative sum‐of‐squares (SOS) stability conditions for polynomial‐fuzzy‐model‐based tracking control systems are derived. In tracking control problems the objective is to drive the system states of a nonlinear plant to follow the system states of a given reference model. A state feedback polynomial fuzzy controller is employed to achieve this goal. The tracking control design is formulated as an SOS optimization problem. Here, unlike previous SOS‐based tracking control approaches, a full‐state‐dependent Lyapunov matrix is used, which reduces the conservatism of the stability criteria. Furthermore, the SOS conditions are derived to guarantee the system stability subject to a given H∞ performance. The proposed method is applied to the pitch‐axis autopilot design problem of a high‐agile tail‐controlled pursuit and another numerical example to demonstrate the effectiveness and benefits of the proposed method.

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Less conservative output‐feedback tracking control design for polynomial fuzzy systems

Cited by 8 publications

References 41 publications

Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems

Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems

Design of output feedback proportional–integral controller for polynomial fuzzy systems

An improved sum‐of‐squares based approach to fuzzy tracking control design of nonlinear systems

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