Adaptive Fuzzy Hierarchical Sliding-Mode Control for a Class of MIMO Nonlinear Time-Delay Systems With Input Saturation

Zhao, Xudong; Yang, Haijiao; Xia, Weiguo; Wang, Xinyong

doi:10.1109/tfuzz.2016.2594273

Cited by 189 publications

(98 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the system signals will be regular and, therefore, can grow at most exponentially [46]. Then, it is possible to conclude that each dynamic gain  [i] i (x, t) of our MIMO differentiator (35) satisfies the following conditions introduced in [18] and [19] for fast and finite-convergence:…”

Section: Theorem 1 Consider the Plant (1) The Reference Model (2)-(mentioning

confidence: 99%

“…(37) with modulation function defined in (21) satisfying (20). The estimateŜ in (36) is given by the global MIMO Differentiator (35). Suppose that assumptions (A1) to (A6) hold.…”

Section: Global Output-feedback Unit Vector Controlmentioning

confidence: 99%

“…Suppose that assumptions (A1) to (A6) hold. For [i] , i = 1, … , m, j = 0, … , i − 1, properly chosen and  [i] i (x, t) in (35) satisfying (33), the estimation † In particular, the following choice is valid for p i ≤ 3:…”

Section: Global Output-feedback Unit Vector Controlmentioning

confidence: 99%

“…Then, we obtain the norm bound (51) from the norm bound for | |. Thus, the global differentiator with dynamic gains given in (35) can indeed be constructed and its state exactly surrogates the time derivatives of the signal e(t) in the variablê S ≡ S (36), after some finite time. From (23), it is easy to TABLE 1 Summary of the proposed control methods…”

Section: Multivariable B-mracmentioning

confidence: 99%

See 3 more Smart Citations

Multivariable extension of global finite‐time HOSM based differentiator for output‐feedback unit vector and smooth binary control

Oliveira

Rodrigues

Battistel

2019

Asian Journal of Control

View full text Add to dashboard Cite

In this paper, we propose a unit vector control law by output feedback to solve the problem of global exact output tracking for a class of multivariable uncertain plants with nonlinear disturbances. In order to face the nonuniform arbitrary relative degree obstacle, we extend our earlier estimation scheme based on global finite-time differentiators using dynamic gains to a multivariable architecture. A diagonally stable condition over the system high-frequency gain (HFG) matrix has to be assumed. Preserving the simplicity of its mono variable framework, variable gain super-twisting algorithm (STA) is employed to obtain the robust and exact multivariable differentiator. Moreover, state-norm observers for the unmeasured state variables are constructed to upper bound the disturbances as well as to update the differentiator gains, being both state dependent. Uniform global exponential stability and ultimate exact tracking are proved. As an alternative to chattering alleviation, we appeal to the Emelyanov's concept of binary control in order to obtain a continuous control signal replacing the unit vector function in the controller by a high-gain gradient adaptive law with parameter projection. As shown in the existing literature for mono variable systems, the proposed multiparameter binary-adaptive formulation tends to the unit vector control as the adaptation gain increases to infinity, also smoothing the transition from adaptive to sliding mode control. A numerical example is portrayed to illustrate the potentialities of the developed multivariable techniques.

show abstract

Section: Theorem 1 Consider the Plant (1) The Reference Model (2)-(mentioning

confidence: 99%

“…(37) with modulation function defined in (21) satisfying (20). The estimateŜ in (36) is given by the global MIMO Differentiator (35). Suppose that assumptions (A1) to (A6) hold.…”

Section: Global Output-feedback Unit Vector Controlmentioning

confidence: 99%

Section: Global Output-feedback Unit Vector Controlmentioning

confidence: 99%

Section: Multivariable B-mracmentioning

confidence: 99%

See 2 more Smart Citations

Multivariable extension of global finite‐time HOSM based differentiator for output‐feedback unit vector and smooth binary control

Oliveira

Rodrigues

Battistel

2019

Asian Journal of Control

View full text Add to dashboard Cite

show abstract

“…. Then, the expression of the asymmetric saturation function defined by (9) can be represented by using two symmetric saturation functions as follows:…”

Section: Asymmetric Input Constraint Analysismentioning

confidence: 99%

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

Nasri

Saifia

Chadli

et al. 2019

Asian Journal of Control

View full text Add to dashboard Cite

This paper aims at presenting a maximum power point tracking (MPPT) controller for photovoltaic (PV) systems subject to asymmetric input constraint.Indeed, the output voltage of the DC-DC converter used for adjusting the photovoltaic output power can be controlled by means of variation of duty ratio limited between 1 and 0. The control design goal is to improve the efficiency of PV systems under asymmetric saturation of duty ratio. To achieve this goal, first, a Takagi-Sugeno (T-S) fuzzy model is used to represent the nonlinear behavior of the PV system. A T-S reference model is employed to give the ideal state direction which must be followed. To achieve a good steady state tracking, the integral of the state tracking error is used to define an extended system state vector. Second, the input characteristic is partitioned into several regions. In each region, the asymmetric saturation function can be considered as a symmetric saturation function. Furthermore, H∞ stabilization conditions for the resulting switching fuzzy control of the PV system under actuator saturation are formulated in term of linear matrix inequalities (LMI) using the Lyapunov approach. Simulation results are exhibited to demonstrate the effectiveness of the proposed design method.

show abstract

A novel no circulating current cooperative adaptive SoC balancing control for large‐scale grid‐connected electric vehicles

Dai

Liu

Cui

et al. 2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary In this article, the state of charge (SoC) balancing problem of large‐scale electric vehicles (EVs) connected to the utility grid is addressed by designing a novel no circulating current cooperative adaptive SoC balancing control. First, considering different capacities and initial SoCs, an adaptive power distribution algorithm based on distributed dynamic consistency algorithm is blue developed to achieve the SoC balancing of large‐scale EVs connected to the utility grid. Then, considering the shortage of battery life caused by the circulating current during the long‐term charging and discharging process, an adaptive balance rate factor is designed to effectively avoid the generation of the circulating current. Then, an adaptive cooperative fuzzy terminal sliding mode controller is proposed for grid‐connected EVs to improve power tracking accuracy and enhance robustness. Considering the parameters' uncertainties and unmodeled parts of grid‐connected EVs, parameter adaptive estimation and fuzzy algorithm are used to approximate the unmodeled part. In addition, the boundedness of the adaptive estimation is guaranteed by using the projection operator. Finally, the validity and reliability of the designed control strategy are verified by simulations.

show abstract

Adaptive Fuzzy Hierarchical Sliding-Mode Control for a Class of MIMO Nonlinear Time-Delay Systems With Input Saturation

Cited by 189 publications

References 18 publications

Multivariable extension of global finite‐time HOSM based differentiator for output‐feedback unit vector and smooth binary control

Multivariable extension of global finite‐time HOSM based differentiator for output‐feedback unit vector and smooth binary control

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

A novel no circulating current cooperative adaptive SoC balancing control for large‐scale grid‐connected electric vehicles

Contact Info

Product

Resources

About