Extremum Seeking Control With Input Dead-Zone

Shao, Guangru; Teel, Andrew R.; Tan, Ying; Liu, Kun‐Zhi; Wang, Rui

doi:10.1109/tac.2019.2946427

Cited by 14 publications

(19 citation statements)

References 23 publications

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“…In this simulation, the performance of the proposed control declared in theorems 1 and 2 will be demonstrated. To verify the effectiveness of the proposed control, it is compared with other state -of-the-art controllers proposed in [23] (compared control 1) and [36] (compared control 2).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…It is notice that in the practical applications of the proposed controller, from the resistance of the damper, the voltage  will be changed to the current to generate the magnetic field which is required to achieve the desired damping force of the MR damper. It is remarked that the controllers proposed in [23,36] will be used as a comparative model to verify the effectiveness of the proposed controller in this study.…”

Section: Model Of Simulationmentioning

confidence: 97%

“…( ) is designed as in (36) with its elements shown in Eqs. ( 37)-( 40), and the adaptation laws for these control inputs are chosen as…”

Section: Proposed Controlmentioning

confidence: 99%

“…(4) Compared with other state-of-the-art methods [23,36], the proposed approach provides superior performance.…”

Section: Introductionmentioning

confidence: 99%

“…It is demonstrated that the unwanted vibrations due to external excitations are well controlled despite of the presence of dead-zone and time delay in actuators. Furthermore, when comparing with other two state-of-theart robust controllers [23,36], the proposed controller provides better vibration suppression capacity and requires less energy consumption.…”

mentioning

confidence: 99%

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Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Phu

Van

2020

Journal of the Franklin Institute

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This study proposes a novel adaptive control method to deal with the dead-zone and time delay issues in actuators of vibration control systems. The controller is formulated based on a type-2 fuzzy neural network integrating with a new modification of Riccati-like equation. The developed new type Riccati-like equation is significant as it reduces energy consumption of control inputs to minimum. Two approaches are suggested to improve performance of the system using the basic elements of Riccati equation. In addition, a fuzzy neural network is applied to approximate the unmodeled dynamics and a sliding mode controller is developed to enhance the robustness of the system against uncertainties and disturbances. After proving the stability of the proposed controller via Lyapunov criterion, the effectiveness of the proposed approach is validated based on computer simulation for vibration control of a vehicle seat suspension. It is demonstrated that the unwanted vibrations due to external excitations are well controlled despite of the presence of dead-zone and time delay in actuators. Furthermore, when comparing with other two state-of-theart robust controllers [23,36], the proposed controller provides better vibration suppression capacity and requires less energy consumption.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Model Of Simulationmentioning

confidence: 97%

“…( ) is designed as in (36) with its elements shown in Eqs. ( 37)-( 40), and the adaptation laws for these control inputs are chosen as…”

Section: Proposed Controlmentioning

confidence: 99%

“…(4) Compared with other state-of-the-art methods [23,36], the proposed approach provides superior performance.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Phu

Van

2020

Journal of the Franklin Institute

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Extremum‐seeking control for unknown static maps with mixed actuator nonlinearity

Guay

2022

Can J Chem Eng

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This study proposes an extremum-seeking controller design for unknown static maps subject to a combination of saturated and discrete actuators with unknown characteristics but with measurable final control elements. The proposed design techniques incorporate a filter for each uncertain actuator that enables the design of a constrained extremum-seeking control that operates at a slow time-scale. The stability analysis demonstrates that the closed-loop system has a practically asymptotically stable equilibrium at the unknown constrained optimum of the optimization problem. A simulation is presented that demonstrates the effectiveness of the proposed technique.

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Distributed extremum‐seeking based resource allocation algorithm with input dead‐zone

Cai

Zhong²,

Li³

et al. 2023

Intl J Robust & Nonlinear

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This paper studies distributed resource allocation problem for agents with input dead-zone, which is not considered in the existing work. At first, the primal problem is transformed to an auxiliary problem by using the exact penalty method to deal with local inequality constraints. It is assumed that the explicit expressions of cost functions and local inequality constraints are unknown to agents but the values of the cost and constraint functions can be obtained. Under such a setup, the extremum seeking control is used to estimate the gradient information. Thus, to obtain the optimal allocation, a novel distributed algorithm is designed by the virtue of the extremum seeking control and a dynamic compensating mechanism which is used to handle the effects of the input dead-zone. Due to a two time-scale structure of the designed distributed algorithm, the semi-globally practically asymptotical convergence of all agents' decisions to the optimal allocation is obtained by the singular perturbation technique. Finally, numerical examples of economic dispatch in smart grids are given to verify the effectiveness of our proposed method.

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Extremum Seeking Control With Input Dead-Zone

Cited by 14 publications

References 23 publications

Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Extremum‐seeking control for unknown static maps with mixed actuator nonlinearity

Distributed extremum‐seeking based resource allocation algorithm with input dead‐zone

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