Nanopositioning control of an electrostatic MEMS actuator: adaptive terminal sliding mode control approach

Tabatabaee-Nasab, Fahimeh S.; Naserifar, Naser

doi:10.1007/s11071-021-06637-3

Cited by 14 publications

(3 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several control methods have been already applied to improve the performance of electromechanical switching devices. Starting with the early works of the 1990s [5][6][7], the literature contains proposals based on sliding-mode control [7][8][9], optimal open-loop control [10,11], or iterative techniques [12,13], among others. The common goal of all these works is to achieve soft landing, i.e., a controlled movement by which the armature reaches the final position with zero velocity [14], thus avoiding impacts and bouncing.…”

Section: Armaturementioning

confidence: 99%

Design of a perfect-tracking soft-landing controller for electromagnetic switching devices

2022

View full text Add to dashboard Cite

Electromagnetic switching devices such as electromechanical relays and solenoid valves suffer from impacts and mechanical wear when they are activated using a constant-voltage policy. This paper presents a new control approach that aims at achieving soft landing in these devices, i.e., a movement without neither impacts nor bouncing. The hybrid nonlinear dynamics of the system is firstly described taking into account the limited range of motion that characterizes this class of devices. Then, the nonlinear expression of the control law is derived and a method to design a soft-landing reference trajectory is proposed. It is shown that, when certain conditions are met, the design methodology presented in the paper results in a controller that achieves perfect tracking of the reference trajectory and, hence, soft landing is accomplished. The theoretical analysis is validated by simulation using a dynamical model of a specific switching device.

show abstract

Section: Armaturementioning

confidence: 99%

Design of a perfect-tracking soft-landing controller for electromagnetic switching devices

2022

View full text Add to dashboard Cite

show abstract

“…Micro actuators are useful components for moving the moveable parts in microsystems. For example, in micro‐pumps, a moveable diaphragm and the actuator are the main components [3]. Among these devices, micro electrostatic actuators due to the compatible fabrication process, the stability to form a small air gap, and the ability to generate high speeds have gained an extensive range of applications compared to the other actuators.…”

Section: Introductionmentioning

confidence: 99%

Adaptive RBFNN‐based predictive control for the nanopositioning of an electrostatic MEMS actuator

Rezvani,

Keymasi‐Khalaji

2023

IET Control Theory & Appl

View full text Add to dashboard Cite

Electrostatic micro electro mechanical system (MEMS) as an actuator is one of the most widely used actuators in micro dimension systems. Due to the high nonlinear characteristics in the micro actuator's model, nanopositioning has been a challenging problem for researchers. In addition, the system is subject to uncertainties associated with the system's unknown parameters and un‐modelled dynamics. Thus, to overcome these problems and achieve precise positioning a robust non‐linear control method is required. In this research, an optimal voltage control algorithm is initially designed utilizing the nonlinear predictive control approach. The Taylor expansion sequence is used to estimate the final position of the parallel plate actuator. To approximate unknown disturbances, a radial basis function neural network (RBFNN) has been designed. The estimations made were used in updating the control input in the previous step, and the obtained results showed an increase in the robustness of the designed controller. The stability of the closed‐loop system is also analyzed. Finally, a comparison is accomplished between the potential of the proposed controller and that of the feedback linearization and sliding mode controllers. The obtained results indicate better performance and robustness of the suggested controller.

show abstract

“…There are many advanced methods in the control of MLSs, including output feedback control [4],linear active disturbance rejection control (LADRC) method [5], adaptive backstepping control method [6], model predictive control (MPC) method [7], disturbance observer based control (DOBC) [8], adaptive fuzzy control method [9], and sliding mode control (SMC) [10] and so on. Among them, SMC is a method with simple structure but good control performance [11,12,13]. Recently, many SMC methods have been used for the control of MLSs, such as fractional-order SMC [14], PID-based SMC [15],high-order SMC [16], super-twisting SMC [17], and neural network adaptive SMC (NNASMC) [18], and so on.…”

Section: Introductionmentioning

confidence: 99%

Predictive-adaptive sliding mode control method for reluctance actuator maglev system

Ding

et al. 2022

Nonlinear Dyn

View full text Add to dashboard Cite

The control performance of reluctance actuator maglev system is seriously affected by inherent nonlinearities (e.g., hysteresis, eddy current, flux leakage, etc.) and external disturbances. To this end, this paper proposes an enhanced unknown system dynamics estimator (USDE)-based sliding mode control (USDE-SMC) method by a novel predictive-adaptive switching (PAS) controller (USDE-SMC-PAS). First, a USDE is incorporated into SMC to compensate for the uncertainties; Second, an adaptive switching (AS) controller is used to reduce chattering; Finally, the switching controller is modified by PAS to enhance the dynamic response ability and disturbance rejection ability with reduced chattering. In the PAS controller, the switching gain comprises a filtered estimate error part and a residual part, which are obtained by a first-order filter and an adaptive law, respectively. Consequently, the strong disturbance compensation ability, high levitation accuracy, high dynamic response, and reduced chattering property can be achieved simultaneously. The stabilities of USDE-SMC, USDE-SMC with an AS controller (USDE-SMC-AS), and USDE-SMC-PAS in the closedloop system are analyzed by the Lyapunov theorem.

show abstract

Nanopositioning control of an electrostatic MEMS actuator: adaptive terminal sliding mode control approach

Cited by 14 publications

References 27 publications

Design of a perfect-tracking soft-landing controller for electromagnetic switching devices

Design of a perfect-tracking soft-landing controller for electromagnetic switching devices

Adaptive RBFNN‐based predictive control for the nanopositioning of an electrostatic MEMS actuator

Predictive-adaptive sliding mode control method for reluctance actuator maglev system

Contact Info

Product

Resources

About