Comment on ‘Adaptive prescribed performance sliding mode control of MEMS gyroscope’

2018 ◽  
Vol 41 (3) ◽  
pp. 883-884 ◽  
Author(s):  
Seyed Majid Esmaeilzadeh ◽  
Mehdi Golestani
Keyword(s):  
Steady State ◽  
Tracking Control ◽  
Sliding Mode ◽  
A Priori ◽  
Original System ◽  
Performance Function ◽  
Prescribed Performance ◽  
Rate Maximum ◽  
Mems Gyroscopes ◽  
Transient And Steady State

An adaptive control of MEMS gyroscopes with guaranteed transient and steady-state performance has been presented in Lu and Fei (2016). A performance function characterizing the convergence rate, maximum overshoot and steady-state error is used for the output error transformation, such that stabilizing the transformed system is sufficient to achieve the tracking control of the original system with a priori prescribed performance. The main objective of this comment is to point out a mistake occurred through the paper, resulted in the ineffectiveness of the proposed controller.

Tracking control of a convoy of autonomous robotic cars with a prescribed performance

2019 ◽  
Vol 41 (13) ◽  
pp. 3725-3741 ◽  
Author(s):  
Khoshnam Shojaei ◽  
Mohammad Reza Yousefi
Keyword(s):  
Control System ◽  
Steady State ◽  
Tracking Control ◽  
Lyapunov Theory ◽  
Relative Distance ◽  
Control Technique ◽  
Dynamic Surface ◽  
Prescribed Performance ◽  
Autonomous Cars ◽  
Transient And Steady State

This paper studies the tracking control of a convoy of multiple autonomous cars or car-like robots in the planar motion without any collision with a prescribed performance that has not been addressed sufficiently in the literature yet. Toward this end, a coordinate transformation is initially employed to transform the posture errors between each two successive cars in a group from the earth-fixed frame into their relative distance and angle errors that should satisfy some predefined transient and steady-state constraints. By employing the prescribed performance technique, a nonlinear transformation is used to transform the constrained relative distance and angle errors and to obtain an unconstrained kinematic error equation. Then, a novel kinematic controller is designed to satisfy the prescribed transient and steady-state performance specifications without any collision and any controller singularity. Next, the Dynamic Surface Control technique is effectively used to simplify the convoy controller design at the dynamic level by using a first-order filter. An adaptive neural network is used to maintain the control system robustness against modelling errors and external disturbances. The Lyapunov theory proves the stability of the convoy control system and, finally, simulation examples verify the controller performance for multiple autonomous cars in intelligent transportation applications.

ADAPTIVE SUPER-TWISTING-LIKE SLIDING MODE CONTROL WITH PRESCRIBED PERFORMANCE FOR ROBOT MANIPULATORS

2019 ◽  
Vol 19 (08) ◽  
pp. 1940053
Author(s):  
SHUPENG ZHENG ◽  
XINJIAN NIU ◽  
CHENHUI PENG
Keyword(s):  
Steady State ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Parameter Tuning ◽  
Unknown Boundary ◽  
Surgical Robots ◽  
Prescribed Performance ◽  
Mode Control

In order to minimize the involuntary tremor of surgeon’s hands, the surgical robots are widely applied in the minimally invasive surgeries. However, unlike ordinary robots, the surgical robots require that the manipulator has high precision and strong anti-disturbance ability. Besides that, the manipulators of surgical robots must be able to move smoothly and respond quickly to the surgeon’s instructions during conducting tasks. To solve aforementioned problems, this paper describes a super-twisting sliding mode controller for the robot manipulator. The basic law is combined with the adaptive term to overcome the unknown disturbances and structural uncertainties, and with the prescribed performance allowing to influence the error dynamics. To ensure the robot system has good transient and steady-state performances, the transformation function of tracking errors is devised. Through using transformed errors, we attain the surface of sliding mode and propose a modified structure of traditional super-twisting algorithm. Considering the derivative of lumped disturbance has unknown boundary, a novel adaptive law is derived for the modified super-twisting sliding mode control which does not require the boundary of disturbance. Simulation experiments showed that the proposed control algorithm not only improves the tracking performance of surgical robot manipulators, but also facilitates the parameter tuning of controller. The devised robot manipulators are also potentially applicable to telesurgery where the steady-state response of surgical robots is required.

scholarly journals Performance Evaluation of Different Control Methods for an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV) with Position Estimator and Disturbance Observer

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Ghulam E. Mustafa Abro ◽  
Zain Anwar Ali ◽  
Saiful A. Zulkifli ◽  
Vijanth Sagayan Asirvadam
Keyword(s):  
Steady State ◽  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
Observer Design ◽  
Control Technique ◽  
Mode Control ◽  
Dynamic Factors ◽  
Transient And Steady State

The main aim of this manuscript is to design and demonstrate the performance of different control algorithms with position estimator and disturbance observer to track the helical trajectory by an underactuated quadrotor craft under the influence of unmodelled dynamic factors and external disturbances. The manuscript consists of the derivations related to the kinematics and dynamics of quadrotor dully derived using the Newton Euler approach. It is one of the strenuous tasks to stabilize and control the quadrotor for helical trajectory tracking since it is an underactuated mechatronic system. In addition to this, with inclusion of unmodelled dynamic factors, it faces some of the serious transient and steady-state issues including Zeno noise. In this research manuscript, dual-loop single-dimension fuzzy sliding mode control (DLSDF-SMC) is proposed to improve the helical trajectory tracking performance, and to tackle the unmodelled dynamic factors, a state feedback controller is proposed consisting of a position estimator and disturbance observer design. The entire system is distributed into two subsystems such that within the angular subsystem, the attitude control is proposed using DLSDF-SMC, and for the translational subsystem, the paper proposes the position control design based on the hyperbolic function to avoid the gimbal lock issue. The overall stability of the proposed closed-loop control scheme is also proved. The simulation work for the proposed algorithm is performed using MATLAB and Simulink software and compared with the conventional sliding mode control (SMC) and fuzzy-based SMC control designs. This work demonstrates that the DLSDF-SMC control technique with position estimator and disturbance observer design in feedback not only improves the aggressive maneuvers while tracking the helical trajectory but also tackles the transient and steady-state issues.

scholarly journals Neural network–based nonaffine control of air-breathing hypersonic vehicles with prescribed performance

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875524 ◽  
Author(s):  
Xiangwei Bu ◽  
Qing Wang
Keyword(s):  
Steady State ◽  
Neural Control ◽  
Tracking Error ◽  
Computational Cost ◽  
Design Procedure ◽  
Hypersonic Vehicles ◽  
Tracking Errors ◽  
Air Breathing ◽  
Prescribed Performance ◽  
Transient And Steady State

This article investigates a novel nonaffine control strategy using neural networks for an air-breathing hypersonic vehicle. Actual actuators are regarded as additional state variables and virtual control inputs are derived from low-computational cost neural approximations, while a new altitude control design independent of affine models is addressed for air-breathing hypersonic vehicles. To further reduce the computational load, an advanced regulation algorithm is applied to devise adaptive laws for neural estimations. Moreover, a new prescribed performance mechanism is exploited, which imposes preselected bounds on the transient and steady-state tracking error performance via developing new performance functions, capable of guaranteeing altitude and velocity tracking errors with small overshoots. Unlike some existing neural control methodologies, the proposed prescribed performance-based nonaffine control approach can ensure tracking errors with preselected transient and steady-state performance. Meanwhile, the complex design procedure of backstepping is also avoided. Finally, simulation results are presented to validate the design.

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