Adaptive finite-time tracking control of robot manipulators with multiple uncertainties based on a low-cost neural approximator

Wang

2023

Sensors

Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed for the uncertainty of a robot model and a camera model. Secondly, a finite-time adaptive controller is designed by using a nonlinear proportional differential plus a dynamic feedforward compensation structure. By applying a continuous non-smooth nonlinear function to the feedback error, the control quality of the closed-loop system is improved, and the desired trajectory of the image is tracked in finite time. Finally, using the Lyapunov stability theory and the finite-time stability theory, the global finite-time stability of the closed-loop system is proven. The experimental results show that the proposed controller can not only adapt to the changes in the EIH and ETH visual configurations but also adapt to the changes in the relative pose of feature points and the camera’s relative pose parameters. At the same time, the convergence rate near the equilibrium point is improved, and the controller has good dynamic stability.

Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Design of A Finite-Time Adaptive Controller for Image-Based Uncalibrated Visual Servo Systems with Uncertainties in Robot and Camera Models

Wang

2023

Sensors

“…Zhou el at. [29] used a TSMC observer to ensure an accurate estimation of the actual position of the end-effector within a finite time. In [30], a second-order finite-time disturbance observer-based backstepping SMC is employed for quadrotor UAV attitude control with external disturbance.…”

Section: Introductionmentioning

confidence: 99%

Fixed-time composite observer-based adaptive recursive sliding mode control for tiltrotor UAV attitude tracking

Luo,

Xu,

et al. 2024

Preprint

An adaptive recursive sliding mode control (ARSMC) scheme based on a fixed-time composite observer (FTO) is introduced in this paper, to address challenges in tiltrotor unmanned aerial vehicle (TUAV) attitude control. As an electric vertical take-off and landing (eVTOL) aircraft, the unique structure of TUAV leads to significant aerodynamic disturbances, particularly during transition modes, causing flight instability. To enhance control robustness, a fast-converging FTO is designed to estimate the system states, model uncertainties and external disturbances, achieving fixed-time convergence. The FTO comprises a fixed-time state observer (FTSO) based on homogeneous function and a fixed-time disturbance observer (FTDO). To accomplish rapid and accuracy attitude tracking during TUAV flight, a recursive sliding mode control (RSMC) is employed. This method utilizes reconstructed information from the FTO, incorporates an adaptive law to update control gains, and ensures finite-time convergence. And the recursive structure reduces the convergence time while reducing chattering phenomena. Ultimately, simulation results demonstrate the effectiveness of the proposed FTO-ARSMC (FAC) strategy in rapidly and robustly controlling the attitude during the transition mode of TUAV.

Intl J Robust & Nonlinear

“…5 However, it is very difficult to achieve the tracking control purpose only by relying on the above methods when the nonlinear structure in the systems has strong nonlinearity and uncertainty. As some alternative methods, the approximation-based adaptive control methods have been reported, such as neural networks (NNs) control, [6][7][8][9] fuzzy logic systems (FLSs) control 10,11 and multi-dimensional Taylor network (MTN) control. [12][13][14] Among them, the MTN is taken as a new type of NN, which has received a growing number of attention, and many MTN-based adaptive tracking control schemes have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Switching threshold‐based event‐triggered adaptive asymptotic tracking control for stochastic nonlinear systems with full‐state constraints

Zhu

Zhai

et al. 2023

In this article, the problem of event-triggered adaptive asymptotic tracking control (ATC) for stochastic nonlinear systems with unknown control directions (UCDs) and full state constraints is concerned. It must be said that the controller design and system analysis is more complex and difficult since the existence of stochastic disturbances, UCDs and full state constraints simultaneously. By introducing the lower bound of the UCDs into the barrier Lyapunov functions, an event-triggered adaptive MTN ATC scheme is proposed based on the boundary estimation method and a new event-triggered control (ETC) strategy, which can achieve satisfactory asymptotic tracking performance and control performance of the system, while reduce the occupation of network resources. The simulation results not only verify the effectiveness of the proposed control scheme, but also present different tracking performances between three ETC strategies for comparison, further confirming the superiority of the proposed ETC strategy in achieving asymptotic tracking performance.