Model-free continuous nonsingular fast terminal sliding mode control for cable-driven manipulators

Model-free robust motion control for biological optical microscopy using time-delay estimation with an adaptive RBFNN compensator

The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand for enhanced precision, extended range, and increased load-bearing capacity in objective motion carrier (OMC). To address this challenge, this study introduces an innovative OMC that employs a ball screw mechanism as its primary driving component. Furthermore, a robust nonlinear motion control strategy has been developed, which integrates fast nonsingular terminal sliding mode, experimental estimation techniques, and adaptive radial basis neural network, to mitigate the impact of nonlinear friction within the ball screw mechanism on motion precision. The stability of the closed-loop control system has been rigorously demonstrated through Lyapunov theory. Compared with other enhanced sliding mode control strategies, the maximum error and root mean square error of this controller are improved by 33% and 34% respectively. The implementation of the novel OMC has enabled the establishment of a high-resolution bio-optical microscope, which has proven its effectiveness in the microscopic imaging of retinal organoids.

Model-free finite-time robust control using fractional-order ultra-local model and prescribed performance sliding surface for upper-limb rehabilitation exoskeleton

To address the trajectory tracking issue of upper-limb rehabilitation exoskeleton with uncertainties and external disturbances, this paper proposes a fractional-order ultra-local model-based model-free finite-time robust controller (FO-FTRC) using predefined performance sliding surface. Different from previous model-free control strategies, a novel multi-input multi-output (MIMO) fractional-order ultra-local model which is a virtual model is proposed to approximate the complex uncertain nonlinear exoskeleton dynamics in a short sliding time window. This allows the design of controller to be independent of any exoskeleton model information and reduces the difficulty of controller design. The developed robust model-free control method incorporates a fractional-order quasi-time delay estimator (FO-QTDE), unknown disturbance estimator (UDE) as well as prescribed performance sliding mode control (PPSMC). The FO-QTDE is utilized to estimate the unknown lumped uncertainties which employs short time delayed knowledge only about the control input. However, the low-pass filter is always added for FO-QTDE when disturbances change fast, which leads to unavoidable estimation error. Then, UDE is designed to further eliminate the estimation error of FO-QTDE to enhance control performance. The PPSMC is constructed to converge sliding surface to zero in a finite time. Besides, the sliding surface is always limited in performance boundaries. After that, the overall system stability and convergence analyses are demonstrated by using the Lyapunov theorem. Finally, with the comparison to other methods of α-variable adaptive model free control (α-AMFC), time-delay estimation-based continuous nonsingular fast terminal sliding mode controller (TDE-CNFTSMC), time delay estimation (TDE)-based model-free fractional-order nonsingular fast terminal sliding mode control (MFF-TSM) and fractional-order proportion-differential (PDβ), the co-simulation results on 7-degree-of-freedom (DOF) iReHave upper-limb exoskeleton virtual prototype and experiment results on 2-DOF upper-limb exoskeleton are obtained to illustrate the effectiveness and superiority of the proposed FO-FTRC method.

A novel adaptive neural network-based time-delayed estimation control for nonlinear systems subject to disturbances and unknown dynamics

This paper presents an adaptive backstepping-based model-free control (BSMFC) for general high-order nonlinear systems (HNSs) subject to disturbances and unstructured uncertainties to enhance the system tracking performance. The proposed methodology is constructed based on the backstepping control (BSC) with radial basis function neural network (RBFNN) -based time-delayed estimation (TDE) to overcome the obstacle of unknown system dynamics. Additionally, a command-filtered (CF) approach is involved to address the complexity explosion of the BSC design. As the errors arising from approximation, new control laws are established to reduce the effects in this regard. The stability of the closed-loop system is guaranteed through the Lyapunov theorem and the superiority of the proposed methodology is confirmed through a comparative simulation with other model-free approaches.

Adaptive super-twisting sliding mode altitude trajectory tracking control for reentry vehicle

This paper addresses the altitude trajectory tracking control problem of reentry vehicle subject to bounded uncertainty. A new continuous adaptive super-twisting sliding mode control (ASTSMC) method is developed based on conventional super-twisting sliding mode control (STSMC) and adaptive gain technique, which can improve tracking accuracy and achieve high control performance. Based on adaptive gain technique, the designed ASTSMC method requires no prior information on uncertainty and avoids the overestimation of control gain, then the unexpected chattering phenomenon is alleviated. By employing fast power rate reaching law and modified fast nonsingular terminal sliding mode (FNTSM) surface, the designed controller achieves faster convergence and stronger robustness than conventional STSMC methods. Furthermore, the finite-time stability of closed-loop system is proved through Lyapunov theory. Simulation results are executed to validate the superiority of the proposed controller.

Adaptive nonsingular fixed-time sliding mode control for manipulator systems’ trajectory tracking

In this paper, an adaptive fixed-time controller is raised for the manipulator system with uncertain disturbances to boost the rate and precision of its trajectory tracking and solve the convergence time dependence on the system's initial conditions. First, a nonsingular fixed-time sliding mode (SM) surface and a reaching law based on an arctangent function are constructed to enhance the control scheme performance. Second, the upper bound is difficult to obtain because of the uncertainty of the disturbance. The disturbance upper bound is estimated by adaptive techniques, which do not require a priori knowledge about the upper bound and effectively inhibit the effect of disturbance on the system. Finally, the fixed-time convergence of the states is analyzed by rigorous theoretical proof, and the validity of the presented control scheme is demonstrated by simulation.

Adaptive dynamic feedback control of parallel robots with unknown kinematic and dynamic properties

Uncertainties in dynamic and kinematic parameters are unavoidable components in the control of robotic manipulators. Although calibration is a well-known method to reject this issue, it is time-consuming, some parameters may be altered slowly, and therefore, it is not applicable to some special cases such as deployable cable-driven robots. This paper addresses an adaptive dynamic feedback controller in which the adaptation laws together with new states could remedy these shortcomings and may be appropriately used in deployable cable-driven robots. For this purpose, the Jacobian matrix and its determinant are expressed in regressor form. Additionally, a non-singular sliding surface is considered for the trajectory tracking error. The fast finite-time feasible trajectory tracking is ensured by Lyapunov direct method using an appropriate design of adaptation laws of unknown parameters together with dynamical matrices in the presence of external disturbance. A 4RPR (revolute-prismatic-revolute) redundant rigid body and a fully actuated 3-DOF cable-driven robot are considered to verify the proposed method and also compare the results with state-of-art by simulation and experiment.

Non-Singular Finite Time Tracking Control Approach Based on Disturbance Observers for Perturbed Quadrotor Unmanned Aerial Vehicles

In this paper, a disturbance observer based on the non-singular terminal sliding mode control method was presented for the quadrotor in the presence of wind perturbation. First, the position and attitude dynamical equation of the quadrotor was introduced in the existence of windy perturbation. It was difficult to exactly determine the upper bound of the perturbations in the practical systems such as robot manipulators and quadrotor UAVs. Then, a disturbance observer was designed for the estimation of wind perturbation which was entered to the quadrotor system at any moment. Afterward, a non-singular terminal sliding surface was proposed based on the disturbance observer variable. Furthermore, finite time convergence of the closed-loop position and attitude models of the quadrotor was proved using Lyapunov theory concept. Unlike the existing methods, the new adaptive non-singular terminal sliding mode tracker for quadrotor unmanned aerial vehicles enabled accurate tracking control, robust performance, and parameter tuning. Through the combination of the finite time tracker and disturbance observer, the position and attitude tracking of quadrotor UAVs could be accurately performed not only in the nominal environment but also in the existence of different types of perturbations. Finally, simulation results based on the recommended method were provided to validate the proficiency of the suggested method. Moreover, comparison results with another existing study were presented to prove the success of the proposed method.

Adaptive nonsingular fixed-time sliding mode control for uncertain robotic manipulators under actuator saturation

This paper describes an adaptive nonsingular fixed-time sliding mode control (ANFSMC) scheme under actuator saturation that can track the trajectory of a robotic manipulator under external disturbances and inertia uncertainties. First, a novel NFSMC that offers rapid convergence and avoids singularities is proposed for ensuring robotic manipulators global approximate fixed-time convergence. An ANFSMC is then developed for which the bound of the coupling uncertainty is not necessary to know in advance. The controller exhibits small absolute tracking errors and consumes little energy. An actuator saturation compensator is designed and shown to minimize the chattering of the system while accelerating the trajectory tracking. The proposed schemes are analyzed using Lyapunov stability theory, and their effectiveness and superiority are demonstrated through numerical simulations.

Desired tracking of delayed quadrotor UAV under model uncertainty and wind disturbance using adaptive super-twisting terminal sliding mode control

In this study, the fully-actuated dynamic equation of quad-rotor as a type of Unmanned Aerial Vehicles (UAVs) is considered in the existence of input-delay, model uncertainty and wind disturbance. Then, a super-twisting terminal sliding mode control approach is planned with the aim of the finite-time attitude and position tracking of quad-rotor UAV considering input-delay, model uncertainty and wind disturbance. The finite time convergence of the tracking trajectory of quad-rotor is proved by Lyapunov theory concept. When the upper bound of the modeling uncertainty and wind disturbance is supposed to be unknown, an adaptive super-twisting terminal sliding mode control is proposed. Therefore, the unknown bounds of the model uncertainty and wind disturbance affecting the quad-rotor UAV are estimated using the adaptive-tuning control laws. Finally, simulation outcomes and experimental verifications are provided to demonstrate the validation and success of planned control technique.

Research on hydraulic motor control system based on fuzzy neural network combing sliding mode control and time delay estimation

The precise motion control of a hydraulic motor system has some problems due to uncertain disturbance, complex nonlinear dynamics. Traditional methods are difficult to obtain the desired control performance. In this paper, a new fuzzy neural network (FNN) combined with terminal sling mode control (TSMC) and time delay estimation (TDE) is proposed. FNN is used to adjust the parameter of TSMC to reduce the time for the system to reach the equilibrium point and chatting. To increase the accuracy of the system, TDE is used to compensate the error caused by uncertain disturbance. This controller was simulated in Amesim and Simulink, and the results showed that the control scheme proposed in this paper has the smallest angular displacement error, angular velocity error and variance than other control schemes, such as PID and sliding mode control (SMC). Furthermore, the designed controller was implemented on a drill pipe automatic handling manipulator, and its control performance was verified.

A Lyapunov-Based Optimal Integral Finite-Time Tracking Control Approach for Asymmetric Nonholonomic Robotic Systems

This study suggests a control Lyapunov-based optimal integral terminal sliding mode control (ITSMC) technique for tracker design of asymmetric nonholonomic robotic systems in the existence of external disturbances. The design procedure is based on the control Lyapunov function (CLF) approach. Hence, the output tracking problem is solved by combining the ITSMC with optimal control. The CLF synthesizes a nonlinear optimal control input for the nominal system. Once the control system’s states lie far away from the operating point, it is activated to drive them toward the equilibrium point optimally. However, on the condition that the system perturbations are the main factor, the ITSMC would be designed to take over in the vicinity of the equilibrium point. Accordingly, the control goals, such as robustness and precise control, are warranted in the perturbed system. The usefulness of the suggested method is demonstrated with a wheeled mobile robot via a simulation study.

Model-free adaptive sliding mode control with adjustable funnel boundary for robot manipulators with uncertainties

Considering that the nominal dynamics model or numerous parameters of robotics are usually unsuitable for real applications, a model-free adaptive sliding mode control with an adjustable funnel boundary is proposed for robot manipulators with uncertainties. First, time delay estimation (TDE) technique is utilized to estimate the unknown dynamics of the control system, which ensures an attractive model-free advantage. Furthermore, a modified funnel function is introduced to transform the trajectory tracking error fall within an adjustable funnel boundary strictly. Then, based on the transformed error variable, a novel funnel nonsingular fast terminal sliding mode control scheme is developed to enhance the transient and steady-state tracking performance of the closed-loop control system. To cope with the TDE error, an adaptive update method is designed with only one adaptive parameter, which is adaptively tuned according to the sliding surface. Finally, the simulation and experimental results are presented to illustrate the superiority and high-precision tracking performance of the proposed approach.

A light cable-driven manipulator developed for aerial robots: Structure design and control research

To effectively reduce the mass and simplify the structure of traditional aerial manipulators, we propose novel light cable-driven manipulator for the aerial robots in this article. The drive motors and corresponding reducers are removed from the joints to the base; meanwhile, force and motion are transmitted remotely through cables. Thanks to this design, the moving mass has been greatly reduced. In the meantime, the application of cable-driven technology also brings about extra difficulties for high-precise control of cable-driven manipulators. Hence, we design a nonsingular terminal sliding mode controller using time-delay estimation. The time-delay estimation is applied to obtain lumped system dynamics and found an attractive model-free scheme, while the nonsingular terminal sliding mode controller is utilized to enhance the control performance. Stability is analyzed based on Lyapunov theory. Finally, the designed light cable-driven manipulator and presented time-delay estimation-based nonsingular terminal sliding mode controller are analyzed. Corresponding results show that (1) our proposed cable-driven manipulator has high load to mass ratio of 0.8 if we only consider the moving mass and (2) our proposed time-delay estimation-based nonsingular terminal sliding mode is model-free and can provide higher accuracy than the widely used time-delay estimation-based proportional–derivative (PD) controller.