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Visual servoing (VS) control has seen wide adoption in harvesting robots. However, parameter calibration is cumbersome, which makes the use of VS robotic systems inconvenient. Besides, dynamic fruits usually lead to a degeneration of control while tracking. To overcome the drawbacks, we present a new image-based uncalibrated visual servoing (IBUVS) control approach, consisting of a hybrid visual configuration and an adaptive tracking controller, referred to as hybrid-IBUVS. Specifically, our hybrid-IBUVS employs an eye-in-hand camera and a fixed red–green–blue-depth camera to construct a hybrid VS system, basing on multiobject detection and edge-computing technologies. Meanwhile, we also propose adaptive laws to online estimate the uncalibrated parameters of the cameras and robot dynamics. Furthermore, our hybrid-IBUVS uses an adaptive tracking controller to guarantee the harvesting robot to track a predefined trajectory to approach a fruit target. By Lyapunov stability theory, asymptotic convergence of the proposed control scheme is rigorously proven. Experimental results demonstrate the effectiveness of the proposed scheme. All shown results supported the research claims. [ABSTRACT FROM AUTHOR]

In this article, a finite-time adaptive fuzzy control scheme based on filter and reduced-order observer is proposed for induction motors (IMs) with load variation. First, the rotor position and the angular velocity of IMs are estimated by a reduced-order observer. Second, the unknown stochastic nonlinear functions are handled by the fuzzy logic systems. In addition, the finite-time control is combined with command filtering to solve the issue of “explosion of complexity” in the traditional backstepping method, and the errors compensation signal is introduced to reduce the filtering error, which can ensure the finite-time convergence and improve the robustness of the systems. The simulation and experimental results are given for validation of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In this article, we discuss fast finite-time consensus (FFTC) problems for uncertain nonlinear multiple mechanical systems with actuator faults and time-varying asymmetric output constraints. In order to guarantee the constraints are satisfied, an appropriate nonlinear mapping (NM) is employed to transform the original system with output constrains into an corresponding unconstrained one. Combining neural networks technology, graph theory, fast finite-time control theory, and backstepping technology, the actuator faults are considered to propose a distributed adaptive finite-time consensus (FTC) protocol, which can guarantee the position errors as well as the velocity errors reaching a region in finite time. Finally, an illustrative example is presented to support the obtained theoretical results. [ABSTRACT FROM AUTHOR]

Admissibility analysis and control synthesis for nonlinear discrete-time singular systems are considered in this article. With regard to the type-1 and interval type-2 fuzzy singular systems, the partition of membership functions and scale transform is imposed, and new switched fuzzy systems, which are equivalent to the original systems, are established. A relaxed stability criterion is derived to ensure the admissibility of the system by using the piecewise Lyapunov function and singular value decomposition. Moreover, two classes of switched controllers are designed for the systems. One is for type 1 systems and the membership functions are consistent with those of the systems. The other can be applied to both of the fuzzy systems by introducing linear membership functions in each subregion. Two criteria are obtained to guarantee that the closed-loop systems are admissible. Several illustrative examples are provided to show the effectiveness of the developed methods. [ABSTRACT FROM AUTHOR]

This brief investigates the problem of finite-time control for a class of uncertain Markov jumping nonlinear systems with state constraints and input saturation. A novel fraction-power and barrier Lyapunov function based adaptive command filtered backstepping scheme is proposed. The new design technique can not only avoid the analytic computation of the derivative of virtual control functions, but also guarantee the closed-loop system is practically finite-time stable in mean square. Examples with simulations are given to illustrate the effectiveness of the theoretic results obtained. [ABSTRACT FROM AUTHOR]

This article considers the problem of finite-time (FT) tracking control for a class of uncertain multi-input–multioutput (MIMO) nonlinear systems with input backlash. A modified FT command filter is designed in each step of backstepping, which ensures the output of the filter can faster approximate the derivatives of virtual signals, suppress chattering, and relax the input signal limit of the Levant differentiator. Then, the corresponding improved FT error compensation mechanism is adopted to reduce the negative impact of filtering errors. Furthermore, a neural-network-adaptive technology is proposed for MIMO systems with input backlash via FT convergence. It is shown that desired tracking performance can be implemented in finite time. The simulation example is presented to illustrate the effectiveness and advantages of the new design method. [ABSTRACT FROM AUTHOR]

This brief proposes an adaptive neural network-based finite-time impedance control method for constrained robotic manipulators with disturbance observer. Firstly, by combining barrier Lyapunov functions with the finite-time stability control theory, the control system has a faster convergence rate without violating the full state constraints. Secondly, the adaptive neural network is introduced to approximate the unmodeled dynamics and a disturbance observer is designed to compensate for the unknown time-varying disturbances. Then, the command filtered control technique with error compensation mechanism is used to deal with the “explosion of complexity” of traditional backstepping and improve the control accuracy. The simulation results show the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

In this brief, the problem of finite-time heading tracking control for surface vehicles with controller faults and full state constraints is studied. The fuzzy logical systems and command filtered backstepping method are utilized to approximate the unknown nonlinear dynamics and construct an adaptive controller, respectively. The Nussbaum function is employed to solve the unknown control direction arising in the system. The new control scheme is proposed based on barrier Lyapunov functions and finite-time control strategy. It is proved that the error between the actual heading angle and the expected one can converge to the region near the origin in a finite time without violating the full state constraints. Finally, the simulation results are presented to show the effectiveness of the proposed finite-time control scheme. [ABSTRACT FROM AUTHOR]

This article considers the problem of finite-time adaptive fuzzy prescribed performance control (PPC) via output-feedback for nonstrict-feedback nonlinear systems. The fuzzy state observer is designed to estimate the unmeasured system states. To rapidly approximate the derivative of virtual signal, a novel finite-time command filter is proposed. The fractional power error compensation mechanism is established to remove filtered error. By integrating the PPC and command filter technique into backstepping recursive design, a finite-time adaptive output-feedback controller is constructed, and the stability of closed-loop system is strictly proved. The designed control strategy shows that the closed-loop system is practical finite-time stable, and the output tracking error converges to a residual set within prescribed performance bound in finite time. Finally, a numerical comparison and practical examples are provided to demonstrate the validity of the developed finite-time control algorithm. [ABSTRACT FROM AUTHOR]

The problem of adaptive fuzzy observer-based tracking control for nonlinear singular systems is considered in this article. The nonlinear singular systems are composed of two kinds of subsystems, differential subsystem and algebraic subsystem, which are coupled to each other. The systems can be nonstrict feedback structures. Through designing a new state observer and a linear controller, an error system with a tunable parameter is obtained. By constructing new one-sided Lipschitz conditions, the regularization and impulse-free conditions are proposed for the error system. With the help of the tunable parameter in the observer, we design an output feedback controller for the nonlinear singular systems to ensure that all states of the closed-loop system are bounded and the tracking observer errors remain in a neighborhood of the origin. Two examples are provided to illustrate the effectiveness of the presented method. [ABSTRACT FROM AUTHOR]

In this article, the problem of finite-time adaptive fuzzy tracking control for multi-input and multi-output (MIMO) nonlinear systems with input saturation is investigated. The new finite-time command filter is introduced for generating command signals and their derivatives to work out the matter of “explosion of complexity,” and the modified fractional power-based error compensation mechanism (ECM) serves as removing the effect of filter error. Then, the finite-time adaptive control scheme is established via the backstepping recursive design technique. It guarantees all the signals of the closed-loop system (CLS) are finite-time bounded while the output tracking errors are regulated to a sufficiently small neighborhood of the origin in finite time. Finally, the effectiveness of the proposed finite-time control scheme is verified by a numerical comparison example. [ABSTRACT FROM AUTHOR]

This brief focuses on the problem of fixed-time adaptive trajectory tracking control for a quadrotor unmanned aerial vehicle (QUAV) subject to error constraints. By virtue of the fixed-time command filter, the phenomenon of “explosion of complexity” (EOC) existing in the conventional backstepping method is successfully eliminated, meanwhile the effect of filtered error is skillfully removed via a new fractional power error compensation mechanism. By combining the prescribed performance control and backstepping design method together with command filter technique, a fixed-time adaptive control strategy is established. It is proved that all signals of the closed-loop system are fixed-time bounded, and the position and attitude tracking errors of the QUAV approach to an arbitrarily small region of the original point within the predefined performance bounds in a fixed time. Finally, simulation results are given to show the availability of the presented fixed-time control algorithm. [ABSTRACT FROM AUTHOR]

In dual-motor servo systems, several factors seriously affect the tracking performance especially in high-speed and high-accuracy situations, which include machinery flexibilities, torque disturbance, unmodeled dynamics, and motor parameter differences. Given these factors, this article investigates the command filtered backstepping synchronization control (CFBSC) method for a servo system driven by two motors synchronously. Command filters are used to deal with the virtual control signals in backstepping design process to avoid the computational burden causing by repeated derivatives, and a compensation system is applied to reduce the tracking error. Adaptive control is used to compensate the torque disturbance and unmodeled dynamics. In addition, the speed and torque synchronization control signals are designed to guarantee high synchronization performance. The stability of the dual-motor servo system is proved. And the effectiveness of the proposed controller is validated through experiments. [ABSTRACT FROM AUTHOR]

This article is concerned with the containment control of multiple manipulators with uncertain parameters. A novel distributed adaptive backstepping strategy is given in the finite-time control framework. The finite-time command filters (FTCFs) used in the strategy can avoid the explosion of complexity problem for conventional backstepping. To further improve the control performance, the filtering errors caused by the used FTCFs are removed by using the error compensation mechanism (ECM). The proposed virtual control signal, the control torque, and the adaptive updating law can guarantee the set tracking errors converge to an adjustable neighborhood of the origin in finite time in the presence of uncertain parameters. Because the virtual control signal and ECM only use the local information, the established method is completely distributed. Two simulation examples are given to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this article, a new command filtered backstepping based finite-time adaptive fuzzy tracking control scheme for a class of unknown nonlinear systems with full-state constraints is established. First, the proposed finite-time command filter will filtering the virtual control signal and get the intermediate control signal within finite-time, so the problem of calculating complexity will not occur in the backstepping process. Then, the fraction-power-based error compensate signal is set up, which can eliminate the influence of filtering error on the control performance. Considering that the unknown nonlinearities exist in the system, the fuzzy logic system based adaptive control technique is used to deal with them, and only one parameter needs to be estimated. It is shown that the states will not violate the prescribed constrains, all the signals in the closed-loop system are bounded in finite-time and the tracking error can converge to the desired neighborhood of the origin in finite time under the barrier Lyapunov function and fraction-power-based virtual control signals. Finally, the effectiveness of the control method is shown by the simulations. [ABSTRACT FROM AUTHOR]

In this paper, the problem of adaptive finite-time attitude containment control for multiple spacecrafts with unknown external disturbances in spacecraft formation flying is investigated. A distributed control strategy combined with finite-time command filtered backstepping (FTCFB) and an adaptive technique is proposed, which can guarantee the containment errors of attitudes between leader spacecrafts and follower spacecrafts reaching the desired neighborhood in finite time. Moreover, the applied second-order sliding mode differentiator in FTCFB can make the output of the command filter fast approximate the derivative of the virtual signal at the second step of backstepping, which can further improve the control quality. A simulation example is given to show the effectiveness of the new designed technique presented. [ABSTRACT FROM AUTHOR]

In this paper, the tracking control problem is considered for a class of multiple-input multiple-output (MIMO) nonlinear systems with input saturation and unknown direction control gains. A command filtered adaptive neural networks (NNs) control method is presented with regard to the MIMO systems by designing the virtual controllers and error compensation signals. First, the command filtering is used to solve the “explosion of complexity” problem in the conventional backstepping design and the nonlinearities are approximated by NNs. Then, the error compensation signals are developed to conquer the shortcoming of the dynamic surface method. In addition, the Nussbaum-type functions are utilized to cope with the unknown direction control gains. The effectiveness of the proposed new design scheme is illustrated by simulation examples. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive funnel control (FC) scheme for servo mechanisms with an unknown dead-zone. To improve the transient and steady-state performance, a modified funnel variable, which relaxes the limitation of the original FC (e.g., systems with relative degree 1 or 2), is developed using the tracking error to replace the scaling factor. Then, by applying the error transformation method, the original error is transformed into a new error variable which is used in the controller design. By using an improved funnel function in a dynamic surface control procedure, an adaptive funnel controller is proposed to guarantee that the output error remains within a predefined funnel boundary. A novel command filter technique is introduced by using the Levant differentiator to eliminate the “explosion of complexity” problem in the conventional backstepping procedure. Neural networks are used to approximate the unknown dead-zone and unknown nonlinear functions. Comparative experiments on a turntable servo mechanism confirm the effectiveness of the devised control method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the finite-time consensus tracking control problems of uncertain nonlinear multiagent systems. A neural network-based distributed adaptive finite-time control scheme is developed, which can guarantee the consensus tracking is achieved in finite time with sufficient accuracy in the presence of unknown mismatched nonlinear dynamics. Such a finite-time feature is achieved by the modified command filtered backstepping technique based on the high-order sliding mode differentiator. Moreover, the proposed control scheme is completely distributed, since the control laws only use the local information. In addition, although mismatched uncertainty nonlinear dynamics are considered, only one parameter needs to be updated for each agent in the control scheme, which will simply the computations and make the proposed scheme more effective for applications. An example is included to verify the presented method. [ABSTRACT FROM AUTHOR]

This paper considers the fuzzy finite-time tracking control problem for a class of nonlinear systems with input saturation. A novel fuzzy finite-time command filtered backstepping approach is proposed by introducing the fuzzy finite-time command filter, designing the new virtual control signals and the modified error compensation signals. The proposed approach not only holds the advantages of the conventional command-filtered backstepping control, but also guarantees the finite-time convergence. A practical example is included to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the adaptive finite-time attitude tracking control problem for rigid spacecraft with upper bounds unknown external disturbances is studied by using a novel combining control scheme of adaptive control technique and adding a power integrator (AAPI) technique. An adaptive finite-time control law with boundary layer is first established under the proposed combined control scheme, which can attenuate the influences of disturbances and contain the advantages of AAPI technique. Then, another adaptive finite-time control law without boundary layer is further given, which can simply the control design. It is proved that both the two control laws can ensure the tracking errors converge to the desired regions in finite-time. Moreover, since the established two control laws are both designed with continuous control architecture, the chattering problem is eliminated, which are more adopt to practical engineering applications. An example is included to show the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Adaptive fuzzy control via command filtering is proposed for uncertain strict-feedback nonlinear systems with unknown nonsymmetric dead-zone input signals in this paper. The command filtering is utilized to cope with the inherent explosion of the complexity problem of the classical backstepping method, and the error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. In addition, by utilizing the bound information of dead-zone slopes, a new adaptive fuzzy method that does not need to establish the inverse of the dead zone is presented for the unknown nonlinear systems. Compared with existing results, the advantages of the developed scheme are that the compensating signals are designed to eliminate the filtering errors and only one adaptive parameter is required, which will make the proposed control scheme more effective for practical systems. An example of position tracking control for the electromechanical system is given to demonstrate the usefulness and potential of the new design scheme. [ABSTRACT FROM PUBLISHER]

In this paper, command filtering-based fuzzy control is designed for uncertain multi-input multioutput (MIMO) nonlinear systems with saturation nonlinearity input. First, the command filtering method is employed to deal with the explosion of complexity caused by the derivative of virtual controllers. Then, fuzzy logic systems are utilized to approximate the nonlinear functions of MIMO systems. Furthermore, error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. The developed method will guarantee all signals of the systems are bounded. The effectiveness and advantages of the theoretic result are obtained by a simulation example. [ABSTRACT FROM PUBLISHER]