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This study presents a combination of Type-2 fuzzy logic and nonsingular fast sliding mode technique to design a robust controller for a robotic system. The control law is composed of two signals. The first one called equivalent control law is dedicated to maintaining the system on the sliding surface and then converges to zero. Since the system is uncertain, a Type-2 fuzzy nominal model was constructed, deduced from linear local models, which allows a good approximation of the real robotic system. The second signal, whose objective is to force the system to attain the sliding surface, is deduced from stability analysis using Lyapunov theory. Several simulations were conducted to evaluate the efficiency of the proposed approach, showing good tracking performance for different reference signals despite the presence of uncertainties and external disturbances.

In this paper, a novel disturbance observer-based robust nonsingular fast terminal sliding mode control (RNFTSMC) technique is proposed for tracking control of robotic manipulators with time-varying disturbances. First, an improved form of nonsingular fast terminal sliding manifold is developed to achieve the strong robustness and finite time convergence of the system, and to avoid the singularity problem. Second, a continuous robust reaching law is designed not only to attenuate chattering phenomena without deteriorating the system tracking precision, but also to guarantee the finite time stability of the system. Furthermore, a nonlinear disturbance observer (NDOB) is employed to estimate the system uncertainties and decrease the switching gain, so that the prior information about the perturbations is not required, and the control signal can be reduced with fewer chattering effect. The system stability is analyzed according to the Lyapunov stability theory. Finally, the superiority of the proposed control scheme is validated by comparative simulation studies. [ABSTRACT FROM AUTHOR]

A predetermined time nonsingular fast terminal sliding mode control (PTNFTSMC) is proposed to solve the problem of long convergence time and instability in the orbit control of remotely operated vehicles (ROVs). First, a new concise method is proposed to design a predetermined-time controller by setting control parameter conditions that self-adjust according to the system state. Then, the control law of PTNFTSMC is formulated by combining the proposed theory of prescribed time control and the theory of fast termination nonsingular sliding control mode. Finally, the stability and tunability of the proposed controller in a specific period are demonstrated by rigorous arguments. Simulation experiments show that the proposed PTNFTSMC achieves stability at any initial state of the system for a specified time with guaranteed convergence accuracy, and the actual convergence time of the system is very close to the parameters of the specified time compared with other existing control schemes. This confirms the effectiveness and superiority of the proposed PTNFTSMC.

In this paper, a novel fault-tolerant control tactic for robot manipulator systems using only position measurements is proposed. The proposed algorithm is constructed based on a combination of a nonsingular fast terminal sliding mode control (NFTSMC) and a novel high-speed third-order sliding mode observer (TOSMO). In the first step, the high-speed TOSMO is proposed for the first time to approximate both the system velocity and the lumped unknown input with a faster convergence time compared to the TOSMO. The faster convergence speed is obtained thanks to the linear characteristic of the added elements. In the second step, the NFTSMC is designed based on a nonsingular fast terminal sliding (NFTS) surface and the information obtained from the proposed high-speed TOSMO. Thanks to the combination, the proposed controller–observer tactic provides excellent features, such as a fast convergence time, high tracking precision, chattering phenomenon reduction, robustness against the effects of the lumped unknown input and velocity requirement elimination. Especially, the proposed observer does not only improve the convergence speed of the estimated signals, but also increases the system dynamic response. The system's finite-time stability is proved using the Lyapunov theory. Finally, to validate the efficiency of the proposed strategy, simulations on a PUMA560 robot manipulator are performed. [ABSTRACT FROM AUTHOR]

In order to solve the problems of high cost, low reliability, unstable performance, and difficult maintenance in the complex working conditions brought about by traditional mechanical sensors to the permanent magnet synchronous motor (PMSM) control system, a continuous hyperbolic tangent function sigmoid is first proposed as the variable-structure model of the switching function. It refers to the method of the model reference adaptive system (MRAS) observer to estimate the motor speed and rotor position. Secondly, in view of the inherent chattering and poor robustness of the traditional sliding mode control (SMC), a speed-loop control strategy of nonsingular fast terminal sliding mode control (NFTSMC) is proposed. On this basis, a new type of reaching law with an improved terminal attractor that can eliminate negative exponential terms is designed. This control technology can quickly converge under conditions of sudden load changes and motor parameter changes, and improve the dynamic response of the system. Finally, simulation and experimental verification are carried out based on PSIM software and the PTS-3000 experimental platform. The results prove that MRAS positionless control can accurately estimate the rotor speed and position, and the NFTSMC based on the improved terminal attractor has superior control performance. [ABSTRACT FROM AUTHOR]

This study aims to build a novel tracking control algorithm using a finite-time disturbance observer which obtains fast convergence within a predetermined amount of time and strong stability for a class of second-order nonlinear systems. Firstly, a nonlinear sliding mode manifold with fast finite-time convergence is introduced. Then, according to the designed manifold for the guarantee of finite-time convergence and robustness stabilization, a nonlinear control algorithm based on theory of finite-time control is developed. Specifically, the information of the lumped uncertainty was achieved by a new finite-time Disturbance Observer (DO). Thanks to the synthetic advantages of the above techniques, the designed controller marked with powerful features including a practical design, fast convergence rate, high precision, a convergence of the control errors in finite-time, along with impressive small chattering in the control actions. Furthermore, the control proposal also eliminates the necessity of the upper boundary of the uncertainties affecting the system and its finite settling time can be estimated in advance by designating the appropriate design parameters. The finite-time stability of the proposed DO, sliding surface, and control algorithm has been fully confirmed by Lyapunov principle. Trajectory tracking simulation for a 3-DOF manipulator and trajectory tracking experiment for a Maglev System (MLS) has been performed under different operating conditions using MATLAB/SIMULINK to testify the effectiveness and feasibility of the suggested strategy.

In this paper, a novel adaptive neuro network nonsingular fast terminal sliding mode control based on barrier Lyapunov functions is proposed for flexible double-clamped beam systems with input saturation and distributed disturbance. First, the Galerkin projection method is employed to reduce the partial differential dynamic equations of the beam into ordinary differential equations. Second, a novel barrier Lyapunov function is employed to design a nonsingular fast terminal sliding mode controller that ensures the closed-loop system is stable with state constraints. In addition, an auxiliary system is proposed to guarantee the stability of the beam system subject to input saturation. Third, an adaptive neural network is used to deal with the possible unknown part of the model parameters. It is proved that the proposed control law can handle input saturation and state constraints simultaneously without knowing the model exactly. Finally, numerical simulations illustrate the effectiveness of the proposed control laws.

In this paper, a novel fault-tolerant control tactic for robot manipulator systems using only position measurements is proposed. The proposed algorithm is constructed based on a combination of a nonsingular fast terminal sliding mode control (NFTSMC) and a novel high-speed third-order sliding mode observer (TOSMO). In the first step, the high-speed TOSMO is proposed for the first time to approximate both the system velocity and the lumped unknown input with a faster convergence time compared to the TOSMO. The faster convergence speed is obtained thanks to the linear characteristic of the added elements. In the second step, the NFTSMC is designed based on a nonsingular fast terminal sliding (NFTS) surface and the information obtained from the proposed high-speed TOSMO. Thanks to the combination, the proposed controller–observer tactic provides excellent features, such as a fast convergence time, high tracking precision, chattering phenomenon reduction, robustness against the effects of the lumped unknown input and velocity requirement elimination. Especially, the proposed observer does not only improve the convergence speed of the estimated signals, but also increases the system dynamic response. The system’s finite-time stability is proved using the Lyapunov theory. Finally, to validate the efficiency of the proposed strategy, simulations on a PUMA560 robot manipulator are performed.

For the problem that the position tracking accuracy of permanent magnet linear synchronous motor (PMLSM) servo system is easily affected by uncertain factors such as parameters change, load disturbance and friction and so on, an adaptive neural network nonsingular fast terminal sliding mode control (ANNNFTSMC) method is proposed. Firstly, the PMLSM dynamic mathematical model with uncertainty is established. Then, the nonsingular fast terminal sliding mode control (NFTSMC) can avoid the singularity problem and make the state of the system converge to the equilibrium point quickly, so as to improve the response speed of the system. Secondly, in order to minimize the influence of disturbance and dynamic uncertainty, the dynamic model of PMLSM servo system is estimated by RBF neural network, and the uncertain upper bound of PMLSM servo system is estimated in real time combined with adaptive control, which weakens the chattering phenomenon and enhances the robustness of the system. It is proved theoretically that the control scheme can make the system achieve fast convergence and good tracking. Finally, the system experiments show that the proposed control scheme has the advantages of high tracking accuracy, good robustness, fast response speed and small position error.

In this paper, a novel finite-time robust adaptive nonsingular fast terminal sliding mode control strategy is designed to achieve high performance control for an electro-optical targeting system which is subjected to nonlinear friction and disturbance torque. First, a robust adaptive control technique is constructed to compensate modified LuGre model and disturbance torque. Then, a nonsingular terminal fast sliding mode is integrated into the robust adaptive control technique to implement response rapidity and enhance the robustness of the closed-loop system. Furthermore, the control strategy is proved by Lyapunov criterion within finite time. Finally, simulation and experimental results indicate that high accuracy, fast response and stable control performance are obtained by the proposed control strategy for the electro-optical targeting system.

Taking into account almost all kinds of variations and uncertainties to which AC island photovoltaic (PV) microgrid is often subjected, this paper proposes a new nonsingular fast terminal sliding mode control (NFTSMC) strategy for two-stage converters to enhance robustness against those disturbances and improve system dynamic performance. Firstly , to effectively decrease the adverse effect on the system from intermittent solar irradiation and uncertain environmental temperature, a NFTSMC cascaded with perturb and observe (P&O) scheme is put forward for fore-stage DC/DC converter, and PV output voltage is controlled to track its reference and thus maximum power point tracking (MPPT) performance is improved. Then , to significantly decrease the adverse effect on the system from variations of load and LC filter parameters, by incorporating an extended state observer (ESO) into NFTSMC, an ESO-based NFTSMC scheme is proposed for post-stage DC/AC converter, and the load voltage is regulated to track its reference and thus system robustness is strengthened, in which ESO is designed to replace load current sensor and thus reduce hardware cost. By using global terminal attractor without discontinuous switching function, the proposed NFTSMC strategy can not only strengthen system robustness but also improve system dynamic performance. Lastly , on account of the variations of PV generation and load demand, a conventional double-loop PI scheme is put into use for bidirectional DC/DC converter and thus system power balance is ensured. Comprehensive MATLAB simulation and StarSim/Hardware experiment results show that the proposed NFTSMC strategy for two-stage converters can overcome negative effects caused by various internal and external disturbances, and thus enable island PV microgrid to operate reliably and supply high-quality AC power. • For PV island microgrid subjected to various disturbances, the proposed NFTSMC strategy can enhance system robustness • The proposed NFTSMC cascaded with P&O for forestage DC/DC effectively improves PV MPPT performance under various disturbances. • An ESO is designed and incorporated into NFTSMC scheme to remove load current sensor and thus reduce hardware cost. [ABSTRACT FROM AUTHOR]

This paper mainly focuses on the attitude tracking controller design for a vertical take-off and vertical landing (VTVL) reusable launch vehicle in regardless of uncertain parameters, un-modeled dynamics, external disturbances and actuator faults. Starting from the kinematics and dynamics model of the VTVL, the attitude tracking error model subject to grid fin faults is built. A novel fixed-time extended state observer (FxTESO) is presented to estimate the derivative of the attitude tracking error and the lumped disturbances including grid fin faults and other uncertainties. Subsequently, a novel nonsingular fast terminal sliding mode surface (NFTSMS) is designed using the FxTESO, which has faster convergence performances than the traditional sliding mode surface. Finally, an adaptive fault-tolerant control scheme is proposed by utilizing the FxTESO, the proposed NFTSMS and the nonsingular fast terminal sliding mode control with an adaptive gain. The proposed controller achieves faster convergence speed and shorter reaching time. Both adaptive fault-tolerant controller and NFTSMS are proved by Lyapunov theory. The performances of the proposed control scheme are demonstrated by numerical simulations. • A new VTVL reusable launch vehicle was studied. • A novel FxTESO was presented to simplify the control system and reduce the knowledge of the model parameters. • A novel NFTSMS was designed to achieve faster convergence performances and better singularity-free property. • An adaptive fault-tolerant control scheme with an adaptive gain was proposed. [ABSTRACT FROM AUTHOR]

In order to improve the performance in the practical engineering applications including so called low-speed video tracking and large-angle swing scanning imaging at the same time for a three-axis universal inertially stabilized platform (UISP), we propose an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) strategy subjected to the uncertain disturbances and input saturation constraints. First of all, a second-order dynamic model is established with uncertain disturbances and input saturation constraints. Secondly, a nonsingular fast terminal sliding mode controller (NTSMC) is constructed to ensure the system error converges to zero fast in a finite time; meanwhile, a novel reaching law based on a modified normal distribution function is designed to adjust the control gain. Thirdly, an adaptive control law is designed to online estimate the parameters of the lumped uncertain disturbances. Additionally, the stability of the control system is proved by Lyapunov theory. Finally, extensive comparative simulations and experiments are carried out, the results comprehensively show the effectiveness and superiority of the proposed control method, which can accelerate convergence, weaken the chattering, and has the better control accuracy and robust performance both in the low-speed tracking and large-angle swing scanning applications. Moreover, the exact dynamic model and the prior knowledge of the upper bounds of the disturbances are not required during the procedure of the controller design, which make it have more extensive application value in practical engineering.

In this work, an efficient robust control scheme is proposed for position control of induction motors based on field-oriented control (FOC). The proposed control scheme consists of three interior loops. In the outer loop, the central controller based on the nonsingular fast terminal sliding mode control (NFTSM) is designed. The objective of this loop is to provide the required stator current in the q-axis for regulating the electromagnetic torque. In the inner loops, two fractional-order PI (FOPI) controllers are designed to provide the stator voltages. Besides, since induction motors have a complex mathematical model, time-varying dynamics, and non-linear structure, to deal with these challenges in the controller design, the quantum neural network (QNN) is presented with a novel framework and employed to estimate the lumped uncertainties. This makes the main contribution of the paper. In addition, to further improve system performance, the parameters of the FOPI controllers are tuned by employing the artificial bee colony (ABC) optimization algorithm. The stability of the proposed control approach is proved by Lyapunov's stability theory. According to the results of the comparative simulation, the superiority of this approach is confirmed. • Addressing the position control of the IM using an effective control approach. • Presenting the QNN with a novel framework. • Estimating the lumped uncertainties using the adaptive QNN. • Combining the merits of the FOPI controllers, and NFTSMC. • Tuning the FOPI controllers using the ABC optimization algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates maximum power extraction from a wind-energy-conversion system (WECS) with a permanent magnet synchronous generator (PMSG) operating in standalone mode. This was achieved by designing a robust adaptive nonsingular fast terminal sliding mode control (ANFTSMC) for the WECS-PMSG. The proposed scheme guaranteed optimal power generation and suppressed the system uncertainties with a rapid convergence rate. Moreover, it is independent of the upper bounds of the system uncertainties as an online adjustment algorithm was utilized to estimate and compensate them. Finally, four case studies were carried out, which manifested the remarkable performance of ANFTSMC in comparison to previous methods reported in the literature. [ABSTRACT FROM AUTHOR]

In order to improve the performance in the practical engineering applications including so called low-speed video tracking and large-angle swing scanning imaging at the same time for a three-axis universal inertially stabilized platform (UISP), we propose an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) strategy subjected to the uncertain disturbances and input saturation constraints. First of all, a second-order dynamic model is established with uncertain disturbances and input saturation constraints. Secondly, a nonsingular fast terminal sliding mode controller (NTSMC) is constructed to ensure the system error converges to zero fast in a finite time; meanwhile, a novel reaching law based on a modified normal distribution function is designed to adjust the control gain. Thirdly, an adaptive control law is designed to online estimate the parameters of the lumped uncertain disturbances. Additionally, the stability of the control system is proved by Lyapunov theory. Finally, extensive comparative simulations and experiments are carried out, the results comprehensively show the effectiveness and superiority of the proposed control method, which can accelerate convergence, weaken the chattering, and has the better control accuracy and robust performance both in the low-speed tracking and large-angle swing scanning applications. Moreover, the exact dynamic model and the prior knowledge of the upper bounds of the disturbances are not required during the procedure of the controller design, which make it have more extensive application value in practical engineering. [ABSTRACT FROM AUTHOR]