In this paper, a novel finite time fault tolerant control (FTC) is proposed for uncertain robot manipulators with actuator faults. First, a finite time passive FTC (PFTC) based on a robust nonsingular fast terminal sliding mode control (NFTSMC) is investigated. Be analyzed for addressing the disadvantages of the PFTC, an AFTC are then investigated by combining NFTSMC with a simple fault diagnosis scheme. In this scheme, an online fault estimation algorithm based on time delay estimation (TDE) is proposed to approximate actuator faults. The estimated fault information is used to detect, isolate, and accommodate the effect of the faults in the system. Then, a robust AFTC law is established by combining the obtained fault information and a robust NFTSMC. Finally, a high-order sliding mode (HOSM) control based on super-twisting algorithm is employed to eliminate the chattering. In comparison to the PFTC and other state-of-the-art approaches, the proposed AFTC scheme possess several advantages such as high precision, strong robustness, no singularity, less chattering, and fast finite-time convergence due to the combined NFTSMC and HOSM control, and requires no prior knowledge of the fault due to TDE-based fault estimation. Finally, simulation results are obtained to verify the effectiveness of the proposed strategy.

This paper develops a novel control methodology for tracking control of robot manipulators based on a novel adaptive backstepping nonsingular fast terminal sliding mode control (ABNFTSMC). In this approach, a novel backstepping nonsingular fast terminal sliding mode controller (BNFTSMC) is developed based on an integration of integral nonsingular fast terminal sliding mode surface and a backstepping control strategy. The benefits of this approach are that the proposed controller can preserve the merits of the integral nonsingular fast terminal sliding mode control in terms of high robustness, fast transient response, and finite time convergence, and of backstepping control strategy in terms of globally asymptotic stability based on Lyapunov criterion. However, the major limitation of the proposed BNFTSMC is that its design procedure is dependent on the prior knowledge of the bound value of the disturbance and uncertainties. In order to overcome this limitation, an adaptive technique is employed to approximate the upper bound value; yielding an adaptive backstepping nonsingular fast terminal sliding mode control (ABNFTSMC) is recommended. The proposed controller is then applied for tracking control of a PUMA560 robot and compared with other state-of-the-art controllers, such as computed torque controller (CTC), PID controller, conventional PID-based sliding mode controller (PID-SMC), and nonsingular fast terminal sliding mode control (NFTSMC). The comparison results demonstrate the superior performance of the proposed approach. Index Terms-Control of robots, backstepping control, fault tolerant control, terminal sliding mode control. I. INTRODUCTIONRACKING CONTROL of robot manipulators, which is required to provide high accuracy, stability and safety in some applications such as industrial robotics, surgical robotics, assistive robotics, in the presence of huge Manuscript

This paper develops an enhanced robust fault tolerant control (FTC) using a novel adaptive fuzzy PID-based nonsingular fast terminal sliding mode (AF-PID-NFTSM) control for a class of second-order uncertain nonlinear systems. In this approach, a new type of sliding surface, called PID-NFTSM, which combines the benefits of the PID and NFTSM sliding surfaces, is proposed to enhance the robustness and reduce the steady state error, whilst preserving the great property of the conventional NFTSM controller. A fuzzy approximator is designed to approximate the uncertain system dynamics and an adaptive law is developed to estimate the bound of the approximation error so that the proposed robust controller does not require a need of the prior knowledge of the bound of the uncertainties and faults and the exact system dynamics. The proposed approach is then applied for attitude control of a spacecraft. The simulation results verify the superior performance of the proposed approaches over other existing advanced robust fault tolerant controllers.

This paper develops a new strategy for robust fault tolerant control (FTC) of robot manipulators using an adaptive fuzzy integral sliding mode control and a disturbance observer (DO). First, an integral sliding mode control (ISMC) is developed for the FTC system. The major features of the approach are discussed. Then, to enhance performance of the system, a fuzzy logic system (FLS) approximation and a DO are introduced to approximate the unknown nonlinear terms, which include the model uncertainty and fault components, and estimates the compounded disturbance, respectively, and then integrated into the ISMC. Next, a switching term based on an adaptive twolayer super-twisting algorithm is designed to compensate the disturbance estimated error and guarantee stability and convergence of the whole system. The nominal controller of the ISMC is reconstructed using backstepping control technique to achieve the stability for the nominal system based on Lyapunov criteria. The computer simulation results demonstrate the effectiveness of the proposed approach.

In this work, a new robust controller is developed for robot manipulator based on an integrating between a novel self-tuning fuzzy proportional-integral-derivative (PID)nonsingular fast terminal sliding mode control (STF-PID-NFTSM) and a time delay estimation (TDE). A sliding surface based on the PID-NFTSM is designed for robot manipulators to get multiple excited features such as faster transient response with finite time convergence, lower error at steady-state and chattering elimination. However, the system characteristics are hugely affected by the selection of the PID gains of the controller. In addition, the design of the controller requires an exact dynamics model of the robot manipulators. In order to obtain effective gains for the PID sliding surface, a fuzzy logic system is employed and in order to get an estimation of the unknown dynamics model, a TDE algorithm is developed. The innovative features of the proposed approach, i.e., STF-PID-NFTSM, is verified when comparing with other up-to-date advanced control techniques on a PUMA560 robot.

Conventional sliding mode control (SMC) has been extensively developed for design of fault tolerant control (FTC) systems. However, the used of conventional SMC has several disadvantages such as large transient state error, less robustness and large chattering, that limit its application for real application. In order to enhance the performance, a novel passive fault tolerant control (AFTC) based on a chattering-free adaptive third-order sliding mode control (ATOSMC), which integrates a novel third-order sliding mode surface (TOSMS) with a continuous strategy and an adaptation law, is proposed. Compared to other state-of-the-art approaches, the proposed controller has a great fault-tolerant capability to accommodate several types of actuator faults with an enhancing on robustness, precision, chattering reduction and time of convergence. The proposed analytical results are then applied to the attitude control of a spacecraft. Simulation results demonstrate the superior performance of the proposed algorithm.

Bearing defect classification based on individual trained wavelet kernel local fisher discriminant analysis with particle swarm optimization. IEEE Transactions on Industrial Informatics.

The presence of faults in the bearings of rotating machinery is usually observed with impulses in the vibration signals. However, the vibration signals are generally non-stationary and usually contaminated by noise because of the compounded background noise present in the measuring device and the effect of interference from other machine elements. Therefore in order to enhance monitoring condition, the vibration signal needs to be properly de-noised before analysis. In this study, a novel fault diagnosis method for rolling element bearings is proposed based on a hybrid technique of non-local means (NLM) de-noising and empirical mode decomposition (EMD). An NLM which removes the noise with minimal signal distortion is first employed to eliminate or at least reduce the background noise present in the measuring device. This de-noised signal is then decomposed into a finite number of stationary intrinsic mode functions (IMF) to extract the impulsive fault features from the effect of interferences from other machine elements. Finally, envelope analyses are performed for IMFs to allow for easier detection of such characteristic fault frequencies. The results of simulated and real bearing vibration signal analyses show that the hybrid feature extraction technique of NLM de-noising, EMD and envelope analyses successfully extract impulsive features from noise signals.