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A multi‐motor coordinated tracking control strategy based on a disturbance sliding‐mode observer and an anti‐saturation non‐singular fast‐terminal sliding mode is proposed to address the issues of slow convergence and controller output saturation in multi‐motor coordinated control systems. Firstly, a mathematical model of a multi‐motor traction system considering uncertain parameter perturbations, external disturbances, and dead zones was established. Secondly, a disturbance sliding‐mode observer was designed based on the mathematical model to eliminate motor disturbances and estimate the torque. The observer's forward compensation was added to design a total‐consensus‐based fast non‐singular terminal sliding‐mode controller. Then, a fast anti‐saturation auxiliary system with fast finite‐time convergence was constructed. Finally, a comparative experiment was conducted with traditional anti‐saturation sliding‐mode control to demonstrate that the proposed method had faster convergence, stronger disturbance rejection, and better tracking performance in the presence of multi‐motor parameter perturbations, unknown disturbances, and input saturation.

•An improved delay-dependent stability criterion is derived for linear time-delay systems with two constant delays with overlapping ranges.•This overlapping feature of the delays is exploited in the delay-dependent analysis using Lyapunov–Krasovskii approach to reduce conservatism compared to the approaches treating the delays individually.•The proposed approach is less conservative than existing approaches. In this paper, an adaptive super twisting sliding mode controller (ASTSMC) is proposed for a class of nonlinear systems to counteract mismatched uncertainties. To estimate the unknown external disturbance efficiently, an adaptive terminal sliding mode disturbance observer (ATSMDO) is proposed. The stability of the over all closed loop system is proved by Lyapunov stability theory. To validate the proposed ATSMDO based ASTSMC, a case study of a nonlinear liquid level regulation problem is considered. Both simulation and real-time results are presented to show the effectiveness of the proposed controller than the traditional adaptive sliding mode controller (ASMC) and reported controllers in literature. From the analysis, it is observed that the proposed controller alleviates the chattering problem effectively.

In this paper, a robust wheel slip control system based on a sliding mode controller is proposed for improving traction-ability and reducing energy consumption during sudden acceleration for a personal electric vehicle. Sliding mode control techniques have been employed widely in the development of a robust wheel slip controller of conventional internal combustion engine vehicles due to their application effectiveness in nonlinear systems and robustness against model uncertainties and disturbances. A practical slip control system which takes advantage of the features of electric motors is proposed and an algorithm for vehicle velocity estimation is also introduced. The vehicle velocity estimator was designed based on rotational wheel dynamics, measurable motor torque, and wheel velocity as well as rule-based logic. The simulations and experiments were carried out using both CarSim software and an experimental electric vehicle equipped with in-wheel-motors. Through field tests, traction performance and effectiveness in terms of energy saving were all verified. Comparative experiments with variations of control variables proved the effectiveness and practicality of the proposed control design.

This paper considers the problem of robust reconstruction of simultaneous actuator and sensor faults for a class of uncertain Takagi-Sugeno nonlinear systems with unmeasurable premise variables. The proposed fault reconstruction and estimation design method with H performance is used to reconstruct both actuator and sensor faults when the latter are transformed into pseudo-actuator faults by introducing a simple filter. The main contribution is to develop a sliding mode observer (SMO) with two discontinuous terms to solve the problem of simultaneous faults. Sufficient stability conditions in terms linear matrix inequalities are achieved to guarantee the stability of the state estimation error. The observer gains are obtained by solving a convex multiobjective optimization problem. Simulation examples are given to illustrate the performance of the proposed observer

Rotating machines represent a class of nonlinear, uncertain, and multiple-degrees-of-freedom systems that are used in various applications. The complexity of the system’s dynamic behavior and uncertainty result in substantial challenges for fault estimation, detection, and identification in rotating machines. To address the aforementioned challenges, this paper proposes a novel technique for fault diagnosis of a rolling-element bearing (REB), founded on a machine-learning-based advanced fuzzy sliding mode observer. First, an ARX-Laguerre algorithm is presented to model the bearing in the presence of noise and uncertainty. In addition, a fuzzy algorithm is applied to the ARX-Laguerre technique to increase the system’s modeling accuracy. Next, the conventional sliding mode observer is applied to resolve the problems of fault estimation in a complex system with a high degree of uncertainty, such as rotating machinery. To address the problem of chattering that is inherent in the conventional sliding mode observer, the higher-order super-twisting (advanced) technique is introduced in this study. In addition, the fuzzy method is applied to the advanced sliding mode observer to improve the accuracy of fault estimation in uncertain conditions. As a result, the advanced fuzzy sliding mode observer adaptively improves the reliability, robustness, and estimation accuracy of rolling-element bearing fault estimation. Then, the residual signal delivered by the proposed methodology is split in the windows and each window is characterized by a numerical parameter. Finally, a machine learning technique, called a decision tree, adaptively derives the threshold values that are used for problems of fault detection and fault identification in this study. The effectiveness of the proposed algorithm is validated using a publicly available vibration dataset of Case Western Reverse University. The experimental results show that the machine learning-based advanced fuzzy sliding mode observation methodology significantly improves the reliability and accuracy of the fault estimation, detection, and identification of rolling element bearing faults under variable crack sizes and load conditions.

This paper designs an improved sliding mode observer (ISMO) compound control scheme combined with a disturbance observer to solve the chattering and anti-disturbance problems of the traditional sliding mode observer (SMO) for permanent magnet synchronous motor (PMSM) in a sensorless control system. First, the sign function is replaced by an exponential type input function, and the fuzzy control rules are developed to automatically regulate the boundary layer control coefficient of the exponential input function, thereby changing the convergence characteristics of the exponential input function and improving the system observation accuracy. Then, the integral sliding mode surface and the quadratic radical term function of the square of the state variable are introduced to reduce system chattering. The proposed ISMO is proved using Lyapunov’s law to guarantee the whole system is stable. Based on the exponential input function and the integral sliding surface, an improved sliding mode disturbance observer (ISMDO) is constructed as a feed-forward compensator, which can optimize the dynamic performance of the improved observation system and ensure the strong robustness of the system by compensating the q-axis current. Finally, MATLAB/Simulink simulation and experimental platform verification have been carried out, which confirms the feasibility of the proposed composite control scheme.

In this paper, we propose the estimation of contact force in a collaborative robot without explicit force-sensing based on the adaptive third-order sliding mode observer. An adaptive third-order sliding mode observer was designed to estimate the contact force based only on the position measurement. The information from the observer was used for admittance control and emergent stop control when the robot interacts with a human. The experimental results with the emergent stop control and admittance control, using the proposed contact force estimation for the 3-DOF AT2-FARA robot manipulator, illustrate the capability of the proposed system in real-world application.

This paper presents a fault detection and isolation system for the satellites attitude control. The fault detection and isolation system is based on an innovative bank of sliding mode observers, designed taking into account the satellite nonlinear dynamics. The observers are based on the sliding mode control theory, thus being robust to parametric uncertainties and bounded disturbances. A pseudo-sliding law is used to avoid the chattering effect and to reconstruct disturbances and faults based on equivalent injection signal. The bank of observers contains a total of seven sliding mode observers designed for different working scenarios. The first sliding mode observer is called the global observer and it is used to detect the fault appearance in the system, based on the equivalent injection signal. The other sliding mode observers are used to isolate and report any malfunction that may occur in the satellite's guidance and control unit. In order to reduce false alarms a mean window is used over the equivalent injection signal.

Interplanetary space missions require spacecraft autonomy in order to fulfill the mission objective. The fault detection and isolation (FDI) system increases the level of autonomy and can ensure the safety of the spacecraft by detecting and isolating potential faults before they become critical. The proposed FDI system is based on an innovative bank of SMOs (sliding mode observers), designed for different fault scenarios cases. The FDI system design aims to detect and isolate actuators and measurement units’ faults used by the satellite control system and considers the nonlinear model of the satellite dynamics. This approach gives the possibility of fault reconstruction based on the information provided by an equivalent injection signal, allowing to reconstruct external perturbances and faults. The SMO chattering phenomenon is avoided by using the pseudo-sliding function, being a linear approximation of the signum function, which gives the possibility of using the equivalent injection signal for fault reconstruction purposes. The proposed fault reconstruction methodology is illustrated by a case study for a 6U Cubesat.

To enhance the dynamic performance and disturbance rejection capability of the permanent magnet synchronous motor speed control system, a novel speed control method based on a novel sliding mode control (NSMC) and load torque observer is proposed on the basis of model predictive current control (MPCC) with a sliding mode disturbance observer. First, on the basis of MPCC, the influence of parameters such as resistance, inductance, and flux linkage on MPCC is analyzed. To address the aggregated disturbance caused by parameter mismatches, a piecewise square-root switching function sliding mode disturbance observer (SMDO) is designed to enhance the robustness of the parameters. To address the poor dynamic performance and inadequate robustness resulting from the proportional-integral-controller (PI) velocity loop control in the MPCC, a novel NSMC velocity control method is proposed. This method utilizes the hyperbolic sine function and fractional-order integral sliding mode surface, resolving the dilemma faced by traditional slide mode controllers (SMC) in balancing fast response and reduced vibration. Additionally, to enhance the system’s disturbance rejection capability, a sliding mode torque observer (SMTO) is designed to continuously update the observed load torque value into the NSMC controller, achieving speed compensation control. Finally, through comparative experiments among the proportional integral controller (PI), SMC, NSMC, and NSMC + SMTO, the results indicate that the proposed NSMC + SMTO exhibits the best speed response, steady-state characteristics, and disturbance rejection capability.