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.

This paper investigates the finite-time command filtered backstepping control problem for dual-motor servo systems. The advantages of the finite-time controller include fast convergence and high robustness which can improve the dynamic and steady control performance of the system. However, the controller often contains nonlinear and exponential terms increasing the computational complexity. Consequently, for the convenience of practical applications, the command filtered technique is utilized to decrease the computational burden causing by repeated derivatives in the backstepping process. Besides, LuGre friction model is used to describe the system friction and a fuzzy logic system is designed to handle it. Only one adaptive parameter is estimated, which makes it suitable for industrial applications. Finally, the stability of the closed-loop system is proved and two experiments are carried out to show the advantages of the proposed scheme.

With the popularization of computerized digital control systems, the discrete-time control design has attracted increasing attention. This article presents a novel discrete-time second-order multipower terminal sliding-mode control (DSMTSC) for the position tracking of multimotor driving servo systems. Instead of the traditional dynamic model, a discrete-time characteristic model, which possesses lower order and fewer parameters, is built based on the system input–output data. In the DSMTSC design, a multipower sliding function is constructed fitting different convergence stages, which achieves faster convergence rate and higher tracking precision than conventional terminal sliding functions. Furthermore, an improved reaching law is designed to avoid the integral saturation, and the high-order sliding-mode approach is utilized to reduce the chattering. The finite-step boundedness of both the sliding functions and the tracking error is proved by rigorous theoretical analysis. Comparative experiments are conducted on a four-motor driving servo turntable, and the results verify the advantages of the DSMTSC, which are particularly suitable for practical application.

This paper presents an adaptive fast finite-time consensus (FTC) for second-order uncertain nonlinear (UN) multi-agent systems (MASs) with unknown nonsymmetric dead-zone and external disturbances. In the process of control protocols design, based on the estimation of the dead-zone width that is obtained by using adaptive method, a fuzzy logic dead-zone compensator is adopted to deal with the nonsymmetric dead-zone input phenomenon. Combining finite-time control technique and Lyapunov’s relevant theory, a new fast FTC protocol is developed. Based on the basis of radial basis function neural networks (RBFNNs) theories, the unknown nonlinear functions are approximated. Under the presented consensus protocols and adaptive laws, it can be proved that the position errors of arbitrary two agents can reach a small region of zero in finite time as well as the velocity errors. Ultimately, the effectiveness of the designed method is tested via two numerical examples.

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.