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In this paper, a novel active disturbance rejection control (NADRC) with a super-twisting extended state observer (SESO) is utilized in the rocket launcher servo system. The main arguments in the shipborne rocket launcher system are control accuracy and antidisturbance ability, which are closely related to phase delay and bandwidth. Firstly, we use Taylor's formula approach to compensate the phase delay in traditional tracking differentiator (TD). Secondly, we design the parallel structured SESO to improve the observation bandwidth, so that it can estimate states with desired accuracy in NADRC. Finally, sinusoidal simulation results show Taylor's formula-based TD can suppress noise and compensate phase delays effectively. In comparison with traditional ADRC, the proposed NADRC is shown to have better tracking performance and stronger robustness. Semiphysical experiments are conducted to prove the feasibility of NADRC. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motors (PMSMs) have been widely applied in the shipborne rocket launcher systems due to their high torque density and high efficiency. However, since there are many external disturbances from the shipborne rocket launcher, the tracking performance under random noises needs to be improved. In this paper, an improved finite control set optimal control (IFCSOC) based on a super-twisting extended state observer (SESO) is investigated for position tracking control of PMSMs. The SESO can improve the anti-interference ability of the proposed controller. Moreover, in order to improve tracking accuracy, Taylor's formula is used to solve the phase-lag problem of nonlinear tracking differentiator in IFCSOC. Simulation shows that compared with conventional FCSOC, IFCSOC exhibits better robustness under random disturbances. Furthermore, the semiphysical experiment is conducted to verify the proposed IFCSOC strategy. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motors (PMSMs) have been widely applied in the shipborne rocket launcher systems due to their high torque density and high efficiency. However, since there are many external disturbances from the shipborne rocket launcher, the tracking performance under random noises needs to be improved. In this paper, an improved finite control set optimal control (IFCSOC) based on a super-twisting extended state observer (SESO) is investigated for position tracking control of PMSMs. The SESO can improve the anti-interference ability of the proposed controller. Moreover, in order to improve tracking accuracy, Taylor's formula is used to solve the phase-lag problem of nonlinear tracking differentiator in IFCSOC. Simulation shows that compared with conventional FCSOC, IFCSOC exhibits better robustness under random disturbances. Furthermore, the semiphysical experiment is conducted to verify the proposed IFCSOC strategy. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motors (PMSMs) have been widely applied in the shipborne rocket launcher systems due to their high torque density and high efficiency. However, since there are many external disturbances from the shipborne rocket launcher, the tracking performance under random noises needs to be improved. In this paper, an improved finite control set optimal control (IFCSOC) based on a super-twisting extended state observer (SESO) is investigated for position tracking control of PMSMs. The SESO can improve the anti-interference ability of the proposed controller. Moreover, in order to improve tracking accuracy, Taylor's formula is used to solve the phase-lag problem of nonlinear tracking differentiator in IFCSOC. Simulation shows that compared with conventional FCSOC, IFCSOC exhibits better robustness under random disturbances. Furthermore, the semiphysical experiment is conducted to verify the proposed IFCSOC strategy. [ABSTRACT FROM AUTHOR]

A novel self-organizing adaptive wavelet cerebellar model articulation controller backstepping (SOWCB) control is proposed, aiming at some nonlinear and uncertain factors that caused difficulties in controlling the AC servo system. This controller consists of self-organizing wavelet cerebellar model articulation controller (CMAC) and robust compensator. It absorbs fast learning and precise approaching advantage of self-organizing wavelet CMAC to mimic a backstepping controller, and then robust compensator is added to inhibit influence of the uncertainties on system performance effectively and realize high accuracy position tracking for AC servo system. Moreover, the stability of the control system can be guaranteed by using Lyapunov method. The results of the simulation and the prototype test prove that the proposed approach can improve the steady state performance and control accuracy and possess a strong robustness to both parameter perturbation and load disturbance. [ABSTRACT FROM AUTHOR]

In order to achieve better motion accuracy and higher robustness of the shipborne rocket launcher position servo system driven by a permanent magnet synchronous motor (PMSM), a passivity-based controller based on active disturbance rejection control (ADRC) optimized by improved particle swarm optimization-back propagation (IPSO-BP) algorithm is proposed in this paper. The convenient method of interconnection and damping assignment and passivity-based control (IDA-PBC) is adopted to establish the port controlled Hamiltonian system with dissipation (PCHD) model of PMSM. To further enhance the robustness and adaptability of traditional ADRC, an BP algorithm is introduced to on-line update the proportional, integral, and derivative gains of ADRC. Furthermore, to improve the learning capability, the improved PSO algorithm is adopted to optimize the learning rates of the back propagation neural networks. The results of numerical simulation and prototype test indicate that the proposed IPSO-BP-ADRC-PBC controller has better static and dynamic performance than the ADRC-PBC and BP-ADRC-PBC controller with fixed learning rate. [ABSTRACT FROM AUTHOR]

Signals with multiple components and fast-varying instantaneous frequencies reduce the readability of the time-frequency representations obtained by traditional synchrosqueezing transforms due to time-frequency blurring. We discussed a vertical synchrosqueezing transform, which is a second-order synchrosqueezing transform based on the short-time Fourier transform and compared it to the traditional short-time Fourier transform, synchrosqueezing transform, and another form of the second-order synchrosqueezing transform, the oblique synchrosqueezing transform. The quality of the time-frequency representation and the accuracy of mode reconstruction were compared through simulations and experiments. Results reveal that the second-order frequency estimator of the vertical synchrosqueezing transform could obtain accurate estimates of the instantaneous frequency and achieve highly energy-concentrated time-frequency representations for multicomponent and fast-varying signals. We also explored the application of statistical feature parameters of time-frequency image textures for the early fault diagnosis of roller bearings under fast-varying working conditions, both with and without noise. Experiments showed that there was no direct positive correlation between the resolution of the time-frequency images and the accuracy of fault diagnosis. However, the early fault diagnosis of roller bearings based on statistical texture features of high-resolution images obtained by the vertical synchrosqueezing transform was shown to have high accuracy and strong robustness to noise, thus meeting the demand for intelligent fault diagnosis. [ABSTRACT FROM AUTHOR]