Comparison of the compensation effects of fiber nonlinear impairments with mid-span optical phase conjugation between PDM CO-OFDM system and PDM QPSK system

The compensation effects of fiber nonlinearity in 112 Gb/s polarization division multiplexing（PDM） coherent optical systems by mid-span optical phase conjugation（OPC） based on four wave mixing（FWM） effect are studied. Comparisons of the compensation results between PDM coherent optical-orthogonal frequency division multiplexing（CO-OFDM）system and the single carrier（SC） PDM quadrature phase shift keying（QPSK） system are provided as well. The results demonstrate that nonlinear compensation effect with mid-span OPC in PDM CO-OFDM system is much more obvious than that in SC PDM QPSK system.

Step-size selection for split-step based nonlinear compensation with coherent detection in 112-Gb/s 16-QAM transmission

Non-uniform step-size distribution is implemented for split-step based nonlinear compensation in singlechannel 112-Gb/s 16 quadrature amplitude modulation （QAM） transmission. Numerical simulations of the system including a 20 × 80 km uncompensated link are performed using logarithmic step size distribution to compensate signal distortions. 50% of reduction in number of steps with respect to using constant step sizes is observed. The performance is further improved by optimizing nonlinear calculating position （NLCP） in case of using constant step sizes while NLCP optimization becomes unnecessary when using logarithmic step sizes, which reduces the computational effort due to uniformly distributed nonlinear phase for all successive steps.

Computationally Efficient Nonlinearity Compensation for Coherent Fiber-Optic Systems

Split-step digital backward propagation （DBP） can be combined with coherent detection to compensate for fiber nonlinear impairments. A large number of DBP steps is usually needed for a long-haul fiber system, and this creates a heavy computational load. In a trade-off between complexity and performance, interchannel nonlinearity can be disregarded in order to simplify the DBP algorithm. The number of steps can also be reduced at the expense of performance. In periodic dispersion-managed long-haul transmission systems, optical waveform distortion is dominated by chromatic dispersion. As a result, the nonlinearity of the optical signal repeats in every dispersion period. Because of this periodic behavior, DBP of many fiber spans can be folded into one span. Using this distance-folded DBP method, the required computation for a transoceanic transmission system with full inline dispersion compensation can be reduced by up to two orders of magnitude with negligible penalty. The folded DBP method can be modified to compensate for nonlinearity in fiber links with non-zero residua dispersion per span.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Nonlinear RCMC method for spaceborne/airborne forward-looking bistatic SAR

In the spaceborne/airborne forward-looking bistatic syn- thetic aperture radar （SA-FBSAR）, due to the system platforms＇ remarkable velocity difference and the forward-looking mode, the range cell migration （RCM） not only depends on the target＇s two- dimensional location, but also varies with the range location non- linearly. And the nonlinearity is not just the slight deviation from the linear part, but exhibits evident nonlinear departure in the RCM trajectory. If the RCM is not properly corrected, nonlinear image distortions would occur. Based on the RCM model, a modified two-step RCM compensation （RCMC） method for SA-FBSAR is proposed. In this method, firstly the azimuth-dependent RCM is compensated by the scaling Fourier transform and the phase multi- plication. And then the range-dependent RCM is removed through interpolation. The effectiveness of the proposed RCMC method is verified by the simulation results of both point scatterers and area targets.

Controlling chaos based on an adaptive nonlinear compensator mechanism

The control problems of chaotic systems are investigated in the presence of parametric uncertainty and persistent external disturbances based on nonlinear control theory. By using a designed nonlinear compensator mechanism, the system deterministic nonlinearity, parametric uncertainty and disturbance effect can be compensated effectively. The renowned chaotic Lorenz system subjected to parametric variations and external disturbances is studied as an illustrative example. From the Lyapunov stability theory, sufficient conditions for choosing control parameters to guarantee chaos control are derived. Several experiments are carried out, including parameter change experiments, set-point change experiments and disturbance experiments. Simulation results indicate that the chaotic motion can be regulated not only to steady states but also to any desired periodic orbits with great immunity to parametric variations and external disturbances.

A Model-Driven Approach to Enhance Faster-than-Nyquist Signaling over Nonlinear Channels

In order to increase the capacity of future satellite communication systems,faster-than-Nyquist(FTN)signaling is increasingly consideredI..Existing methods for compensating for the high power amplifier(HPA)nonlinearity require perfect knowledge of the HPA model.To address this issue,we analyze the FTN symbol distribution and propose a complex-valued deep neural network(CVDNN)aided compensation scheme for the HPA nonlinearity,which does not require perfect knowledge of the HPA model and can learn the HPA nonlinearity during the training process.A model-driven network for nonlinearity compensation is proposed to further enhance the performance.Furthermore,two training sets based on the FTN symbol distribution are designed for training the network.Extensive simulations show that the Gaussian distribution is a good approximation of the FTN symbol distribution.The proposed model-driven network trained by employing a Gaussian distribution to approximate an FTN signaling can achieve a performance gain of 0.5 dB compared with existing methods without HPA's parameters at the receiver.The proposed neural network is also applicable for non-linear compensation in other systems,including orthogonal frequency-division multiplexing(OFDM).

Robust Adaptive Actuator Failure Compensation for a Class of Uncertain Nonlinear Systems

This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compensates a general class of actuator failures without any need for explicit fault detection. The parameters, times, and patterns of the considered failures are completely unknown. The proposed controller is constructed based on a backstepping design method. The global boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. The proposed approach is employed for a two-axis positioning stage system as well as an aircraft wing system. The simulation results show the correctness and effectiveness of the proposed robust adaptive actuator failure compensation approach.

Capacity Scaling Limits and New Advancements in Optical Transmission Systems

Optical transmission technologies have gone through several generations of development.Spectral efficiency has significant ly improved,and industry has begun to search for an answer to a basic question：What are the fundamental linear and nonlin ear signal channel limitations of the Shannon theory when there is no compensation in an optical fiber transmission system？Next-generation technologies should exceed the 100G transmis sion capability of coherent systems in order to approach the Shannon limit.Spectral efficiency first needs to be improved be fore overall transmission capability can be improved.The means to improve spectral efficiency include more complex modulation formats and channel encoding/decoding algorithms,prefiltering with multisymbol detection,optical OFDM and Ny quist WDM multicarrier technologies,and nonlinearity compen sation.With further optimization,these technologies will most likely be incorporated into beyond-100G optical transport sys tems to meet bandwidth demand.

Dynamic parameter identification and nonlinear friction compensation method for safety perception of heavy explosion-proof robots

This article focuses on the problem of how to accurately calculate the joint control torques when the explosion-proof robot performs collision detection without sensors and gives a complete solution.Nonlinear joint frictions are incorporated into the dynamic model of a robotic manip-ulator to improve calculation accuracy.A genetic algorithm is used to optimise the excitation trajectories to fully stimulate the robot dynamic characteristics.Effective and applicable data filtering and smoothing methods are proposed and the Iteratively Reweighted Least-Squares method based on the error term is applied to identify the robot dynamic parameters.Compared with Ordinary Least-Squares method,the proposed algorithm improves the accuracy of joint control torques estimation.

Neural network equalization based on delta-sigma modulation

We propose a neural network equalization delta-sigma modulation(DSM)technique.After performing DSM on the multiorder quadrature amplitude modulation(QAM)orthogonal frequency division multiplexing(OFDM)signal at the transmitting end,neural network equalizer technology is used in the digital signal processing at receiving end.Applying this technology to a 4.6 km W-band millimeter wave system,it is possible to achieve a 1 Gbaud 8192-QAM OFDM signal transmission.The data rate reached 23.4 Gbit/s with the bit error rate at 3.8×10^(-2),lower than soft-decision forward-error correction threshold(4×10^(-2)).

Adaptive sliding mode control of the A-axis used for blisk manufacturing

As a key assembly in the 5-axis CNC machine tools, positioning precision of the A-axis directly affects the machining accuracy and surface quality of the parts. First of all, mechanical structure and control system of the A-axis are designed. Then, considering the influence of nonlin- ear friction, backlash, unmodeled dynamics, uncertain cutting force and other external disturbance on the control precision of the A-axis, an adaptive sliding mode control （ASMC） based on extended state observer （ESO） is proposed. ESO is employed to estimate the state variables of the unknown system and an adaptive law is adopted to compensate for the input dead-zone caused by friction, backlash and other nonlinear characteristics. Finally, stability of the closed-loop system is guaran- teed by the Lyapunov theory. Positioning experiments illustrate the perfect estimation of ESO and the stronger anti-interference and robustness of ASMC, which can improve the control precision of the A-axis by about 40 times. Processing experiments show that the ASMC can reduce the waviness, averaKe error and roughness of the nrocessed surface by 35.63%, 31.31% and 30.35%, respectively.