A Hybrid Nonlinear Active Noise Control Method Using Chebyshev Nonlinear Filter

Investigations into active noise control(ANC)technique have been conducted with the aim of effective control of the low-frequency noise.In practice,however,the performance of currently available ANC systems degrades due to the effects of nonlinearity in the primary and secondary paths,primary noise and louder speaker.This paper proposes a hybrid control structure of nonlinear ANC system to control the non-stationary noise produced by the rotating machinery on the nonlinear primary path.A fast version of ensemble empirical mode decomposition is used to decompose the non-stationary primary noise into intrinsic mode functions,which are expanded using the second-order Chebyshev nonlinear filter and then individually controlled.The convergence of the nonlinear ANC system is also discussed.Simulation results demonstrate that proposed method outperforms the FSLMS and VFXLMS algorithms with respect to noise reduction and convergence rate.

Stability analysis of linear/nonlinear switching active disturbance rejection control based MIMO continuous systems

In this paper,a linear/nonlinear switching active disturbance rejection control(SADRC)based decoupling control approach is proposed to deal with some difficult control problems in a class of multi-input multi-output(MIMO)systems such as multi-variables,disturbances,and coupling,etc.Firstly,the structure and parameter tuning method of SADRC is introduced into this paper.Followed on this,virtual control variables are adopted into the MIMO systems,making the systems decoupled.Then the SADRC controller is designed for every subsystem.After this,a stability analyzed method via the Lyapunov function is proposed for the whole system.Finally,some simulations are presented to demonstrate the anti-disturbance and robustness of SADRC,and results show SADRC has a potential applications in engineering practice.

Chip-Based High-Dimensional Optical Neural Network

Parallel multi-thread processing in advanced intelligent processors is the core to realize high-speed and high-capacity signal processing systems.Optical neural network(ONN)has the native advantages of high parallelization,large bandwidth,and low power consumption to meet the demand of big data.Here,we demonstrate the dual-layer ONN with Mach-Zehnder interferometer(MZI)network and nonlinear layer,while the nonlinear activation function is achieved by optical-electronic signal conversion.Two frequency components from the microcomb source carrying digit datasets are simultaneously imposed and intelligently recognized through the ONN.We successfully achieve the digit classification of different frequency components by demultiplexing the output signal and testing power distribution.Efficient parallelization feasibility with wavelength division multiplexing is demonstrated in our high-dimensional ONN.This work provides a high-performance architecture for future parallel high-capacity optical analog computing.

Generation and Shaping of Soliton-Like Pulses along Resonant Tunneling Diodes NMOS Varactors Lattice

The characteristics of N-type accumulation-mode MOS (NMOS) varactors line periodically loaded with resonant tunneling diodes (RTDs) are used for soliton-like pulses generation and shaping. The problem of wide pulse breaking up into multiple pulses rather than a single is solved. Applying perturbative analysis, we show that the dynamics of the nonlinear transmission line (NLTL) is reduced to expanded Korteweg-de Vries (KdV) equation. Moreover, numerical integration of nonlinear differential and difference equations that result from the mathematical analysis of the line is discussed. As results, NLTL can simultaneously sharpen both leading and trailing of pulse edges and one could obtain a rising and sharpening step pulse.

Nonlinear Damped Oscillators on Riemannian Manifolds:Fundamentals

The classical theory of mass-spring-damper-type dynamical systems on the ordinary flat space R^3 may be generalized to higher-dimensional Riemannian manifolds by reformulating the basic underlying physical principles through differential geometry.Nonlinear dynamical systems have been studied in the scientific literature because they arise naturally from the modeling of complex physical structures and because such dynamical systems constitute the basis for several modern applications such as the secure transmission of information.The flows of nonlinear dynamical systems may evolve over time in complex,non-repeating(although deterministic) patterns.The focus of the present paper is on formulating the general equations that describe the dynamics of a point-wise particle sliding on a Riemannian manifold in a coordinate-free manner.The paper shows how the equations particularize in the case of some manifolds of interest in the scientific literature,such as the Stiefel manifold and the manifold of symmetric positive-definite matrices.

Active Disturbance Rejection Control for PMLM Servo System in CNC Machining

Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine.In this paper,based on the principle of Active Disturbance Rejection Control(ADRC),a control method is proposed,where both the extended state observer(ESO) and the reduced order extended state observer(RESO) are used to estimate and compensate for the disturbance.The authors prove that both approaches ensure high accuracy in theory,and give the criterion for parameters selection.The authors also prove that ADRC with RESO performs better than that with ESO both in disturbance estimation and tracking error.The simulation results on CNC machine show the effectiveness and feasibility of our control approaches.