First-order Filter Research Articles

0.3-V Voltage-Mode Versatile First-Order Analog Filter Using Multiple-Input DDTAs.

This paper presents a versatile first-order analog filter using differential difference transconductance amplifiers (DDTAs). The DDTA employs the bulk-driven (BD) multiple-input MOS transistors technique (MI-MOST) operating in the subthreshold region. This results in low-voltage and low-power operational capability. Therefore, the DDTA, designed using 130 nm CMOS technology from UMC in the Cadence environment, operates with 0.3 V and consumes 357.4 nW. Unlike previous works, the proposed versatile first-order analog filter provides first-order transfer functions of low-pass, high-pass, and all-pass filters within a single topology. The non-inverting, inverting, and voltage gain of the transfer functions are available for all filters. Furthermore, the proposed structure provides high-input and low-output impedance, which is required for voltage-mode circuits. The pole frequency and voltage gain of the filters can be electronically controlled. The total harmonic distortion of the low-pass filter was calculated as -39.97 dB with an applied sine wave input signal of 50 mVpp@ 50 Hz. The proposed filter has been used to realize a quadrature oscillator to confirm the advantages of the new structure.

Current-Mode First-Order Versatile Filter Using Translinear Current Conveyors with Controlled Current Gain

This paper offers a new current-mode first-order versatile filter employing two translinear current conveyors with controlled current gain and one grounded capacitor. The proposed filter offers the following features: realization of first-order transfer functions of low-pass, high-pass, and all-pass current responses from single topology, availability of non-inverting and inverting transfer functions for all current responses, electronic control of current gain for all current responses, no requirement of component-matching conditions for realizing all current responses, low-input impedance and high-output impedance which are required for current-mode circuits, and electronic control of the pole frequency for all current responses. The proposed first-order versatile filter is used to realize a quadrature sinusoidal oscillator to confirm the advantage of the new topology. To confirm the functionality and workability of new circuits, the proposed circuit and its application are simulated by the SPICE program using transistor model process parameters NR100N (NPN) and PR100N (PNP) of bipolar arrays ALA400-CBIC-R from AT&T.

A dual-layer cooperative control strategy of battery energy storage units for smoothing wind power fluctuations

The large-scale integration of wind power with intermittent characteristics into grids brings a challenge to the power system. Installation of the battery storage energy system (BESS) in a wind farm (WF) can effectively smooth wind power fluctuation. However, the BESS units may face the problem of over-charge/over-discharge if the power dispatch strategy for multiple units of BESS is improper, which results in lifetime degradation. In this paper, a dual-layer cooperative control strategy of multiple BESS units is proposed. In the first layer, the time-varying characteristics of wind power are introduced to define a power fluctuation coefficient. The coefficient can adjust the time constant of the first-order low pass filter (FLF) to avoid the deep energy utilization of BESS and decrease the over-charge/over-discharge possibility. To facilitate more power output for units with high SOC and absorb more energy for units with low SOC, the second layer calculates a SOC distribution factor by a function of the SOC of each unit to allocate the power command. The two layers of control operate cooperatively to reduce the SOC variation and unbalance degrees, thus the over-charge/over-discharge can be avoided, which is good for prolonging the lifetime of BESS with multiple units. Taking an actual WF in the Hunan province of China as the research object, the effectiveness of the proposed strategy is verified by the co-simulation of DIgSILENT/PowerFactory and Matlab/Simulink.

Neuroadaptive Dynamic Surface Asymptotic Tracking Control of a VTOL Aircraft with Unknown Dynamics and External Disturbances

This work studies the asymptotic tracking control problem of a vertical take-off and landing (VTOL) aircraft with unknown dynamics and external disturbances. The unknown nonlinear dynamics of the VTOL aircraft are approximated via the introduction of radial basis function neural networks. Then, the weight update laws are designed. Furthermore, the parameter update control laws are presented to deal with the errors generated during the approximation process and the external disturbances of the aircraft system. Moreover, first-order filters are introduced to avoid repeated differentiation of the designed virtual control laws, thereby effectively eliminating the “complexity explosion” problem caused by traditional backstepping control. Based on the application of the neural network control method, dynamic surface control technique, weight update laws and parameter update control laws, neuroadaptive dynamic surface control laws for the aircraft system are finally proposed. Theoretical analysis shows that the proposed control law can ensure that the aircraft system asymptotically tracks the reference trajectories and the tracking errors can converge to a small neighborhood of zero by choosing the appropriate designed parameters. Finally, simulation examples are provided to verify the effectiveness of proposed control laws.

Decentralized Adaptive Quantized Dynamic Surface Control for a Class of Flexible Hypersonic Flight Vehicles with Input Quantization

A control strategy for a certain class of hypersonic flight aircraft dynamic models with unknown parameters is proposed in this article. The strategy is adaptive dynamic surface input quantization control. To address the issues in conventional inversion control, a first-order low-pass filter and an adaptive parameter minimum learning law are introduced in the control system design process. This method has the following features: (1) it solves the problem of repeated differentiation of the virtual control law in the conventional back-stepping method, greatly simplifying the control law structure; (2) by using the norm of the neural network weight vector as the adaptive adjustment parameter instead of updating each element online, the number of adaptive adjustment parameters is significantly reduced, improving the execution efficiency of the controller; (3) the introduced hysteresis quantizer overcomes the disadvantage of the quantization accuracy deterioration when the input value is too low in the logarithm quantizer, improving the accuracy of the quantizer. Stability analysis has shown that all signals in the closed-loop system are semi-globally uniformly bounded, and simulation results have verified the effectiveness of the proposed adaptive quantized control scheme.

Nonlinear Uncertainty Estimator-Based Robust Control for PMSM Servo Mechanisms With Prescribed Performance

Active nonlinear uncertainties compensation is crucial for realizing high-precision servo control. However, the rejection of the unknown uncertainties is still a challenging problem. In view of these issues, this paper proposes a novel nonlinear uncertainty estimator based time-varying sliding mode control scheme for servo systems with prescribed performance. A nonlinear uncertainty estimator, which employs first-order low-pass filter operations with only one tuning parameter, is constructed to deal with unknown nonlinearities, while the NDE estimation error and uncertainties of the servo system are handled by the robust integral of the sign of the error (RISE) feedbacks. Meanwhile, a modified prescribed performance function (PPF) with a faster convergence rate is incorporated into the control design to restricted the tracking errors within the predefined asymptotic boundaries. By combining PPF and NDE, a time-varying sliding mode controller is developed to eliminate the reaching phase and improve the control performance. The validity and feasibility of the presented control scheme are verified with simulations and experiments based on a motor driving system.

Barrier Lyapunov Function Based Model Predictive Control of a Morphing Waverider With Input Saturation and Full-State Constraints

With the fast development in aeronautical technology, aircraft are evolving towards a wider speed ranging from subsonic, transonic, and supersonic to hypersonic speeds. The variable-sweep-wing morphing waverider provides an effective way to meet the demanding wide-speed and long-range flight requirements. However, the special morphing mechanism, variable stability margin, and the aero-thermal heating of the morphing waverider, altogether impose difficulties and challenges on its flight tracking control problem, especially under parameter uncertainties, input saturation, and state constraints. To handle this issue, a six-degrees-of-freedom (6DOF) Barrier-Lyapunov-Function (BLF) based nonlinear model predictive controller (NMPC) consisting of two loops is proposed in this paper based on the control-oriented model of a symmetric-sweep-wing morphing waverider. Specifically, a virtual control signal of three-axis angular rates is provided by the BLF based outer-loop NMPC to not violate the flight constraints, combined with an auxiliary system according to the desired angle of attack, sideslip angle, and bank angle. Then, the desired virtual control signal is modified by a saturation function and a first-order command filter, and the control commands are generated by the BLF based inner-loop NMPC to deal with the input saturation by an auxiliary system. Meanwhile, a nonlinear disturbance observer is applied to estimate the morphing moments considering parameter uncertainties. The stability of the overall closed-loop system is analyzed by the Lyapunov stability theory. Finally, the performance of the controller is investigated via extensive and comparative numerical simulations.

Discrete-Time Adaptive Neural Tracking Control and Its Experiments for Quadrotor Unmanned Aerial Vehicle Systems

For the control of a quadrotor unmanned aerial vehicle, the strong nonlinearities, coupling, and underactuated problem in both positioning and attitude systems of the quadrotor are major challenging issues to be solved. In this article, a discrete-time adaptive dynamic surface control (DSC) scheme for the quadrotor is proposed to obtain a satisfactory tracking performance. The nonlinearities and couplings are overcome by employing the designed robust adaptive DSC nonlinear control method. The underactuated problem is overcome by solving the designed adaptive neural control equations. Also, different from the continuous-time control scheme, the discrete-time control is more suitable for the computer and network control in practicable cases. Furthermore, the digital first-order low-pass filters are constructed to predict the future virtual control signal in the backstepping method, leading to the avoidance of the model transformation problem in the discrete-time backstepping method.

Adaptive Fixed-Time Control for the Postcapture Tethered Spacecraft With Full-State Constraints

This paper studies the fixed-time control problem for the post-capture tethered spacecraft subject to full-state constraints and uncertainties. A <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> smooth adaptive fixed-time controller is constructed via introducing a smooth switch between fractional and quadratic form feedback, such that the undesired chattering and singularity issues are removed. With the aid of universal transformed function (UTF) technique, the proposed controller not only ensures that the constraint boundaries are not violated, but also eliminates the feasibility condition existing in the traditional barrier Lyapunov functions (BLFs)-based control solutions. Furthermore, by incorporating the generalized first-order filter and adaptive laws into control design procedure, the fixed-time stability of the closed-loop system can be guaranteed. The validity of the proposed control scheme is demonstrated by a simulation example.

A CMOS-realizable, compact and integrable all-pass structure and its tunable variant

In this paper, two novel and compact structures of voltage-mode first-order all-pass filter are proposed. The first proposed structure is designed to provide non-inverting all-pass response only. It consists of only four MOS transistors and minimal number of passive elements i.e. one capacitor and one resistor. The proposed filter also offers the feature of high input impedance and is free from passive component matching constraints. Additionally, by including an inverting stage at the output, the first proposed design is extended to deliver both non-inverting and inverting all-pass responses simultaneously. Moreover, the proposed idea is further enriched with very essential feature of tunability by replacing the passive resistor with its active equivalent NMOS transistor. The theoretical analysis of the proposed design is verified with PSPICE simulation using TSMC 0.18 µm level-7 CMOS process parameters at supply voltage of ±0.9 V. Post layout verification is also explored to validate real time performance of proposed idea.

Finite-Time Adaptive Fuzzy Control for Unmodeled Dynamical Systems with Actuator Faults

This article concentrates upon the issue of finite-time tracking control for a category of nonlinear systems in pure-feedback form with actuator faults and unmodeled dynamics, where the loss of effectiveness and bias fault are considered. Meanwhile, the function approximation method utilizing fuzzy logic systems and dynamic surface control approach with first-order filter are implemented to model the unknown nonlinear terms induced from the proposed controller procedure and tackle the “explosion of complexity” issue of the classic backstepping method. The use of the maximal norm of the weight vector estimation method and adaptive approach reduces the computation load induced by fuzzy logic systems. Within the framework of backstepping control, a finite-time adaptive fuzzy fault-tolerant control protocol is derived to guarantee the boundedness of all signals and tracking error of the controlled system within a finite-time. Simulation studies are offered to show the validity of the derived theoretical results of the finite-time control protocol.

A Time-Mode PWM 1st Order Low-Pass Filter

In this work, a first-order low-pass filter is proposed as suitable for time-mode PWM signal processing. In time-mode PWM signal processing, the pulse width of a rectangular pulse is the processing variable. The filter is constructed using basic time-mode building blocks such as time registers and time adders and so it is characterized by low complexity which can lead to the modular and versatile design of higher-order filters. All the building blocks of the filter were designed and verified in a TSMC 65 nm technology process. The sampling frequency was 5 MHz, the gain of the filter at low frequencies was at −0.016 dB, the cut-off frequency was 1.2323 MHz, and the power consumption was around 59.1 μW.

UDE-Based Dynamic Surface Control for Quadrotor Drone Attitude Tracking under Non-Ideal Actuators

Quadrotor drone attitude tracking is inevitably affected by the combination of model uncertainties, external disturbances, and non-ideal actuator dynamics during stable flight and complex maneuvers. In order to achieve precise attitude control in these situations, a cascade-structured dynamic surface control (DSC) strategy is proposed based on an uncertainty and disturbance estimator (UDE), considering the actuator dynamics as represented by a first-order plus time-delay model. The DSC scheme is used to transform the original attitude dynamics system into a set of interconnected subsystems. On the one hand, the mismatched disturbances in the attitude kinematics and dynamics loops are converted into matched disturbances to accommodate the structural constraints of the UDE so that these disturbances, as well as the non-ideality caused by the actuator time delay, are estimated and compensated for by the approach. On the other hand, the “complexity explosion” problem is addressed by the first-order filter employed by DSC. The ultimate boundedness of the closed-loop system is proven while the parameter design constraints are provided. MATLAB Simulink simulations are conducted to demonstrate the desirability of considering actuator dynamics and to verify that the proposed control strategy can relax the constraints of the control parameters and enable a higher accuracy.

On the fast track: Rapid construction of stellar stream paths

ABSTRACT Stellar streams are sensitive probes of the Galactic potential. The likelihood of a stream model given stream data is often assessed using simulations. However, comparing to simulations is challenging when even the stream paths can be hard to quantify. Here we present a novel application of self-organizing maps and first-order Kalman filters to reconstruct a stream’s path, propagating measurement errors and data sparsity into the stream path uncertainty. The technique is Galactic-model independent, non-parametric, and works on phase-wrapped streams. With this technique, we can uniformly analyse and compare data with simulations, enabling both comparison of simulation techniques and ensemble analysis with stream tracks of many stellar streams. Our method is implemented in the public Python package TrackStream, available at https://github.com/nstarman/trackstream.

A Dual Aircraft Maneuver Formation Controller for MAV/UAV Based on the Hybrid Intelligent Agent

This paper proposes a hybrid intelligent agent controller (HIAC) for manned aerial vehicles (MAV)/unmanned aerial vehicles (UAV) formation under the leader–follower control strategy. Based on the high-fidelity three-degrees-of-freedom (DOF) dynamic model of UAV, this method decoupled multiple-input-multiple-output (MIMO) systems into multiple single-input-single-output (SISO) systems. Then, it innovatively combined the deep deterministic policy gradient (DDPG) and the double deep Q network (DDQN) to construct a hybrid reinforcement learning-agent model, which was used to generate onboard desired state commands. Finally, we adopted the dynamic inversion control law and the first-order lag filter to improve the actual flight-control process. Under the working conditions of a continuous S-shaped large overload maneuver for the MAV, the simulations verified that the UAV can achieve accurate tracking for the complex trajectory of the MAV. Compared with the traditional linear quadratic regulator (LQR) and DDPG, the HIAC has better control efficiency and precision.

Оптимизация параметров обработки сигналов в психофизиологических исследованиях на примере КГР и ФПГ

&lt;p&gt;When analyzing physiological signals, the problem of setting data processing parameters arises due to the blurring of the boundary between signal and noise properties, as well as the fundamental lack of objective criteria for the quality of data processing in psychophysiology. This paper describes an approach to optimizing processing parameters on the example of galvanic skin response (GSR) and photoplethysmogram (PPG), based on the use of stimuli that are significant for a person, selected on the basis of biographical data, which can be considered as criteria validation. As a metric for the optimization, we used the frequency of coincidence of the stimuli identified as a result of the analysis with the a priori given ones (human names, including the name of the volunteer, and also visit cards selected by the volunteer). GSR and PPG signals were recorded using an MRI-compatible polygraph under conditions of functional magnetic resonance imaging (N=46 volunteers). In the first part of the work, optimization of frequency filters and analysis intervals (epochs) was performed. It has been established that the following processing parameters are optimal for analyzing the amplitude properties of the GSR signal: first-order Butterworth filters, frequency range is 0.025-0.25 Hz, interval of analysisis1-7 s from a stimulus. To analyze the PPG signal using the length of the curve, the following processing parameters are optimal: second-order Butterworth filters, frequency range is 1.25&amp;mdash;12.5 Hz, interval of analysis is 3&amp;mdash;10 s from a stimulus. Using the same criterion, several alternative signal processing methods were tested: change in the amplitude of the GSR signal over the analysis interval compared to the classical method by the amplitude maximum relative to the baseline; several types of ranking of reactions within a block of stimuli compared to simple averaging of all responses. The parameters and methods of processing of the GSR and PPG signals obtained in the work demonstrate universality in relation to the variety of initial data and could be applicable in applied and fundamental research. The general approach described in the work can also be used to optimize the processing parameters of other physiological signals including fMRI.&lt;/p&gt;

Dynamic surface sliding mode control of chaos in the fourth-order power system

As a typical complex nonlinear model, the power system is influenced by the parameters and initial values, and chaotic oscillations can easily occur in the actual operation process, which seriously endangers the stability of its operation and may even lead to the collapse of the whole power system. To suppress chaotic oscillations in power systems, a method of dynamic surface sliding mode control is first proposed, which overcomes the “term explosion” problem in the traditional backstepping design process by introducing first-order low-pass filters, and reduces the design steps of dynamic surface controllers and the complexity of stability analysis by combining sliding mode control. And then, the steadiness of the closed-loop controlled system is evaluated according to Lyapunov asymptotic stability theory. Lastly, the simulation and experiment are implemented to show that the designed control method can effectively inhibit the power system's chaotic oscillations and stabilize it.

Electronically Tunable Voltage-Mode Multiphase Sinusoidal Oscillator with Low Output Impedance Nodes Employing VD-DIBAs

The multiphase sinusoidal oscillator (MSO) is useful for various electrical and electronic applications. This study aims to design an MSO employing voltage differencing differential input buffered amplifiers (VD-DIBAs). The design procedure is based on cascading the first-order low-pass filter. Each phase consists of a VD-DIBA, two resistors, and a grounded capacitor. An odd-phase system without requiring an additional amplifier. The frequency is electronically controlled through the bias current without affecting the condition. The sinewave amplitudes and the phase difference between each waveform are identical. The proposed MSO is designed to obtain three-phase waveforms (n = 3). PSPICE simulation demonstrates the performance of the proposed oscillator with 0.18 μm TSMC CMOS parameters with ±0.9 V power supply. The feasibility of the proposed MSO is also verified with experiments using the VD-DIBA constructed from commercial integrated circuits (ICs) with a ±5 V power supply. The simulated and experimental results align with theoretical predictions.

Active damping of LCL-Filtered Grid-Connected inverter based on parallel feedforward compensation strategy

Resonance related to the LCL-filter grid-connected inverter (GCI) is one of the most challenging issues in power electronics. Active damping is a widely used methodology to damp the resonance problem due to its effective control structure. In capacitor current feedback active damping methodologies, a compensator is primarily required in the feedback loop where the damping efficiency depends on the imitated features of the compensator. Such capacitor current feedback damping techniques encounter restrictions in their layout at the critical resonance frequency and may need extra amendment in the delay to assure stability. This paper proposes a different design method called parallel feedforward compensation method, which designs an almost strictly real positive plant and achieved damping with enhanced stability features. In the proposed alternative, a first-order high pass filter is used as a compensator across the LCL filter plant and filter capacitor current feedback loop. The resultant output of this augmented plant is then transmitted back at the reference point of a GCI system to attenuate the undesirable resonance peak. The key benefits of the proposed method are efficient damping without any limitation of critical resonance frequency region, better control characteristics, improved damping area, and better robustness under variations in filter parameters. The simulation and experimental outcomes based on transient response and steady-state analysis are demonstrated to validate the efficacy of the suggested method.

Single VDGA-Based Mixed-Mode Electronically Tunable First-Order Universal Filter.

This article presents a mixed-mode electronically tunable first-order universal filter configuration employing only one voltage differencing gain amplifier (VDGA), one capacitor, and one grounded resistor. With the appropriate selection of the input signals, the proposed circuit can realize all three first-order standard filter functions, namely low pass (LP), high pass (HP), and all pass (AP), in all four possible modes, including voltage mode (VM), trans-admittance mode (TAM), current mode (CM), and trans-impedance mode (TIM), from the same circuit structure. It also provides an electronic tuning of the pole frequency and the passband gain by varying transconductance values. Non-ideal and parasitic effect analyses of the proposed circuit were also carried out. PSPICE simulations and experimental findings have both confirmed the performance of the design. A number of simulations and experimental observations confirm the viability of the suggested configuration in practical applications.