Input Gain Research Articles

Investigating system performance in 16 channel WDM network at minimum attenuation window for pre-defined input noise level

Abstract Input and output optical signal-to-noise ratio in 16-channel WDM network are investigated for predefined input noise level when design is set at minimum attenuation window. By keeping the input OSNR constant, gain and noise figure are computed along with SNR at both transmitting and receiving terminals for two different data rates and also with short-to-long range of trans-receiver distance. Corresponding variations of all the network properties, i.e., maximum Q-factor, eye height and noise figure are measured for estimation of performance degradation. Optimization in terms of both bit rate and channel distance is required, as evident from simulation result, for best possible system performance. Setting up of input noise level at 20 dBm indicates the fact of real-time compatibility with optimum value of output OSNR is revealed at a particular distance, which suggests the best result for communication system design.

Prescribed‐time regulation of nonlinear uncertain systems with unknown input gain and appended dynamics

AbstractThe prescribed‐time stabilization problem for a general class of uncertain nonlinear systems with unknown input gain and appended dynamics (with unmeasured state) is addressed. Unlike the asymptotic stabilization problem, the prescribed‐time stabilization objective requires convergence of the state vector to the origin in a finite time interval that can be arbitrarily picked (i.e., “prescribed”) by the control system designer irrespective of the system's initial condition. The class of systems considered is allowed to have general nonlinear uncertain terms throughout the system dynamics as well as uncertain appended dynamics (that effectively generate a time‐varying non‐vanishing disturbance signal input into the nominal system). The control design is based on a nonlinear transformation of the time scale, dynamic high‐gain scaling, adaptation dynamics with temporal forcing terms, and a composite control law that includes two components. The first component in the composite control law is analogous to prior dynamic high‐gain scaling‐based control designs, but with a time‐dependent function in place of the unknown input gain, while the second component has a non‐smooth form with time‐dependent terms that ensure prescribed‐time convergence in spite of the unknown input gain and the disturbances. The efficacy of the proposed control design is illustrated through numerical simulation studies on two example systems (a “synthetic” fifth‐order system and a “real‐world” electromechanical system).

Synthesizing network dynamics for short-term memory of impulsive inputs.

Illuminating the mechanisms that the brain uses to manage and coordinate its resources is a core question in neuroscience. In particular, circuits and networks in the brain are able to encode, store and recall large amounts of information, in the service of a wide range of functionality. How do the various dynamical mechanisms within these networks allow for such coordination? We consider the specific problem of how the dynamics of networks can enact a representation of input stimuli that is retained over time, i.e., a form of short-term memory. We utilize modeling and control-theoretic methods to approach these questions, treating the state trajectory of a dynamical system as an abstract memory trace of prior inputs. The inputs impinge on the network via a variable gain, which is to be synthesized by optimization. In order to perpetuate these memory traces of stimuli, we propose that this gain is adapted to optimize: i) the error between a ground truth representation of stimuli and the encoding of them; as well as ii) overwriting of prior information. Optimizing over these central tenets of memory, we obtain a 'policy' for adapting the input gain that is dependent on the state of the network. This derived policy yields a recurrent neural network between the policy and the neural circuits, affirming existing theories that the prefrontal cortex may hold subnetworks dedicated to working memory while actively engaging with other neural subnetworks.

The MUSCAT Readout Electronics Backend: Design and Pre-deployment Performance

MUSCAT is a new large-format 1.1 mm continuum camera for local and extra-galactic astronomy currently being installed at the 50 m Large Millimetre Telescope Alfonso Serrano, LMT. The focal plane is populated with 1458 feedhorn coupled Aluminium LEKIDs, cooled to 130 mk, and read out with 6 frequency division multiplexed RF readout chains, each with a 500 MHz bandwidth. The nominal mux ratio is sim 250 resonators per chain with an average spacing of 2 MHz between resonators. In each RF chain, the multiplexed waveform generation/decomposition is performed with the BLAST-TNG firmware on a ROACH2 FPGA board with a MUSIC DAC/ADC. The quadrature modulated IF signals are mixed to and from the LEKID readout band on a custom card that houses IQ mixers, a programmable synthesizer, and additional programmable input and output gain control and filtering. Within the cryostat, the RF signals are attenuated prior to reaching the focal plane array and then amplified at 4K. A novel software system controls all the programmable hardware and handles instructions from the LMT instrument control system to record and store observation data, as well as performing automated resonator retuning and providing results of quick look analysis to the telescope operators. In this paper, we present the detailed design and in-lab performance of the cryogenic and room temperature electronics, and the software control system.

Design and Implementation of Ku-Band High Directionality Antenna

In this article, a Ku-band high directivity antenna is designed, which consists of a radiation waveguide section, a mode conversion section, and a coaxial waveguide conversion section. In this article, the theoretical calculation process of antenna components is summarized and supplemented. The calculation method between key technical indexes and structural parameters is established. The key technical parameters of the antenna, including input return loss, half-power beamwidth, gain, and cross-polarization level, are studied and explored. The radiation performance of the antenna can be further improved by optimizing the structural parameters. Finite-element analysis and COMSOL simulation software are used to study. In order to reduce antenna reflection, a method of equal-Q impedance transformation is proposed for rectangular and circular waveguide converters and coaxial waveguide converters. Finally, the proposed feed antenna is processed and verified, and the measured results are in good agreement with the simulation results.

A 23–31 GHz high‐gain GaN low‐noise amplifier using T‐type matching networks and multiple feedback techniques for broadband 5G millimeter‐wave applications

AbstractA 23–31 GHz three‐stage low‐noise amplifier (LNA) based on 100 nm gallium nitride‐on‐Si technology is presented with a total circuit size of 2.0 × 1.4 mm2. To achieve an excellent noise figure (NF) and gain, a special inductive dual‐source feedback network is used; it contributes to noise matching and input conjugate matching by resonating with the parasitic gate‐source capacitance of the transistor. T‐type networks with low‐quality factor are carefully employed for broadband matching circuits to extend the bandwidth. Meanwhile, a lossy RLC feedback network of the output stage can further obtain a wider frequency band and improve the stability through Miller approximation analysis of the input quality factor and gain of the closed‐loop system. The proposed LNA achieves a NF of 1.9–2.5 dB, a small signal gain of 24–27 dB, and an output 1 dB compression point (P1dB) of 16 dBm across the band.

Composite adaptive neural tracking control of uncertain strict‐feedback systems

AbstractComposite adaptive neural control of uncertain strict‐feedback systems is synthesized. It mainly consists of an adaptive neural backstepping controller, an immersion and invariance (I&I) update algorithm, and a set of state filters for conquering the in‐feasibility of the states' derivatives required in the update algorithm. For compensating the indefinite coupling terms in the update algorithm, a novel nonlinear ‐modification method is promoted. To further tackle the case with unknown input gain functions, the dynamic surface control (DSC) and the adding‐an‐integrator technique are incorporated for preventing the so‐called explosion of complexity and the algebraic‐loop problems in the virtual controller and the composite update algorithm, respectively. The proposed design ensures the semi‐globally uniformly ultimately bounded (SGUUB) stability of the closed‐loop system and, in particular, the convergence of prediction errors to the vicinity of zero without persistent excitation (PE), which in turn improves the tracking performance.

입력이득의 부호가 미지인 일반적인 비선형시스템의 규정된 성능을 가지는 출력궤환 제어기 설계

The systematic procedure for the design of the output-feedback controller of uncertain general nonautonomous nonlinear systems without a priori knowledge of the sign of the input gain is proposed. The proposed controller adopts higher-order switching differentiator to estimate time-derivatives of the output tracking error. It is mathematically proved that the output tracking error and its time-derivatives are all maintained in the prescribed regions. To illustrate the performance of the proposed controller, numerical simulation was performed. To author’s knowledge, there are no results on the problem tackled in this paper.

Disturbance rejection and robust tracking control design for turbofan systems

The intention of this work is to analyse the issues of multiple disturbance estimation and rejection as well as robust tracking control design for turbofan systems subject to input gain perturbations. A standard generalized extended state observer is developed to estimate both the state disturbances and output measurement disturbances, simultaneously. Therewith, a modified repetitive controller is utilized with generalized extended state observer to track the states of the turbofan system accurately. Then, a new composite control strategy is developed by incorporating the estimates obtained via generalized extended state observer in modified repetitive controller to attenuate the effect of disturbances. Based on the pole placement technique, the observer gain is calculated and in accordance with Lyapunov stability theory, a set of sufficient conditions which ensures the robust asymptotic stability of the considered turbofan system is derived in the form of linear matrix inequalities. Moreover by offering the numerical examples with simulation results, the superiority of developed control strategy is validated.

Enhanced extended state observer-based model-free force control for a Series Elastic Actuator

With inherent mechanical compliance and programmable force controllability, the Series Elastic Actuator (SEA) has been a popular choice for modern mechanical systems. It is crucial to realize accurate and robust force control for a SEA, especially in a physical human–robot interaction condition. In this paper, a model-free force controller (MFFC) for the SEA is developed, which relies only on the input–output measurement. Firstly, based on the ultra-local model concept, the SEA force dynamics is reformulated in a simpler way, and all unknown terms are grouped as one term called lumped total disturbance. Secondly, an enhanced extended stated observer (EESO) is designed to simultaneously estimate the lumped total disturbance, the force velocity, and the control input gain. Thirdly, a disturbance rejective intelligent PD (iPD) control scheme is established. In addition, the effects of the control input gain are analyzed and the close-loop stability is demonstrated with Lyapunov method. The control accuracy and robustness of the MFFC are verified in a physical human–robot interaction environment.

Power Factor Correction Application Based on Independent Double-Boost Interleaved Converter (IDBIC)

In this paper, a Power Factor Correction (PFC) application, based on the novel power stage topology named Independent Double-Boost Interleaved Converter (IDBIC), has been analyzed. The novelty of the proposed PFC rectifier is based on the sum of capabilities, such as supplying three independent output voltage levels with interleaved operation at the input and high voltage gain. The hardware used within this application consists of an AC input L-C-L filter, a single-phase bridge rectifier, the IDBIC power stage, output capacitors group and a group of variable high-power rheostats (resistors) group as DC load. The main purpose of the carried study was to highlight the advantages and disadvantages of the novel power stage topology in the context of a green and modern AC to DC conversion solution. Nowadays, a high level of the efficiency and power factor have become a mandatory feature for the AC to DC conversion solutions to satisfy the international electrical standards. Thus, considering the modern electrical standards and recommendations, the current study tries to better depict the working steps and principles of the modern power stage topology within an AC to DC conversion application. The behavior of the considered power stage described in different detailed working steps (such as the Discontinuous Conduction Mode and Continuous Conduction Mode) may help understand how the energy conversions process of AC to DC becomes more efficient. The high output voltage gain of the considered power stage is the key feature in the Power Factor Correction process. With such a feature, the AC to DC conversion solution/application can also operate at lower input AC voltages (such as 90 [V] and 110 [V]). The proposed solution can be successfully used in the electric vehicle (automotive field) and high-power electrical traction (e.g., trains, high power electrical machines and drives). The same solution can also be used successfully in fast battery charging applications and chemical electrolysis processes.

Adaptive Optimal Control for Unknown Constrained Nonlinear Systems With a Novel Quasi-Model Network.

A policy-iteration-based algorithm is presented in this article for optimal control of unknown continuous-time nonlinear systems subject to bounded inputs by utilizing the adaptive dynamic programming (ADP). Three neural networks (NNs), called critic network, actor network, and quasi-model network, are utilized in the proposed algorithm to give approximations of the control law, the cost function, and the function constituted by partial derivatives of value functions with respect to states and unknown input gain dynamics, respectively. At each iteration, based on the least sum of squares method, the parameters of critic and quasi-model networks will be tuned simultaneously, which eliminates the necessity of separately learning the system model in advance. Then, the control law is improved by satisfying the necessary optimality condition. Then, the proposed algorithm's optimality and convergence properties are exhibited. Finally, the simulation results demonstrate the availability of the proposed algorithm.

VHF BALANCED AMPLIFIER WITH LOSSLESS FEEDBACKS

Today’s practice of developing VHF radio systems paths widely uses MMIC as low-noise amplifiers. This approach is acceptable for radio systems operating in a relatively quiet electromagnetic environment. However, for systems operating in a complex interference environment of the VHF band, low-noise amplifiers with a lower gain and increased overload capacity are desirable. This requires maintaining a low noise figure and manufacturability of the device. Therefore, the solution to this problem requires the development of a low-noise amplifier of the VHF band with increased overload capacity, made on commercially available MMIC. This paper presents the results of a logical-heuristic synthesis of a VHF low-noise high-linear amplifier performed on an MMIC, utilising noiseless negative feedback technique. Analytical expressions are given for calculating the gain, the input gain compression point, input intercept points of the J-th order, and the noise figure of the structure. The analysis of the performance of the amplifier implemented on the MGA 62563 MMIC showed that, in comparison with other integrated solutions, increased overload capacity and structure linearity are provided. The high noise immunity and ease of manufacture of the device using commercially available components, make it a promising element in the design and modernization of VHF receiving and amplifying paths operating in a complex electromagnetic environment.

New convergence conditions for the super twisting algorithm with uncertain input gain

A simple proof is proposed that extends Seeber and Horn’s recent sufficient conditions (Seeber and Horn, 2017) for the finite time convergence of the super twisting algorithm to perturbations in the input gain. The new convergence conditions are compared to state of the art conditions, and turn out to accept sensibly smaller gains.

Observer‐based distributed fault‐tolerant containment control for stochastic nonlinear multi‐agent systems with asymmetric hysteretic quantization

AbstractThis article investigates the distributed containment control problem for high‐order stochastic nonstrict‐feedback nonlinear multi‐agent systems. To overcome the difficulty of unknown control input gain caused by the asymmetric hysteretic quantization and actuator fault, the properties of Nussbaum function are employed and an auxiliary virtual controller is designed, which does not need to estimate the bounds of the parameters of asymmetric hysteretic quantizer and efficiency factors. Moreover, the unknown terms are estimated by introducing the radial basis function neural networks. Based on the input‐driven filter, an adaptive containment control scheme is designed by using the Nussbaum function technique, the backstepping approach, and the dynamic surface control method. It is shown that the proposed control method can guarantee that all the signals are semi‐globally uniformly ultimately bounded, and the containment control performance can be achieved. Finally, some simulation results are presented to illustrate the effectiveness of the proposed approach.

Error driven Fuzzy Logic Controller (FLC) for Spherical Mobile Robot: Simulation & Experimental Performance Analysis

Spherical mobile robot is a ball-shaped mobile robot that capable to move from one place to another to perform the desired tasks. The challenge for spherical mobile robot falls within control algorithm aspects, where it is nonlinear and highly under-actuated increases the difficulties to control its motion. In this paper, the potentiality of intelligent controller is explored to control the motion spherical mobile robot. An error driven Fuzzy Logic controller (FLC) which consist of modular of two Proportional-Derivative (PD) type FLC and a Proportional-Integral (PI) type FLC were designed and tested to control the position of the spherical mobile robot, angle of the rotation of the pendulum and the angular velocity of the spherical mobile robot, respectively. The performance of the controller was then optimized by tuning the input and output gain of the controller with Particle Swarm optimization (PSO) method. The performance of the robot without the controller and with optimized controller were compared and analysed. As a result, the performance of the system in the form of rise time and settling time of the robot to control its position managed to be reduced by 86% and 89% respectively with optimized PD-type. For PD-type FLC to control the rotation of the pendulum, it was capable to eliminate the overshoot and reduce it settling time by 35.5%. While the optimized PI-type FLC has managed to eliminate the steady state error and achieved it desired velocity setpoint in 1.2s. Lastly, all the designed controllers were successfully tested on the prototype of the spherical mobile robot to study the performance of the spherical mobile robot. However, the overall performance of the implemented designed controller has shown a minimum effectiveness. The controller managed to achieve the setpoint value but with low stability which result from the less accuracy of the hardware sensors.

Design of a Source Degenerated Cascode Stage Low Noise Amplifier for 5G Applications

Low Noise Amplifier (LNA) is the most critical part of a receiver front end in terms of the receiver performance. The performance tradeoff among input matching, noise figure, gain, and linearity are analyzed in detail. The LNA finds its application at Portable GPS Receiver, BLE, Zigbee, NFC, WiFi, Wireless Sensor Network, RFIC operating at 2.4GHz frequency. Millimeter wave communication is an evolving technology for bandwidth demanding 5G wireless application. A high gain and linear narrowband cascode Low Noise Amplifier (LNA) operating at 2.18GHz to 2.47GHz is proposed. To demonstrate design methodology, a narrow-band source degenerated cascode LNA is designed and simulated in a standard 90nm CMOS process to operate in the 2.4 GHZ band. The LNA achieves a voltage gain of 5.38dB, Noise figure of 4.1127dB, and from 3.2 V supply voltage. Proper input and output impedance matching have been performed to achieve the input return loss of -14 dB (S11) and output return loss of -19.72 dB (S22). Simulation study has been done using Cadence spectre.

Challenges to “going local”: Lessons from direct food sourcing initiatives in Cusco, Peru

Restaurants can improve the quality and reliability of their input supplies and gain favor with consumers through direct sourcing while also contributing to development goals around sustainable production and income generation. However, limited evidence exists on the willingness of restaurants to invest in direct sourcing, the implications of these linkages, and the options to achieve scale. We interviewed 46 restaurants to examine their preferences and experiences in sourcing local foods and analyzed three cases that link local production to the tourist sector in Cusco, Peru. Results suggest that the interventions succeeded in providing a few restaurants with high value food. However, the interventions failed to deliver impact at scale. Bottlenecks included low business capacities in farmer organizations, limited support from NGOs and the government, and weak incentives for restaurants. We conclude with a discussion on the changes needed in the business and policy environment for achieving greater impact at scale.

Improving the Charge Preamplifier of ITER Neutron Flux Monitor System

The fission chamber plays a key role in International Thermonuclear Experimental Reactor (ITER) neutron flux measurement. However, the matched preamplifier cannot tolerate the strong radiation of ITER. This can be solved by using a cable to transmit the signal from the detector to the preamplifier. The object of this project is to develop charge preamplifiers that admit a long cable as input. The input stage and gain stage of the charge preamplifier in previous work have been improved to reduce the rise time and noise degradation caused by the capacitance of the long cable. The experimental results confirm that the preamplifier can admit the fission chamber detector and a 20-m cable.

Adaptive Door Opening Control Algorithm of Bio-Inspired Mobile Manipulator Based on Synchronous Sensing.

At present, the research of robot door opening method is basically realized by identifying the door handle through the synchronous sensing system on the premise that the bio-inspired mobile manipulator is located in front of the door. An adaptive door opening strategy of a bio-inspired mobile manipulator based on a synchronous sensing system is proposed. Firstly, the random delay distribution in clock synchronization technology is analyzed in detail, and its distribution is verified on the experimental platform of adjacent nodes. Based on the Gaussian distribution of random delay, the relative frequency offset and relative phase offset of adjacent nodes are calculated. The clock synchronization of network cable sensor nodes is realized. Secondly, based on the information data of synchronous sensing system, this article realizes target detection and tracking based on depth network. In addition, based on the sliding mode control theory, the dynamic model of the nonholonomic bio-inspired mobile manipulator is applied. Finally, a robust adaptive sliding mode control method for nonlinear systems with input gain uncertainty and unmatched uncertainty is proposed by combining adaptive backstepping with sliding mode control. By adding sliding mode control in the last step of adaptive backstepping, the uncertainty of the system is compensated, and the system trajectory is maintained on the specified sliding mode manifold. The tracking control and stability control of the nonholonomic bio-inspired mobile manipulator are simulated. The experimental and simulation results show that the control method proposed in this article is effective and feasible.