Branch Currents Research Articles

Active Power Decoupling Control for PWM Converter Considering Sensor Failures

The power converters integrated with active power decoupling (APD) may handle the ripple power in dc link and then reduce the volume of the filter capacitor dramatically. Generally, voltage and current signals of the LC branch are required for the closed-loop APD control. However, sensor failures could degrade the control performance and even lead to the breakdown of the converter system. This article proposes a detection method for sensor failures in the APD circuit of the single-phase converter. The voltage and current of the LC branch in the APD circuit are estimated by a dual sliding mode observer (SMO). The residuals of the estimated and measured signals are calculated, and they have high sensitivity to specific sensor faults, namely, the current residual is sensitive to the fault of the current sensor and the voltage residual is sensitive to the fault of the voltage sensor, which could be employed to locate the faulty sensors. Finally, the effectiveness of the proposed method is verified by the simulation and experimental results.

Toward Ultrasonic Wire Bonding for High Power Device: A Vector Based Resonant Frequency Tracking and Constant Amplitude Control

The electrical packaging for high power devices such as IGBT or MOSFET is achieved by heavy aluminum ultrasonic wire bonding. In this process, the amplitude stability of ultrasonic transducer determines the bonding quality, which demands more accuracy in resonant frequency tracking (RFT) and constant amplitude control (CAC). In this investigation, we proposed a vector based resonant frequency (VRFT) tracking and vector based constant amplitude control (VCAC) to control the ultrasonic transducer. The current of dynamic branch was conducted by calculating the voltage and current vector of ultrasonic transducer. Small signal model of ultrasonic transducer was established and applied into RFT and CAC. A control strategy of fuzzy self-tuning PID closed loop was utilized to RFT and CAC. The PID parameters was calculated by the linear control theories and modified by the fuzzy controller which improved the vibration stability of the transducer. A prototype of 100Watt/60kHz ultrasonic driver was self-developed to verify the VRFT and VCAC. It demonstrated that the locked frequency of VRFT can be controlled within less than 0.04 millisecond when staring from the swept frequency, and the vibration response is fast with the varying bonding pressure. The amplitude of fuzzy PID VCAC is more stable and robust compared to the classical PID control, which improved the bonded joint quality in heavy aluminum wire packaging. Note to Practitioners—This article was motivated by the reliability and efficiency of IGBT/ MOSFET device packaging through ultrasonic aluminum wire bonding. This bonding process requires more amplitude stability of the ultrasonic transducer to achieve acceptable bonded quality. Currently, the resonant frequency tracking (RFT) by classical PID control is in slow speed, and the amplitude of the transducer cannot be controlled constantly due to the inherent static capacitor of the transducer. These issues for the ultrasonic control are originated from the engineer’s experience or simple heuristic rule instead of advanced approaches. To improve the vibration performance, we proposed a vector based model consisting of the relationship the dynamic branch current and the total current of the transducer, to control the RFT and constant amplitude control (CAC). Moreover, the vector based is utilized into the fuzzy PID control, where the calculation is reduced by area coefficient defuzzy. The verification experiments prove that the response time of the proposed vector based RFT and CAC, and the bonded joint quality is optimized obviously. It is noted that in our control strategy, the RMS value, the phase of voltage and current of the transducer are acquired by DSP processor, and the calculation of fuzzy PID controller is not complicated, which is feasible to implement in application. This significantly benefits the demand of accurate control to the ultrasonic power in electronic packaging.

A Σ-Δ Modulator Based on an Inverter-based Integrator with Dynamic Current Switch

This paper presents a low-power high-resolution 3rd-order 1-bit Σ-Δ modulator based on an inverter-based integrator with a dynamic current switch. To reduce the power consumption of the modulator circuit, a dynamic current switch branch is added to form a low-power inverter-based integrator. A 3rd-order 1-bit Σ-Δ modulator is designed in a TSMC 65 nm CMOS technology to verify the effectiveness of the proposed integrator circuit. The prototype Σ-Δ modulator achieves 102.4 dB SNDR, 16.71 Bit ENOB in a 2 KHz signal BW at an Over Sampling Ratio (OSR) of 160, while consuming only 29.5-μW. And the FOMSNDR is 180.7 dB.

Rotor Faults Diagnosis in PMSMs Based on Branch Current Analysis and Machine Learning

To solve the problem that it is difficult to accurately identify the rotor eccentric fault, demagnetization fault and hybrid fault of a permanent magnet synchronous motor (PMSM) with a slot pole ratio of 3/2 and several times of it, this paper proposes a method to identify the rotor fault based on the combination of branch current analysis and a machine learning algorithm. First, the analysis of the electrical signal of the PMSM after various types of rotor faults shows that there are differences in the time domain of the electrical signal of the PMSM after three types of rotor faults. Considering the symmetry of the structure of the PMSM with a slot-pole ratio of 3/2 and its integer multiples, the changes in the time domain of the phase currents cancel each other after the fault, and the time domain fluctuations of the stator branch currents that do not cancel each other are chosen as the characteristics of the fault classification in this paper. Secondly, after signal preprocessing, feature factors are extracted and several fault feature factors with large differences are selected to construct feature vectors. Finally, a genetic algorithm is used to optimize the parameters of a support vector machine (SVM), and the GA-SVM model is constructed as a classifier for multifault classification of permanent magnet synchronous motors to classify these three types of faults. The fault classification results show that the proposed method using branch current signals combined with GA-SVM can effectively diagnose faulty PMSM.

Vanishing short multiplets in rank one 4d/5d SCFTs

We study the short multiplet spectrum in 4d mathcal{N} = 2 superconformal theories of low rank using the full superconformal indices and the selection rules from the superconformal representation theory. We find a universal expression for the leading terms for the superconformal index of rank one H0, H1, H2, D4, E6, E7 theories. From this result, we argue that certain short multiplets appear in the operator product expansions involving stress-tensor, conserved current, and Coulomb branch operator vanish. We also apply the same procedure to 5d superconformal theories and find that E1 theory has vanishing short multiplets analogous to that of the H1 theory.

A new low voltage low power fully differential CMOS class AB current output stage with unique current drive capability

ABSTRACT This paper presents a novel low-voltage low power fully differential class AB current output stage with high linearity and unique current drive capability. The proposed circuit is based on a simple and efficient structure to obtain high linearity by minimising the channel length modulation effect and also avoids cascade structure to act best in low-voltage applications. Giving the complete analyses and equations of the circuit, its properties are verified by Cadence using TSMC 0.18 µm CMOS parameters. In order to study its performance at the presence of non-idealities, Pre-layout and Post-layout both plus Monte–Carlo simulations are also performed. Under±0.9 V supply and 35 µA output bias current, it can deliver the ever high output current of ±350 mA with THD of −49 dB and output impedance of 2.8 MΩ, which leads to a unique high current drive ratio (Ioutmax/Ibias) of 10,000 and low consumed power of 150 µw in pre-layout simulation. In post-layout plus Monte–Carlo simulation, the results will be as ±320 mA output current, −42 dB THD, 2.2 MΩ output impedance, 40 µA DC current of the output branch, 8000 current drive ratio and 160 µw consumed power. These remarkable results prove the proposed novel COS not only as the unique one in the world but Longley ahead of the yet second rank COS by some unbeatable ratios as 11300×,14×,4× and3× in F T , I outmax , (Ioutmax/power), and current drive, respectively, that promise to keep it as the lead one for many years in low-voltage/power ultra-high current applications.

Where to look: Multi-granularity occlusion aware for video person re-identification

Video person re-identification(re-ID) plays an important role in intelligent video surveillance, which can automatically match the same person across video clips under non-overlapping cameras. Despite great progress in re-ID, the performance of most existing methods still is corrupted severely under partial occlusion. Although some multi-granularity methods have alleviated this dilemma, these methods still suffer from weak diversity of features and conflict between rigid horizontal partition and vertical occlusion. In this paper, we propose a novel video person re-ID framework, called Multi-Granularity Occlusion Aware (MGOA), which extracts multi-granularity features by precisely erasing the occlusion. Different from previous works based on multiple granularities, the proposed MGOA predicts the partial occlusion in a coarse-to-fine manner instead of erasing the occlusion in video clips by one step. Specifically, we first propose the multi-granularity feature extraction to obtain diverse features at different levels of feature maps, which is beneficial for the fine erasure of the occlusion. Moreover, to avoid the limitation of horizontal stripes that cannot handle vertical occlusion, we design Attention-Aware Occlusion Erasure (AA-OE) that can obtain the attention maps with coarse occlusion erasure in the coarse-grained branch and the attention maps with fine occlusion erasure in the fine-grained branch. It is worth noting that each granularity in our network is not independent but relevant through the top-down information transmission between granularities, which transfers the erased occlusion feature maps of the current branch to the next finer-grained branch for guiding AA-OE to obtain more discriminative features. Extensive experiments on three challenging public benchmarks show that our MGOA can deal well with occlusion and achieves state-of-the-art performance.

A study of a modified design of dumbbell-shaped flux switching tubular linear generator for regular wave energy conversion

Wave energy converters (WEC) use indirect drive hydraulic or turbine-type power take-off (PTO) mechanisms which consist of many moving parts, creating mechanical complexity and increasing the installation and maintenance costs. Linear generator-based direct drive wave energy converters could be a solution to overcome this problem, but the efficiency of the single conventional linear generator is not high enough, and it cannot work satisfactorily in the low-frequency range.In this paper, a novel dumbbell-shaped flux-switching linear generator has been proposed and studied as a power take-off unit for ocean wave energy conversion. The linear generator has a dumbbell-shaped stator, and the design is ameliorated by placing the permanent magnet rings of longitudinally alternating magnetic pole directions in the slots of its stator outer surface and is separated by thin wall steel ring shoulders. The linear generator also has a dumbbell-shaped translator. The stator is hollow where the translator slides inside axially inducing current in the coil. A long permanent magnet is inserted inside the hollow steel dumbbell core of the translator and a copper coil is wound around the outer surface of the moving translator core. The addition of permanent magnets on the outer slots of the stator is found to increase the output power significantly. To facilitate the investigation, the modified generator design has been compared to the conventional linear permanent magnet generator for their performances using the finite element method, as both machines are different in their structures. The results show that the double dumbbell-shaped flux-switching linear generator gives higher power output, magnetic flux density, branch current, and induced voltage. The double dumbbell-shaped flux-switching linear generator is then placed in a cylindrical buoy and investigated in a wave energy converter in the ocean environment. The hydrodynamic response of the cylindrical buoy has been investigated through ANSYS AQWA. The dynamic differential equations of the wave energy converter have been developed and solved for regular waves using Matlab codes. The peak output voltage, power, and the relative displacement of the linear generator translator with respect to the stator fixed with the buoy have been calculated through the Fourier Transform in the frequency domain using a Matlab code and through numerical integrations in the time domain using a Matlab Simulink code. The results in the time and frequency domains are compared and verified with each other. The relative displacement between the translator and stator buoy has been used as motion input of the ANSYS Maxwell simulation model, and the output voltage results of the ANSYS Maxwell simulation model have been compared and verified with those of the Matlab simulation models. The linear generator design in the wave energy converter under the regular wave excitation is further optimized for the maximum ratio of the peak output power to peak cogging force using the central composite design-based response surface method (RSM). The ANOVA analysis is used to validate the response surface model where its R2 coefficient of 99.93% has indicated an excellent fit. The methods and results differ from those presented in previous studies.

Convergence of the Malvinas Current branches near 44°S

Field measurements of the Malvinas Current (MC) velocity distribution were performed at the western slope of the Argentine Basin in the South Atlantic Ocean between 47° and 43°S including several sections across the current. The data were collected in January and March 2020 using a Shipborne Acoustic Current Doppler Profiler (SADCP) and allowed us to study circulation patterns in the upper 700 m of the ocean. The observations reveal substantial differences in the current structures at each location; the SADCP data suggest that two distinct current branches at 46°S converge downstream near 44°S making it difficult to distinguish the high-velocity cores farther north. A detailed comparison between the velocity structures indicates that the branches converge due to the change in the orientation and width of the continental slope, and is consistent with potential vorticity conservation. At the same time, satellite altimetry shows that the branches merge to a single high-velocity jet, suggesting that satellite altimetry does not reproduce all features of the MC internal structure and indicates the importance of further direct velocity observations in this region. Despite the above-mentioned limitations of altimetry, the satellite-derived geostrophic velocities suggest that the pathways of the MC high-velocity jets are quite stable. In addition, both satellite altimetry and direct measurements indicate that the branches tend to converge downstream near 44°S.

Revisiting the tropical Atlantic western boundary circulation from a 25-year time series of satellite altimetry data

Abstract. Geostrophic currents derived from altimetry are used to investigate the surface circulation in the western tropical Atlantic over the 1993–2017 period. Using six horizontal sections defined to capture the current branches of the study area, we investigate their respective variations at both seasonal and interannual timescales, as well as the spatial distribution of these variations, in order to highlight the characteristics of the currents on their route. Our results show that the central branch of the South Equatorial Current and its northern branch near the Brazilian coast, the North Brazil Current component located south of the Equator, and the Guyana Current have similar annual cycles, with maxima (minima) during late boreal winter (boreal fall) when the Intertropical Convergence Zone is at its southernmost (northernmost) location. In contrast, the seasonal cycles of the North Brazil Current branch located between the Equator and 7–8∘ N, its retroflected branch, the northern branch of the South Equatorial Current to the west of 35∘ W, and the North Equatorial Countercurrent show maxima (minima) during late boreal summer (boreal spring), following the remote wind stress curl strength variation. West of 32∘ W, an eastward current (the Equatorial Surface Current, ESC) is observed between 2–2∘ N, identified as the equatorial extension of the retroflected branch of the North Brazil Current. It is part of a large cyclonic circulation observed between 0–6∘ N and 35–45∘ W during boreal spring. We also observed a secondary North Brazil Current retroflection flow during the second half of the year, which leads to the two-core structure of the North Equatorial Countercurrent and might be related to the wind stress curl seasonal changes. To the east, the North Equatorial Countercurrent weakens and its two-core structure is underdeveloped due to the weakening of the wind stress. At interannual scales, depending on the side of the Equator examined, the North Brazil Current exhibits two opposite scenarios related to the phases of the tropical Atlantic Meridional Mode. At 32∘ W, the interannual variability of the North Equatorial Countercurrent and of the northern branch of the South Equatorial Current (in terms of both strength and/or latitudinal shift) are associated with the Atlantic Meridional Mode, whereas the variability of the Equatorial Surface Current intensity is associated with both the Atlantic Meridional Mode and Atlantic Zonal Mode phases.

A failure detection method based on multivariate variational mode decomposition and skewness for modular DC circuit breakers

Modular DC circuit breakers (MDCCBs) are widely used to protect multi-terminal HVDC (MT-HVDC) girds. However, the metal-oxide varistor (MOV) failure detection of MDCCBs still poses a challenge for the reliability of MT-HVDC grids. To this end, this paper analyzes the faulty features of the MDCCB and proposes a failure detection method that uses a multivariate variational mode decomposition (MVMD) and a differential skewness. The proposed method is as follows. First, MVMD decomposes the differential current, which is obtained by the current of the MDCCB energy absorption branch, into its time–frequency components, and then the time–frequency component that has the highest frequency is selected as the feature component. Second, a differential skewness is constructed by the feature component, and the differential skewness is employed to detect the MOV failure of the MDCCB. Finally, the performance of the proposed method is evaluated by a four-terminal symmetric bipolar HVDC system with MDCCBs. The simulation experiment results show that the proposed method can correctly detect the MOV failures of the MDCCB in different faulty conditions, even in the weak failure condition with noise influence.

Fault Detection and Ride Through of CHB Converter-Based Star-Connected STATCOM Through Exploring the Inherent Information of Multiloop Controllers

A simple detection and ride-through operation approach is proposed for star-connected cascaded H-bridge (CHB) converter-based STATCOMs with a single IGBT open circuit fault. It adopts a modified current regulator with high gains at both dc and fundamental frequencies. Then, the output signals of the current regulator branches and the dc voltage balancing regulator are synthesized as an inherent indicator to quickly determine the position of the open-circuit fault IGBT. With this approach, the controller can also be considered as an inherent system state monitor, but without any additional sensors or computing burdens. Afterwards, in the ride-through operation stage, the faulty H-bridge module can switch to half-bridge operation and the corresponding dc offset voltage is compensated by the remaining healthy modules. It has been validated that the proposed approach is accurate in various conditions, including grid voltage and load disturbances.

Backup protection method based on multi-interval information in low voltage distribution network of high proportion of renewable energy system

With the large number of renewable energy power sources such as wind power and photovoltaic power connected to the grid, the power system is becoming more electronic. The fault characteristics of renewable energy power sources and synchronous generators are obviously different, mainly manifested as the characteristics of short circuit current amplitude limitation and frequency offset, etc. The traditional protection based on the fault characteristics of synchronous generators may have adaptability problems. For a high proportion of renewable energy system, the short circuit current in the low voltage distribution network is greatly affected by the operation state of the renewable energy power sources after the short circuit fault occurs, which leads to the difficulty of the traditional three-stage overcurrent protection setting and coordination. In order to ensure the safe and stable operation of the system, this paper proposes a new backup protection method for low voltage distribution network. This method uses the information of the electric parameters on the high voltage side and low voltage side of the transformer. Firstly, the modulus sum of the voltage sampling value, the equivalent distance between the fault point and the protection installation place, and the modulus sum of the current sampling value are calculated. Secondly, the direction is judged by the criterion of the voltage direction element and the criterion of the distance protection element based on the multi-interval information. Finally, the maximum current branch of the low voltage distribution network is selected as the fault branch by the overcurrent element based on multi-interval information, so as to trigger the circuit breaker trip and isolate the fault. The low voltage distribution network model of the high proportion of renewable energy system is built on the PSCAD/EMTDC electromagnetic simulation platform. The simulation results show that the proposed protection method can reliably achieve fault removal by using multi-interval information, and has strong adaptability to the high proportion of renewable energy system.

Simplified topological algorithm for forming a steady mode of electric power system

The paper presents the possibility of simplifying the algorithms for forming the parameters of the steady state mode of a complex electrical network, using the independence of the currents of its equivalent circuit. In this case, all independent currents of a complex circuit of an electrical network must be found in advance, which is, in the general case, a rather difficult task, since it requires additional calculations of the steady state. The matrix of current distribution coefficients, formalized on the basis of the topology of the electrical network, can be used to directly determine the currents in the branches of its equivalent circuit. This allows you to preliminarily estimate the values of pre-selected independent currents in the circuit branches of a complex electrical network and determine its simplified design scheme. In this case, a calculation model is established, consisting of some trees of a complex electrical network graph.

Electric Vehicle Charging Capacity of Distribution Network Considering Conventional Load Composition

At present, the large-scale access to electric vehicles (EVs) is exerting considerable pressure on the distribution network. Hence, it is particularly important to analyze the capacity of the distribution network to accommodate EVs. To this end, we propose a method for analyzing the EV capacity of the distribution network by considering the composition of the conventional load. First, the analysis and pretreatment methods for the distribution network architecture and conventional load are proposed. Second, the charging behavior of an EV is simulated by combining the Monte Carlo method and the trip chain theory. After obtaining the temporal and spatial distribution of the EV charging load, the method of distribution according to the proportion of the same type of conventional load among the nodes is adopted to integrate the EV charging load with the conventional load of the distribution network. By adjusting the EV ownership, the EV capacity in the distribution network is analyzed and solved on the basis of the following indices: node voltage, branch current, and transformer capacity. Finally, by considering the 10-kV distribution network in some areas of an actual city as an example, we show that the proposed analysis method can obtain a more reasonable number of EVs to be accommodated in the distribution network.

Two-stage Optimization for Active Distribution Systems Based on Operating Ranges of Soft Open Points and Energy Storage System

Due to the lack of flexible interconnection devices, power imbalances between networks cannot be relieved effectively. Meanwhile, increasing the penetration of distributed generators exacerbates the temporal power imbalances caused by large peak-valley load differences. To improve the operational economy lowered by spatiotemporal power imbalances, this paper proposes a two-stage optimization strategy for active distribution networks (ADNs) interconnected by soft open points (SOPs). The SOPs and energy storage system (ESS) are adopted to transfer power spatially and temporally, respectively. In the day-ahead scheduling stage, massive stochastic scenarios against the uncertainty of wind turbine output are generated first. To improve computational efficiency in massive stochastic scenarios, an equivalent model between networks considering sensitivities of node power to node voltage and branch current is established. The introduction of sensitivities prevents violations of voltage and current. Then, the operating ranges (ORs) of the active power of SOPs and the state of charge (SOC) of ESS are obtained from models between networks and within the networks, respectively. In the intraday corrective control stage, based on day-ahead ORs, a receding-horizon model that minimizes the purchase cost of electricity and voltage deviations is established hour by hour. Case studies on two modified ADNs show that the proposed strategy achieves spatiotemporal power balance with lower cost compared with traditional strategies.

Устройства экспрессдиагностирования силовых полупроводниковых приборов и полупроводниковых преобразователей

The increase in the power of power semiconductor converters operated in the railway industry is associated with the use of group connections of power semiconductor devices in them, the variation in the parameters of which, and, therefore, their unequal load, causes a decrease in the reliability of the power semiconductor converters as a whole. In this regard, it becomes necessary to develop and implement innovative methods and devices for express diagnostics in order to identify potentially unreliable semiconductor devices, and the implementation of technical diagnostics should not be associated with dismantling the electrical circuits of the converters. The method is proposed for determining potentially unreliable power semiconductor devices in group connections based on the results of analyzing the distribution of reverse currents in parallel branches, which made it possible to create a series of devices for diagnosing power semiconductor devices in converters, both with and without communication resistors. The methodological error of measurements made using the developed express diagnostics devices of the transducers do not exceed the standard value equal to 10 %.

Adjacent Bi-Hierarchical Network for Scene Parsing of Remote Sensing Images

Driven by the rapid development and application of earth observation sensors, the scene parsing of remote sensing images (RSIs) has attracted extensive research attention in recent years. Restricted by the limited local receptive field of successive convolution layers, traditional models of scene parsing cannot effectively and interactively utilize the local-global information and digital surface model (DSM) of RSIs. Comparatively, accurate scene parsing faces more challenges because of unbalanced categories, small targets, and more complex scenes. To address these challenges, herein, we propose a novel adjacent bi-hierarchical network (ABHNet). Specifically, we introduce a DSM-enhanced (DSE) module to excavate characteristic DSM information from DSM images and enhance the red, green, and blue (RGB) features by exploiting informative cues between RGB and DSM modalities. In addition, an adjacent context exploration (ACE) module is proposed, which contains current and adjacent branches. The branches first exploit multiscale complementary characteristics of multilevel features and then integrate these features by applying adjacent exploration. Our model includes five ACE modules—three are deployed to activate detailed features and two obtain deep-guided features. The mutual collaboration of deep and detailed features is more beneficial to the segmentation of small objects. Extensive experiments on two remote sensing benchmark datasets (ISPRS Potsdam and Vaihingen) showed that the proposed ABHNet qualitatively and quantitatively outperformed other methods.

Position Sensorless Control for PMSM Drives With Single Current Sensor

The aim of this article is an attempt to provide a more credible control mode or a fault-tolerant control strategy for permanent magnet synchronous motor (PMSM) drives when an unexpected failure occurs to the current or position sensor. Considering that, a position sensorless control method that uses only one current sensor is proposed. Different from a traditional position sensorless control scheme that utilizes additional current sensors to obtain information of multiple phase currents, only a single current sensor (SCS) arranged on one of the current branches is included among the whole control circuit. Three-phase currents are reconstructed by sequentially sampling the SCS under specific voltage vectors, and directly employed for motor position estimation. A nonlinear position observer established according to the gradient descent is adopted. Focusing on the special current-acquisition pattern in this article, a step-size optimization method based on golden section search is proposed to minimize position estimation error. The experimental results reveal that the method in this article is comparable to the traditional full-current-sensor method in terms of position estimation, which confirms the fault-tolerant capability as one certain sensor of the control structure malfunctions.

0.5 V Universal Filter and Quadrature Oscillator Based on Multiple-Input DDTA

This paper presents a universal voltage-mode filter and quadrature oscillator based on low-voltage multiple-input differential difference transconductance amplifier (MI-DDTA). Unlike the previous published DDTAs, that utilize the bulk-driven (BD) multiple-input MOS transistor technique (MI-MOST) in the differential pair of the first stage only, the proposed DDTA, for the first time, utilize the BD MI-MOST in the second stage of the DDTA. This results in capability of providing more arithmetic operations without additional current branches or power dissipation. Hence, simplify the topology of the filter and oscillator applications, by decreasing the count of active blocks. The voltage-mode filter offers high-input and low-output impedances, and both non-inverting and inverting versions of five types of transfer functions, namely low-pass, high-pass, band-pass, band-stop, and all-pass characteristics. The oscillator offers three-phase of quadrature signals, and orthogonal control of the condition and frequency of oscillations. The circuit was designed in Cadence environment using 180 nm CMOS TSMC technology. The voltage supply is 0.5 V and the power consumption of the filter is 472 nW. The simulation results are in accordance with theory and confirm the performance of the proposed circuit.