Dynamic Control Technique Research Articles

Investigating the Effect of Different Drying Strategies on the Quality Parameters of Daucus carota L. Using Dynamic Process Control and Measurement Techniques

The present work aims to improve the understanding of the effect of different drying strategies at varying temperatures on the dynamic drying behaviour and quality of organic products such as carrots using non-invasive measurement techniques. For this purpose, carrot slices of 3 mm thickness were dried under three different strategies namely air temperature controlled (A), product temperature controlled (P) and stepwise temperature controlled (S) at different temperatures (50 °C, 60 °C and 70 °C) to measure and analyse the changes in moisture content, colour, total carotenoid retention, water activity, rehydration ratio and specific energy consumption. From the investigation performed, it was incurred that the application of different drying strategies influences rather significantly both the product quality as well as the overall process efficiency. Modelling the drying curves deemed Page model to be a good fit for all the strategies with R2adj = 0.99 and RMSE = 0.01. The results also show that implementing strategy P not only led to shorter drying times but also led to higher total carotenoid retention within the samples (TCR = 0.59–0.73). Colour changes, however, were observed to be maximum with strategy P as compared to strategy A and strategy S. Furthermore, the use of a non-invasive measurement technique such as infrared camera proved to be reliable in order to detect the phase transition of the product during the drying process.

Feasibility-ratio based sequencing for computationally efficient constrained optimization

Real world optimization problems typically involve constraints that must be satisfied for a design to be viable. Such constraints could represent physical limitations on induced behavior such as stress, displacement, temperature etc., or other practical limitations such as cost, geometry, manufacturability, etc. Constraint handling is therefore an active area of research, and a number of approaches have been proposed in the literature to be used with evolutionary algorithms to solve constrained optimization problems. Most approaches assume that the objective and constraints are simultaneously evaluated, and counted together as one evaluation as far as computation budget is concerned. However, in practical applications, there could be situations where the constraints and the objective can be independently evaluated (e.g., using different analyses). Therefore, it is worthwhile exploring if one can forego evaluation of certain constraints or the objective to save computational cost without misleading the search owing to insufficient information. Towards this end, the main focus of this study is to deal with a partial evaluation paradigm. We propose a feasibility-ratio based sequencing for partial evaluation of solutions during the evolutionary search. A lexicographic ranking approach is used for ordering the partially evaluated solutions. To balance the evaluation cost and information gain near constraint boundaries, a dynamic feasibility control technique is incorporated. A number of variants are systematically constructed to demonstrate the efficacy of partial evaluation and proposed sequencing approach. An extensive numerical study is conducted to evaluate the approach on a range of constraint problems, which confirms its competence.

Neuro-observer based control of double gimbal control moment gyro systems

In this paper, a new third-order nonlinear dynamics solving the mismatched problem is proposed for double gimbal control moment gyros (DGCMGs) affected by friction and coupling torques, unmodeled dynamics, or parameter uncertainties; the new nonlinear dynamics with the control inputs and the disturbances into the same equations should not be linearized and any control method handling multivariate systems with cross-coupling between channels can be then used to design a controller. Secondly, a feed-forward neural network based observer with disturbance rejection ability is proposed to estimate both the exogenous/endogenous disturbances and the states of the system, the number of necessary sensors being decreased. Thirdly, in order to control the rotations of the inner/outer gimbals, compensate the disturbances, enhance the robustness of the control system, and handle the channel interferences, we design, evaluate, and compare two novel control architectures using the Lyapunov theory, the backstepping method or the dynamic inversion control technique. Each of the two control architectures uses two interconnected controllers (an inner gimbal controller and an outer gimbal controller), a neuro-observer, and two reference models to generate the necessary fictive control signals. The simulation results show that the proposed control approaches provide very good angular rate precision of the DGCMG system and successfully handle a wide range of disturbances, parameter uncertainties, and channel interferences. The smaller fluctuations of the rotation angles, angular rates, and angular accelerations in the gimbal channels indicate that the backstepping control provides better ability to reject disturbances, smaller overshoot and convergence time than the dynamic inversion control technique.

An energy clock boosting based super regenerative receiver for WBANs

The use of low power, high sensitivity, ultra-regenerative (SR) receivers for WBAN is recommended in this document. To ensure high sensitivity while maintaining low power consumption, a two-stage cyclic cooling controller with automatic negative (-Gm) contact controller is designed to adjust the SRO bias current to double the input data rate. To reduce power consumption without affecting loop boost, a new SRO architecture has been introduced across platforms using dynamic threshold control techniques, larger adaptive bias, and gm optimization. The proposed 2.4 GHz centre frequency super regenerative receiver is implemented in a 180 nm CMOS technology using a clock optimization scheme.

Modeling and control of an electromechanical system with a permanent magnet generator and a voltage source converter

In the paper simulation dynamic models for the analysis of characteristics and transients of electromechanical system using a permanent magnet electric generator (PMG) connected to a variable speed fixed pitch wind turbine (WT) and a voltage source converter (VSC) mathematical models are developed. The system supplies a direct current (dc) resistive load through a controlled switch. The objective of the controlled resistive load connected to the VSC dc circuit of the system is to perform the dc output voltage stabilization for simulating the mode of generating the active power into a grid via a grid invertor. Two algorithm structures of realization of tracking the optimal WT motion trajectory in the coordinates “WT aerodynamical power – rotary speed” have been considered. The tracking algorithms function is to provide the maximization of power extraction from wind flow by WT. Electromechanical processes in the PMG – VSC system for both tracking algorithms have been investigated using developed dynamic simulation models and vector control technique of electromagnetic torque of the generator at variable WT mechanical power. The results of numerical investigations of the electromagnetic processes in the system have been analized. The efficiencies of the proposed control algorithms applied to the VSC in the considered electromechanical system have been compared and discussed.

High-Speed Production of Crystalline Semiconducting Polymer Line Arrays by Meniscus Oscillation Self-Assembly.

Evaporative self-assembly of semiconducting polymers is a low-cost route to fabricating micrometer and nanoscale features for use in organic and flexible electronic devices. However, in most cases, rate is limited by the kinetics of solvent evaporation, and it is challenging to achieve uniformity over length- and time-scales that are compelling for manufacturing scale-up. In this study, we report high-throughput, continuous printing of poly(3-hexylthiophene) (P3HT) by a modified doctor blading technique with oscillatory meniscus motion-meniscus-oscillated self-assembly (MOSA), which forms P3HT features ∼100 times faster than previously reported techniques. The meniscus is pinned to a roller, and the oscillatory meniscus motion of the roller generates repetitive cycles of contact-line formation and subsequent slip. The printed P3HT lines demonstrate reproducible and tailorable structures: nanometer scale thickness, micrometer scale width, submillimeter pattern intervals, and millimeter-to-centimeter scale coverage with highly defined boundaries. The line width as well as interval of P3HT patterns can be independently controlled by varying the polymer concentration levels and the rotation rate of the roller. Furthermore, grazing incidence wide-angle X-ray scattering (GIWAXS) reveals that this dynamic meniscus control technique dramatically enhances the crystallinity of P3HT. The MOSA process can potentially be applied to other geometries, and to a wide range of solution-based precursors, and therefore will develop for practical applications in printed electronics.

H∞ Tracking Control of Uncertain Markovian Hybrid Switching Systems: A Fuzzy Switching Dynamic Adaptive Control Approach.

This article investigates the H∞ stochastic tracking control problem for uncertain fuzzy Markovian hybrid switching systems by using a fuzzy switching dynamic adaptive control approach. The long and the short is to construct multiple piecewise stochastic Lyapunov functions which provide an effective tool for designing hybrid switching law and fuzzy switching dynamic adaptive law. A hybrid switching law, including both stochastic switching and deterministic switching, is designed to represent more general switching scenarios, which can improve the H∞ adaptive tracking performance through offering a running time before stochastic switching for the adaptive control strategy to work well. A fuzzy switching dynamic adaptive control technique is developed such that all signals of the tracking error equation are bounded, and the system state trajectory tracks the reference model state trajectory under a disturbance attenuation level as closely as possible. Finally, an application study verifies the effectiveness of the acquired methods.

A Dynamic Resonant Period Control Technique for Fast and Zero Voltage Switching in GaN-Based Active Clamp Flyback Converters

Compared to Si FETs, when the main GaN FET is in full zero voltage switching condition, maximum switching loss reduction can be achieved. Therefore, in this article, an active clamp flyback converter with GaN devices that implements fast ZVS by using the proposed dynamic resonant period control (DRPC) technique can reduce large transformer leakage inductance energy loss on the active resonant circuit. As the loading changes, the DRPC technique can dynamically adjust the on -time in auxiliary switch to prevent large voltage stress on the components in the primary side. In full load condition, the leakage energy loss can be reduced, thereby transferring more energy to the secondary side with maximum efficiency up to 94%.

The New Control Scheme for the PV and Wind Hybrid System Connected to the Single Phase Grid

The proposed system comprises of the hybrid (PV and wind) system for 1 kw is integrated with the single phase grid. The new control scheme sine pulse width modulation (SPWM) switching with a deadbeat based PI controller is designed to a DC/AC single phase inverter. This controller is used to pure sinusoidal output voltage with low total harmonic distortion (THD), fast dynamic response control techniques and to keep the power output constant if any variation in the input from the PV and wind system occurs, and the output voltage at the grid remains constant. Even when the load varies, the sinusoidal voltage output maintains 230Vrms with 50 Hz frequency and also low THD is 2.54%. This controller proves the stiffness and robustness characteristics for maintaining the output voltage at desired value with low harmonics.

Robust stabilisation for a class of stochastic T–S fuzzy descriptor systems via dynamic sliding‐mode control

In this study, the authors research the problem of robust stabilisation for a class of stochastic Takagi–Sugeno (T–S) fuzzy descriptor systems via dynamic sliding mode control technique. In the majority of stochastic T–S fuzzy sliding-mode control approaches, two restrictive assumptions are required, one is every subsystem's input matrix is identical, the other is the product of the sliding-mode gain and the stochastic perturbation matrix must be zero. In order to eliminate two restrictive assumptions, we put forward a dynamic sliding-mode control technique for a class of stochastic T–S fuzzy descriptor systems. A criterion is established according to linear matrix inequalities, it guarantees that the stochastic T–S fuzzy descriptor systems with the mismatched uncertainty and disturbance are stochastically admissible and strictly robust dissipative. Moreover, a dynamic sliding-mode controller ensures the reachability of the system trajectories to the predefined sliding surface in finite time. In the end, the technique is applied to an inverted pendulum model to demonstrate the merit and effectiveness of the proposed methods.

A 6.4–11 Gb/s Wide-Range Referenceless Single-Loop CDR With Adaptive JTOL

A referenceless single-loop clock and data recovery (CDR) with a 6.4–11-Gb/s capture range is presented. A dynamic bandwidth control (DBWC) technique for reducing the frequency-acquisition time and adaptive loop gain control (ALGC) for optimizing the jitter tolerance are described in detail. In addition, a cycle-slip detector (CSDET) with a consecutive-edge selector (CES) is proposed to improve the accuracy of the frequency detection. Fabricated in a 28-nm CMOS process, the proposed CDR has a frequency-acquisition time that is reduced by approximately 30% with the DBWC technique enabled. Also, the capture range is expanded by 1.1 Gb/s compared to the prior work due to improvement of the CSDET. The proposed ALGC technique based on jitter estimation is demonstrated with JTOL test results using PRBS15 input data with 0.28-UI ${_{PP}}$ random jitter and 1–100 MHz sinusoidal jitter.

Particle swarm optimization based proportional-derivative parameters for unmanned tilt-rotor flight control and trajectory tracking

ABSTRACTThis paper presents the dynamic modelling and control technique for a tilt-rotor aerial vehicle operating in bi-rotor mode. This kind of aircraft combines two flight envelopes, making it ideal for scenarios that require hovering, vertical take-off/landing and fixed-wing capabilities. In this work, a detailed mathematical model is derived using Newton–Euler formalism. Based on the obtained model, a new control scheme that incorporates six Proportional-Derivative (PD) controllers is proposed for the attitudes (roll (φ), pitch (θ), yaw (ψ)) and the positions (x, y, z) of the aircraft. Then, intelligent Particle Swarm Optimization (PSO) and conventional Reference Model (RM) techniques are applied for optimal tuning of the controllers' parameters. The stability analysis is developed using the Lyapunov approach and its application to the tilt-rotor system in the case of intelligent and conventional PD controllers. Numerical results of two scenarios prove the efficiency of the controllers tuned using the PSO method. Indeed, its ability to track the desired trajectories is demonstrated through 3D path tracking simulations, even in the presence of wind disturbances. Finally, experimental tests of stabilization and trajectory tracking are carried out on our prototype. These testing showed that our tilt-rotor was stable and suitably follows the imposed trajectories.

Torque ripple reduction of Induction Motor using Dynamic Fuzzy Prediction Direct Torque Control

This paper presents a Dynamic Fuzzy Logic based Prediction Direct Torque Control (DFL-PDTC) technique to reduce torque ripples within the squirrel cage induction motor (SCIM). This DFL and PDTC combination reduces the high amount of torque ripple and improves the starting conditions in both low& high mechanical speeds of the motor. The Induction Motor (IM) is used mainly in industrial applications due to its limited size and self-starting performance than other motors. The dynamic behavior of the SCIM is investigated in terms of a parameter such as torque, speed, and flux. In this work, a fuzzy logic controller (FLC) with the Gaussian membership function (GMFs) is used to generate an optimal control pulse, which controls the speed of the induction motor. Depending on the GMFs parameter, the motor speed is controlled and the number of torque ripples is decreased. Furthermore, PDTC selects the suitable voltage vector by analyzing the comparator output of Torque and flux and select the best one using the optimization method. In the proposed work, a Flower Pollination Algorithm (FPA) is used to optimize the GMFs parameter (α,c) in the controller, which reduces the number of ripples by selecting the best value (optimized). Whenever the motor runs, this optimized value is set as a fixed value to reduce the torque ripples. The experimental result indicates that the proposed optimization algorithm reduces the torque ripple using dynamic fuzzy controller and PDTC control techniques. The proposed method is implemented in the MATLAB/Simulink platform and the performance analysis highlights the efficiency of the suggested approach.

True eddy accumulation trace gas flux measurements: proof of concept

Abstract. Micrometeorological methods to quantify fluxes of atmospheric constituents are key to understanding and managing the impact of land surface sources and sinks on air quality and atmospheric composition. Important greenhouse gases are water vapor, carbon dioxide, methane, and nitrous oxide. Further important atmospheric constituents are aerosols, which impact air quality and cloud formation, and volatile organic compounds. Many atmospheric constituents therefore critically affect the health of ecosystems and humans, as well as climate. The micrometeorological eddy covariance (EC) method has evolved as the method of choice for CO2 and water vapor flux measurements using fast-response gas analyzers. While the EC method has also been used to measure other atmospheric constituents including methane, nitrous oxide, and ozone, the often relatively small fluxes of these constituents over ecosystems are much more challenging to measure using eddy covariance than CO2 and water vapor fluxes. For many further atmospheric constituents, eddy covariance is not an option due to the lack of sufficiently accurate and fast-response gas analyzers. Therefore, alternative flux measurement methods are required for the observation of atmospheric constituent fluxes for which no fast-response gas analyzers exist or which require more accurate measurements. True eddy accumulation (TEA) is a direct flux measurement technique capable of using slow-response gas analyzers. Unlike its more frequently used derivative, known as the relaxed eddy accumulation (REA) method, TEA does not require the use of proxies and is therefore superior to the indirect REA method. The true eddy accumulation method is by design ideally suited for measuring a wide range of trace gases and other conserved constituents transported with the air. This is because TEA obtains whole air samples and is, in combination with constituent-specific fast or slow analyzers, a universal method for conserved scalars. Despite the recognized value of the method, true eddy accumulation flux measurements remain very challenging to perform as they require fast and dynamic modulation of the air sampling mass flow rate proportional to the magnitude of the instantaneous vertical wind velocity. Appropriate techniques for dynamic mass flow control have long been unavailable, preventing the unlocking of the TEA method's potential for more than 40 years. Recently, a new dynamic and accurate mass flow controller which can resolve turbulence at a frequency of 10 Hz and higher has been developed by the first author. This study presents the proof of concept that practical true eddy accumulation trace gas flux measurements are possible today using dynamic mass flow control, advanced real-time processing of wind measurements, and fully automatic gas handling. We describe setup and methods of the TEA and EC reference flux measurements. The experiment was conducted over grassland and comprised 7 d of continuous flux measurements at 30 min flux integration intervals. The results show that fluxes obtained by TEA compared favorably to EC reference flux measurements, with coefficients of determination of up to 86 % and a slope of 0.98. We present a quantitative analysis of uncertainties of the mass flow control system, the gas analyzer, and gas handling system and their impact on trace gas flux uncertainty, the impact of different approaches to coordinate rotation, and uncertainties of vertical wind velocity measurements. Challenges of TEA are highlighted and solutions presented. The current results are put into the context of previous works. Finally, based on the current successful proof of concept, we suggest specific improvements towards long-term and reliable true eddy accumulation flux measurements.

Bridgeless Triple-Mode Resonant AC–DC Converter: Dynamic Modeling and Controls

This paper introduces the bridgeless triple-mode resonant ac–dc converter and presents its dynamic model and control technique. The proposed converter operates in triple mode: discontinuous-conduction mode (DCM), continuous-conduction mode (CCM), and missing resonance mode (MRM). It has the advantages of small number of required components, medium power capacity, and high efficiency, but it is difficult to control because DCM, CCM, and MRM have their own dynamic characteristics. To solve this control problem, the mode boundaries are first identified and, corresponding to each mode, the dynamic model is developed to design the controller. In each mode, we propose to add a repetitive controller (RC) with a phase-lead compensator to the conventional duty ratio plus feedback controller. The RC is used to suppress the deterministic periodic disturbances and the phase-lead compensator is used to compensate for the incurred phase lag. A 1-kW digitally controlled converter prototype is built and used to demonstrate the validity of the proposed modeling and control approach.

A super-regenerative-oscillator wake-up receiver for underwater applications with improved PVT immunity

A novel super-regenerative wake-up receiver for underwater communication systems is presented. Optimized wake-up receiver design for underwater communications plays an important role in increasing the deployment duration of sensor nodes through reduced power consumption. In this work, the super-regenerative oscillator (SRO) based receiver is designed to receive 20 kHz underwater acoustic signal. To enable high sensitivity without compromising the loop gain, a novel current-reuse SRO architecture is proposed using adaptive bulk biasing to increase negative transconductance $$ - G_{m} $$ under the same biasing current with improved sensitivity and start-up time. Differential input transistors with dynamic threshold control techniques are used to increase input transconductance and improve the gain without the need of a front-end low noise amplifier. A differential switch-controlled charge-pump is adopted to provide the quenching mechanism for the SRO. Furthermore, additional digital automatic gain control, frequency-lock loop, and common mode feedback are designed to improve the SRO immunity under process–voltage–temperature variations. The proposed super-regenerative receiver is implemented in TSMC 180 nm CMOS technology with center frequency of 20 kHz. It achieves sensitivity of − 83 dBm with data rate of 100 kbps and power consumption of 114 μW.

Modeling, Identification, and Control of a Discrete Variable Stiffness Actuator (DVSA)

A branch of robotics, variable impedance actuation, along with one of its subfields variable stiffness actuation (VSA) targets the realization of complaint robotic manipulators. In this paper, we present the modeling, identification, and control of a discrete variable stiffness actuator (DVSA), which will be developed for complaint manipulators in the future. The working principle of the actuator depends on the involvement of series and parallel springs. We firstly report the conceptual design of a stiffness varying mechanism, and later the details of the dynamic model, system identification, and control techniques are presented. The dynamic parameters of the system are identified by using the logarithmic decrement algorithm, while the control schemes are based on linear quadratic control (LQR) and computed torque control (CTC), respectively. The numerical simulations are performed for the evaluation of each method, and results showed the good potentialities for the system. Future work includes the implementation of the presented approach on the hardware.

A Low-Power, High-Sensitivity, OOK-Super-Regenerative Receiver for WBANs

A low power, high sensitivity, super-regenerative (SR) receiver for wireless body area networks (WBANs) is proposed in this brief. To enable high sensitivity while maintaining low power consumption, a two-step periodically quenching controller with automatic negative transconductance ( ${-G}_{{m}} $ ) controller is designed for tuning the biasing current of the super-regenerative oscillator (SRO) at twice the data rate of the input signal. To reduce the power consumption without compromising the loop gain, a novel cross-coupled SRO architecture using gm-boosting, adaptive bulk biasing, and dynamic threshold control techniques is presented. The proposed super-regenerative receiver with a center frequency of 2.4-GHz is implemented in 180-nm CMOS technology. Simulation results show that this receiver achieves a BER of ${2}{\times }{10}^{{-3} }$ at SNR = 12 dB and sensitivity of −87 dBm at 3.3 Mb/s while consuming 398 ${\mu }\text{W}$ .

A Novel Data Mining Approach for Analysis and Pattern Recognition of Active Fingerprinting Components

Active fingerprinting is an effective penetration testing technique to know about vulnerability of hosts against security threats and network as a whole. Sometimes firewalls may block fingerprinting packets, hence making the probes infeasible. Measured Round Trip Time (RTTm) is a benign number that can be obtained from communication based on legitimate non malicious packets. In this paper, RTTm has been used along with other timers namely Smoothened Round-trip Time (SRTT), Round-trip Time Variance (RTTVar), Retransmission Time Out (RTO) and Scantime for pattern recognition and association analysis with the aid of cross-correlations. Experimental relationship among these timers are derived to back-up existing theoretical knowledge. A novel method to estimate IP-ID Sequence classes and network-traffic intensity based on these timers has been proposed. Results show that the model can be used to accurately derive (about 100% accuracy) active fingerprinting components IP-ID sequences and link traffic estimation. Analytical results obtained by this study can help in designing high-performance realistic networks and dynamic congestion control techniques.

Long-Stroke Hydraulic Robot Motion Control With Incremental Nonlinear Dynamic Inversion

High precision motion control of hydraulic manipulators is challenging due to the highly nonlinear dynamics and model uncertainties typical for hydraulic actuators. This paper addresses the implementation of a novel sensor-based incremental nonlinear dynamic inversion control technique for a high-precision hydraulic force controller in existence of parameter uncertainties. Combined with a widely used force computation outer-loop controller, the proposed motion control structure is implemented on a 6-DOF hexapod hydraulic robot, the Simulation, Motion and Navigation (SIMONA) Research Simulator, TU Delft. The proposed control technique is inherently robust to hydraulic parameter uncertainties. As an important contribution, the robustness against parameter uncertainty is rigorously proven. Stability of the proposed controller is also analyzed. Techniques for solving characteristic implementation issues, such as higher-order valve dynamics and oil transmission effects, are discussed in detail. Motion tracking experiment results on the SIMONA simulator validate the effectiveness of the proposed method in terms of performance and the robustness against parameter uncertainties. Significant control accuracy improvement is demonstrated by comparing with the state-of-the-art motion control implementations.