Loop Control System Research Articles

An Integrated Transient Enhancement Circuit Suitable for Buck Converter With Large Output Capacitor

This brief proposes an integrated transient enhancement circuit (TEC) suitable for Buck converter with large output capacitor, which is composed by resistors, capacitors, and operational amplifier. The presented TEC brings in two additional zeros and two additional poles in the system control loop without affecting the low frequency characteristics. The introduced zeros and poles extend the bandwidth of the loop as they are placed before crossover frequency. With load transient response, the system response speed can be accelerated and the overshoot/undershoot voltage can be reduced. A current-mode Buck converter with the proposed TEC is implemented in a 0.35 ${\mu }\text{m}$ BCD process. With a 330- $\mu \text{F}$ output capacitor and a 2.5-A/ ${\mu }\text{S}$ load change, the undershoot/overshoot voltage and recovery time are 32/46 mV and 74/88 ${\mu }\text{s}$ , respectively, which are improved by 39% compared with those of converter without proposed TEC.

Enhancing Optimal Automatic Generation Control in a Multi-Area Power System With Diverse Energy Resources

New power system control methodologies have recently been proposed that combine economic dispatch (ED) and automatic generation control (AGC) in order to maintain economic operation when the generation mix incorporates a high penetration of renewable energy sources. The theoretical framework that underpins these techniques assumes that an aggregated control area (CA) model can be defined, assuming that the dynamic response of the entire CA is dominated by a single energy source, typically a steam-turbine generator. This paper investigates a combined AGC and ED control methodology for a power system with CAs containing multiple hybrid energy resources that cannot be simply aggregated into a single equivalent source. An optimization approach is then used to develop a control law and parameter design algorithm for each energy source, which accounts for their individual dynamics while aggregating the generators output to match with the target output of the CA. The performance of the proposed AGC and ED controller is demonstrated using simulation studies of an interconnected power system, conducted within the DIgSILENT power factory platform. This model incorporates non-linear network system dynamics and control loops within automatic voltage regulators and power system stabilizers. The study results indicate that the proposed AGC optimal control strategy offers superior performance compared to traditional and recently published economic AGC strategies, particularly when the generation mix includes both dispatchable conventional sources and a high penetration of non-dispatchable or semi-dispatchable sources such as wind.

A variable sampling period scheduling method for networked control system under resource constraints

ABSTRACTIn order to improve the performance of networked control system, a variable sampling period scheduling method for networked control system under resource constraints is presented based on network operation state. First, the scheduler obtains the current and past network utilisation, and packet transmission delay online. Based on the acquired network state, the improved particle swarm optimisation algorithm is used to optimise Gaussian process regression model to predict the network utilisation and packet transmission delay in the next sampling period. According to the error and error change rate of system control loop, the weight of the control loop is calculated based on fuzzy rules. Then, in accordance with the needs of network performance and control performance, the network bandwidth is allocated based on the predictive value of network utilisation and packet transmission delay. Finally, the new sampling period of each control loop is calculated. The simulation experiments are performed out based on True time toolbox. The simulation results show that the proposed variable sampling period scheduling methodcan improve output control performance of the system, reduce the packet transmission delay and integral absolute error value of the control loops, and improve network utilisation. The overall control performance of the system is improved. The variable sampling period scheduling method in this paper is effective.

Do groundwater management plans work? Modelling the effectiveness of groundwater management scenarios

In contrast to management optimisation methods, which quantify decision variables to create plans, this study does not seek the “best” strategy. Instead, it simulates the sequential decision-making process implicit in environmental management, so that the effectiveness of management scenarios, when implemented as intended, can be evaluated. The purpose was to develop a methodology to quantitatively evaluate the effectiveness of groundwater management plans by simulating sequential management decisions that evolve based on aquifer/management feedback. A groundwater management scheme was structured as a system control loop to capture the aquifer/management feedback, and management decisions were based on realistically sparse observation times and locations. The method indicates how a plan may proceed in reality under alternate timings and frequencies of management decisions and in systems with differing response times. A synthetic example quantified the impact of a generic plan, specifying environmental objectives, extraction restrictions and entitlement limits (maximum volume/year that users are permitted), relative to no-management by combining a numerical model of “reality” with management rules under a stochastic climate. The management decision-making frequency varied from daily to decadal. Generally, effectiveness decreased as the interval between management interventions increased and intervals greater than annual showed minimal improvement compared to entitlement only. The timing of management decisions relative to the irrigation season also impacted plan effectiveness, and when decisions were made prior to the irrigation season, quarterly management was less effective than annual and biannual management. By testing the capacity of plans to achieve objectives, groundwater management can be systematically and objectively improved.

A linear control of composite model for glucose insulin glucagon pump

Abstract Presently Type 1 diabetes is global issue and challenges for diabetes public for healthy life. Fully automatic artificial pancreas is well solution for diabetic patients to avoid the hyperglycemia/hypoglycemia as it provided the insulin/glucose when needed. A composite model of Glucagon-Glucose Dynamics is treated for type 1 diabetes mellitus to check the linear controllability and observability of the model and the stability analysis by using Lyapunov function. Two cases are discussed in system according to the input. For case I, Insulin as the input only and glucose as an output and in case II insulin and glucagon as an input and glucose as output only. A control system can only be used in the form of closed-loop control to stabilize the system. This may be show vital part in the progress of fully automatic artificial pancreas and stabilize the control loop system for the Glucose Insulin Glucagon pump.

Renewable power systems dynamic security using a new coordination of frequency control strategy based on virtual synchronous generator and digital frequency protection

The renewable power systems have become more susceptible to the system insecure than traditional power systems due to reducing of the total inertia and damping properties that result from replacing the conventional generators with Renewable Energy Sources (RESs) as well as decoupling of the RESs from the AC grid using power converters. Therefore, maintaining the dynamic security of renewable power systems is the key challenge for integrating more RESs. This paper addresses a new strategy of frequency control including virtual inertia control based on Virtual Synchronous Generator (VSG), which emulates the behavior of conventional synchronous generators in large power systems, thus adding some inertia to the system control loop virtually and accordingly stabilizing the system frequency during high penetration of RESs. Moreover, the proposed virtual inertia control system-based VSG is coordinated with digital frequency protection for improvement the frequency stability and preservation the power system dynamic security because of the high integration level of the RESs. The effectiveness of the proposed coordination scheme is tested and verified through small and large scales of power systems, Microgrid (µG) and real hybrid power system in Egypt, respectively. System modelling and simulation results are carried out using Matlab/Simulink® software. The simulation results validated that the proposed coordination scheme can effectively regulate the system frequency and ensure robust performance to maintain the dynamic system security with high share of RESs for different contingencies.

High Voltage DC Transmission with Power Synchronization Control using VSC

The main scope of this paper is a propose suitable power synchronization control scheme for high voltage dc links based on voltage source converter (VSC), operating with ac grid. The proposed of power synchronization control (PSC) concept, where grid synchronization achieved without use of dedicated synchronization unit in MATLAB/Simulink. PSC concept used, where detect the power at the sending side and meet the system power demand at receiving side through high voltage. PLL system is also implemented for synchronize converter with grid and current control loop system is perform to minimize the active reactive power demand in grid. We can develop the VSC-HVDC link model in MATLAB/Simulink to observer our system response.

From mind to molecules and back to mind-Metatheoretical limits and options for systems neuropsychiatry.

Psychiatric illnesses like dementia are increasingly relevant for public health affairs. Neurobiology promises progress in diagnosis and treatment of these illnesses and exhibits a rapid increase of knowledge by new neurotechnologies. In order to find generic patterns in huge neurobiological data sets and by exploring formal brain models, non-linear science offers many examples of fruitful insights into the complex dynamics of neuronal information processing. However, it should be minded that neurobiology neither can bridge the explanatory gap between brain and mind nor can substitute psychological and psychiatric categories and knowledge. For instance, volition is impaired in many mental disorders. In experimental setups, a "preactional" brain potential was discovered that occurs 0.5 s before a consciously evoked motor action. Neglecting the specific experimental conditions, this finding was over-interpreted as the empirical falsification of the philosophical (!) concept of "free volition/will." In contrast, the psychology of volition works with models that are composed of several stage-related hierarchically nested mental process cycles that were never tested in obviously "theory-free" neurobiology. As currently neurobiology shows a network turn (or systemic turn), this is one good reason to enhance systemic approaches in theoretical psychology, independently from neurobiology that still lacks "theory." Cybernetic control loop models and system models should be integrated and elaborated and in turn could give new impulses to neuropsychology and neuropsychiatry that conceptually can more easily connect to a network-oriented neurobiology. In this program, the conceptual background of nonlinear science is essential to bridge gaps between neurobiology and psychiatry, defining a real "theoretical" field of neuropsychiatry.

Controllability and observability of glucose insulin glucagon system in humans

Artificial pancreas is one of the solutions to control the type1 diabetes mellitus now days. Efforts are being made to develop the artificial pancreas. The controllability and observability of the glucose insulin glucagon dynamical model is calculated which is the modified form of composite model of glucose insulin glucagon dynamics for type 1 diabetes mellitus is considered. The concept of controllability and observability for the linearized control system is used to design a feedback control. This model completely describes the glucagon affects the safety of artificial pancreas to overcome the risk of hyperglycemia. Composite model of glucagon-glucose dynamics and its extension is treated for type 1 diabetes mellitus to check the linear controllability and observability. Two cases are discussed on the basis of input of the system. For case I, insulin as the only input and glucose as an output and in case II insulin and glucagon as inputs and glucose as only output. The model is observable but not controllable in each case. This may show vital part in the progress of fully automatic artificial pancreas and stabilize the control loop system for the glucose insulin glucagon (GIG) pump to control the type 1 diabetes mellitus.

Stability analysis and control of the glucose insulin glucagon system in humans

The goal for the treatment of type-1 diabetes mellitus is the development of an artificial pancreas to regulate the blood glucose level in a closed loop design. A system of nonlinear differential equations having five variables (glucose, insulin, β-cell mass, α-cell mass, and glucagon) with seventeen parameters is considered. The Lyapunov function is used to check the stability analysis of the model. Controllability and observability of the linearized model are discussed under two different cases: in case 1 insulin is taken as an input, and in case 2 insulin and glucagon are taken as inputs for the system. This model played an important role in the development of a fully automatic artificial pancreas by stabilizing the control loop system for the glucose-insulin glucagon pump. A proportional integral derivative (PID) controller is designed for an artificial pancreas by using the transfer function. According to the desired value, the algorithm of an artificial pancreas measures the glucose level in the blood of a patient by using a glucose sensor that sends a signal to an insulin glucagon pump to adjust the basal insulin. A closed-loop system is tested in the Simulink environment, and the simulation results show the performance of the designed controller.

Assessment of Cardiac Vegetative Control during Acute Graduated Exogenous Normobaric Hypoxia in Rats.

The effects of exogenous normobaric hypoxic hypoxia on vegetative control of the heart and BP were examined in Wistar rats. The reference ranges of variation pulsometry parameters were determined in rats with normoxemia for 3 physiological variants of autonomic homeostasis: eutony, sympathicotony, and vagotony. Most rats (80%) demonstrated autonomic eutony. The study showed that saturation of arterial blood with oxygen is the most adequate assessment of severity of acute exogenous normobaric hypoxic hypoxia progressing within a closed hypoxic chamber, which standardizes this method and minimizes inaccuracies resulting from individual sensitivity to hypoxic stress. The changes in functional activity of systems that control the heart rhythm closely correlated with the drop in arterial blood oxygenation. While a small arterial hypoxemia activated the ergotropic elements of autonomic nervous system central subdivision accompanied by elevation of systolic BP, the moderate hypoxemia augmented the cholinergic influences and moderated the adrenergic ones under maintaining mobilization of the central autonomic nervous system-control loop and normotension. Severe hypoxemia was manifested by augmented influences from autonomic nervous system central subdivisions on the heart rate, disadaptation of the control systems, and systolic-diastolic arterial hypotension.

A new practical feed-forward cascade analyze for close loop identification of combustion control loop system through RANFIS and NARX

Boiler-turbine is a multi-variable and complex system in steam power plants including combustion control loop, temperature control loop and drum water level control loop, where each of them are separate control loops. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complex task, because of nonlinear time variant dynamic characteristics of the boiler. In the present article, a realistic and efficient model of the combustion control loop of the 320 MW steam power plant of Islam Abad, Isfahan is identified separately from other control loops of the boiler, unlike similar articles. Another critical point about this article is being superior to the others, due to identifying the combustion control loop system by feed-forward cascade analysis. Due to the sensitivity and complexity of the system, with respect to its nonlinear and closed loop characteristics, the combustion control loop system is considered as a feed-forward cascade and the identification of the system is carried out during the load changes and conducted through intelligent procedures like recurrent adaptive neuro-fuzzy inference system (RANFIS) and nonlinear autoregressive model with exogenous input (NARX). The obtained results through actual data collected from the plant are presented and the accuracy of the procedures is determined.

The Research on Characteristics of Hydraulic Support Advancing Control System in Coal Mining Face

This paper researches the electro hydraulic control system of two-column shield hydraulic supports, takes the hydraulic support base advancing loop as the position servo control system, and studies its dynamic characteristics. It establishes the power amplifier, position sensor, hydraulic cylinder and loading mathematical model of the position servo control system, determines the model parameters of the advancing control system according to the shield hydraulic support used in the 1315 working face of GuoTun coal mine, and derives the opening loop transfer function of the valve controlled advancing cylinder. This paper also analyzes the stability of the control system of the advancing loop with the modern design method, and verifies the stability of the electro-hydraulic control system loop according to the simulation curve and the stability. By comparing with the valve core displacement and system flow curve while the system opening or closing, this paper explains the application effect of servo control system. It provides a new research idea and method for the study of the overall stability and effectively reduces the failure rate of electro-hydraulic control system of the hydraulic support. It also plays practical significance and value to improve the mining efficiency of the coal mining face.

Stability Analysis of Discrete-time Networked Control T-S Fuzzy Systems

Background: The networked control systems are becoming progressively more significant and have many outstanding advantages compared to traditional point-to-point control systems. T-S fuzzy systems are nonlinear systems described by a set of If-Then rules. Especially, the combination communication networks with feedback control loops for fuzzy systems are worthy of being investigated, such as network-induced time delays, and control. Methods: Owing to existing network-induced random delays of the forward and feedback communication links in a direct-drive linear control system, we use two homogeneous Markov chains to express the delays. For the stability analysis, the new Lyapunov function and the free-weighting matrix inequality technique are used. Results: A new stability criterion is obtained, and the controller can be computed in terms of linear matrix inequalities (LMIs). The new criterion is less conservative for a new non finite-sum term is introduced in the Lyapunov-krasovskii functional, which brings some adjustable slack variables into the criterion, and can be efficient use of the networked delay information. Conclusion: The new stability criterion is shown to be effective and efficient by the numerical examples. It improves the stability theory of networked control systems and T-S fuzzy systems. Keywords: Networked control systems, State feedback control, Finite-sum inequalities, Takagi-Sugeno (T-S) fuzzy model, communication networks, stability analysis.

The research of the pulse oxygen supply based on the fuzzy control technology

According to the working principle of pulse oxygen supplies, we analyze how to realize the control of the oxygen flow by double different valves. a two-dimensional fuzzy control system is proposed to solve the unstable problem, which is brought by the shortcomings of the open-loop control system. We add a new parameter, the rate of the differential pressure signal changes, which contributes to a close –loop control system and increases the stability of the system. The experiments and the data show that the fuzzy control system make the process of breathing much more comfortable and solve the hysteresis and overshoot caused by the open-loop control system. The product reliability has been greatly improved.

Mitigation of TMR Using Energy Ratio and Bit-Flipping Techniques in Multitrack Multihead BPMR Systems

Track misregistration (TMR) in ultra-high density bit-patterned media recording (BPMR) is one of the crucial problems, because it can severely degrade the overall system performance. In practical, TMR can be detected and adjusted by a servo control loop system. However, this paper proposes to utilize multiple readback signals obtained from the optimized positioning of the two side read head closer to the main read head to improve the TMR prediction process in a multitrack multi-head BPMR system with position jitter noise. In addition, we also propose the soft-information exchange and the bit-flipping techniques for the multitrack data detection, so as to improve the bit-error rate (BER) performance of all three data tracks simultaneously. Simulation results indicate that the proposed system is superior to the conventional system, especially, when the amount of TMR and position jitter is high. Furthermore, we also found that the upper and lower read heads, which are moved closer to the center track by 25% of a track pitch, will provide the best BER performance with and without position jitter noise.

Control of an artificial human pancreas

The controllability and observability of a glucose insulin system is checked for the Sturis–Tolic model and its modified form for a type 1 diabetic patient. This technique plays a vital role in the development of a fully automatic artificial pancreas and stabilizes the control loop system for the glucose insulin pump. It would be important for helping type 1 diabetic patients to control their disease. We treated the Sturis–Tolic model for a healthy person and modified this model for a type 1 diabetic patient to check the linear controllability and observability. The Lyapunov equation is used to check the stability analysis of the model, which yields that the modified model is stable. We show the numerical simulation of the model for type 1 diabetes mellitus for the controllability and observability matrix according to different initial conditions on state vector. These models can be used to simulate a glucose insulin system for the treatment of type 1 diabetes.

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth.

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production.

Evaluation of Nonlinear Model-Based Predictive Control Approaches Using Derivative-Free Optimization and FCC Neural Networks

Nonlinear control methods have been researched with the objective of improving performance of control loop systems. Among such control methods, nonlinear model-based predictive control (NMPC) strategies present significant importance, mainly due to explicit performance optimization and constraint handling. NMPC depends on a representative nonlinear model of the process to be controlled and an adequate optimization method. This work focuses on these two aspects. Simulation tests with a wastewater treatment process model are presented, to evaluate the use of two optimization methods, differential evolution and bound optimization by quadratic approximation (BOBYQA), under different conditions. Experimental results using BOBYQA and a fully connected cascade artificial neural network in a pressure process are presented, showing a performance improvement comparing to a linear model predictive controller.

Harmonic Instability Assessment Using State-Space Modeling and Participation Analysis in Inverter-Fed Power Systems

This paper presents a harmonic instability analysis method using state-space modeling and participation analysis in the inverter-fed ac power systems. A full-order state-space model for the droop-controlled distributed generation (DG) inverter is built first, including the time delay of the digital control system, inner current and voltage control loops, and outer droop-based power control loop. Based on the DG inverter model, an overall state-space model of a two-inverter-fed system is established. The eigenvalue-based stability analysis is then presented to assess the influence of controller parameters on the harmonic instability of the power system. Moreover, the harmonic-frequency oscillation modes are identified, where participation analysis is presented to evaluate the contributions of different states to these modes and to further reveal how the system gives rise to harmonic instability. Based on the participation analysis, a reduced-order model for harmonic instability analysis is also proposed. The experimental results are presented for validating the theoretical analyses.