Feedback Control Loop Research Articles

(Keynote) Real-Time Biosensors for Continuous Measurements of Biomolecules in Live Subjects

A biosensor capable of continuously measuring specific molecules in vivo would provide a valuable window into patients’ health status and their response to therapeutics. Unfortunately, continuous, real-time molecular measurement is currently limited to a handful of analytes (i.e. glucose and oxygen) and these sensors cannot be generalized to measure other analytes. In this talk, we will present a biosensor technology that can be generalized to measure a wide range of biomolecules in living subjects. To achieve this, we develop synthetic antibodies (aptamers) that change its structure upon binding to its target analyte and produce an electrochemical current or emit light. Our real-time biosensor requires no exogenous reagents and can be readily reconfigured to measure different target analytes by exchanging the aptamer probes in a modular manner. Using our real-time biosensor, we demonstrate the first closed loop feedback control of drug concentration in live animals and discuss potential applications of this technology. Finally, we will discuss methods for generating the aptamer probes which are at the heart of this biosensor technology.

Integrated Prognostics Observer for Condition Monitoring of an Automated Manual Transmission Dry Clutch System

The closed loop feedback control system of an Automated Manual Transmission (AMT) electro-pneumatic clutch actuator is used for intelligent real time condition monitoring, enhanced diagnostics and prognostic health management of the dry clutch system, by integrating with the existing gearbox prognostics observer. The real-time sensor data of the clutch actuator piston position is analyzed for monitoring the condition of the clutch system. Original parameters of the new clutch are stored in the Electrically Erasable Programmable Read-only Memory (EEPROM) of the AMT controller and the real-time data is used by the observer for assessing the degradation/wear of the frictional clutch parts. Also, clutch slip during torque transmission is monitored, using the engine speed and the gearbox input shaft speed from Controller Area Network (CAN). Condition monitoring of clutch system provides enhanced prognostic functionality for AMT system which ensures consistent clutch performance, gear shift quality and timely warning for recalibration, repair and/or replacement of the critical wear and tear parts. Also, systematic analysis of the monitored data provides an accurate diagnosis of a developing fault. Thus, with the advanced control systems in place for AMT, a closed loop feedback based condition monitoring system is modelled for improved diagnostics and prognostics of AMT clutch system.

Synchronization and Sampling Time Analysis of Feedback Loop for FPGA-Based PMSM Drive System

The proportional-integral (PI)-based control for the motor drive system is commonly used in industrial applications. However, motor drive system development and prototyping are tedious tasks especially considering a field programmable gate array (FPGA)-based real-time system implementation. In addition, the time-synchronization of the feedback control loop is another vital aspect concerning sampling time for the discrete-time controller. This paper presents an FPGA-based design and development of a permanent magnet synchronous motor (PMSM) drive system considering the impact of time-synchronization corresponding to the sampling time criteria for a feedback control loop. Furthermore, the repercussion of time-synchronization is examined for the transient conditions due to a step change in load as well as motor speed. The field-oriented control (FOC) of the PMSM drive system is designed and implemented for the system authentication using a digital model integration approach provided by the Xilinx system generator (XSG) and VIVADO platform. Moreover, harmonic distortion in the motor current is considered for an in-depth analysis of the system performance corresponding to sampling time as well as switching frequencies.

Adaptive monitoring for autonomous vehicles using the HAFLoop architecture

ABSTRACT Current Self-Adaptive Systems (SASs) such as Autonomous Vehicles (AVs) are systems able to deal with highly complex contexts. However, due to the use of static feedback loops they are not able to respond to unanticipated situations such as sensor faults. Previously, we have proposed HAFLoop (Highly Adaptive Feedback control Loop), an architecture for adaptive loops in SASs. In this paper, we incorporate HAFLoop into an AV solution that leverages machine learning techniques to determine the best monitoring strategy at runtime. We have evaluated our solution using real vehicles. Evaluation results are promising and demonstrate the great potential of our proposal.

Towards better understanding of the influence of process parameters in roll compaction/dry granulation on throughput, ribbon microhardness and granule failure load

A key quality attribute for solid oral dosage forms is their hardness and ability to withstand breaking or grinding. If the product is to be manufactured continuously, it can be of interest to monitor the hardness of the material at different stages of manufacturing. Using the controlled process parameters of roll compaction/dry granulation specific compaction force, roll speed and gap width, hardness of the resulting ribbons and granules can be predicted. For the first time, in this study two yield variables (corrected torque of the granulation unit and throughput of material) are used to predict the granules failure load. The increase in granule hardness was monitored in-line when the specific compaction force was increased during the compaction process. This opens the way for in-line control of material hardness, and its use for feedback and feedforward control loops for future continuous manufacturing processes.

Optimising power system frequency stability using virtual inertia from inverter‐based renewable energy generation

The objective of this study is to optimise the use of virtual inertia given a virtual inertia budget and a network topology. Following a brief investigation into inertia distribution, it was observed that distributed inertia is more effective than centralised inertia for a large and sparse power system network. A subsection of the South African transmission network, the Western Transmission network, is expected to host large-scale inverter-based generation. The total power system inertia is in decline due to the large-scale integration of inverter-based renewable energy generation. In the literature, mitigation methods such as virtual inertia and ‘noise-cancelling’ network topology design has been proposed to improve frequency stability. In this study, the Western Transmission network is modelled as a network of coupled oscillators. A state-space model for the power system network is developed with virtual inertia as a feedback control loop. The H 2 -norm is used to design optimal feedback control through virtual inertia allocation/distribution, to increase power system frequency stability. The results show that the optimal distribution significantly improves system frequency stability by decreasing the rate of change of frequency and delaying the time to reach similar frequency nadir values.

Optimal DC Voltage and Current Control of an LCC HVDC System to Improve Real-Time Frequency Regulation in Rectifier- and Inverter-Side Grids

High-voltage direct-current (HVDC) systems for constant or intermittent power delivery have recently been developed further to support grid frequency regulation (GFR). This paper proposes a new control strategy for a line-commutated converter-based (LCC) HVDC system, wherein the dc-link voltage and current are optimally regulated to improve real-time GFR in both rectifier- and inverter-side grids. A dynamic model of an LCC HVDC system is developed using the dc voltage and current as input variables, and is integrated with feedback loops for inertia emulation and droop control. A linear quadratic Gaussian (LQG) controller is also designed for optimal secondary frequency control, while mitigating conflict between the droop controllers of HVDC converters. An eigenvalue analysis is then conducted, focusing on the effects of model parameters and controller gains on the proposed strategy. Simulation case studies are performed using the models of a real HVDC system and a CIGRE benchmark system. The case study results confirm that the proposed strategy enables the HVDC system to improve GFR, in coordination with generators in both-side grids, by exploiting the fast dynamics of HVDC converters. The proposed strategy is also effective under various conditions for the LQG parameters, inertia emulation, and droop control.

Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of critical engineered systems/processes masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, industrial processes, etc.) may be compromised by feedback control loops, which mask severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control, and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. A novel control-theoretic framework is presented to address the masking problem. Major elements of the proposed approach are employed in simulation to develop, implement and validate how faults are distinguished from disturbances and how faults are detected and identified with performance guarantees, i.e., prescribed confidence level and given false alarm rate.The demonstration and validity of the tools/methods employed necessitates, in addition to the theoretical content, a suitable testbed. We have employed and describe briefly in this paper an autonomous hovercraft as the test prototype. We pursue a systems engineering process to design, construct and test the prototype hovercraft instrumented appropriately for purposes of fault injection, monitoring and the presence of control loops. We emphasize a general control-theoretic framework to the masking problem and utilize a simulation environment to derive results and illustrate the efficacy of the methodology.

Fault Tolerant Digital Data-Path Design via Control Feedback Loops

In this paper, we propose a novel fault tolerant methodology for digital pipelined data-paths called Control Feedback Loop Error Decimation (CFLED), that reduces the error magnitude at the outputs. The data-path is regarded from a control perspective as a process affected by perturbations or faults. Based on the corresponding dynamic model, we design feedback control loops with the goal of attenuating the effect of the faults on the output. The correction loops apply correction factors to selected data-path registers from blocks that have their execution rewinded. We apply the proposed methodology on the data-path of a controller designed for a 2-degree of freedom robot arm, and compare the cost and reliability to the generic triple modular redundancy. For Field Programmable Gate Array (FPGA) technology, the solution we propose uses 30% less slices with respect to Triple Modular Redundancy (TMR), while having a third less digital signal processing blocks. Simulation results show that our approach improves the reliability and error detection.

On the maximal parameter range of global stability for a nonlocal thermostat model

The global asymptotic stability of the unique steady state of a nonlinear scalar parabolic equation with a nonlocal boundary condition is studied. The equation describes the evolution of the temperature profile that is subject to a feedback control loop. It can be viewed as a model of a rudimentary thermostat, where a parameter controls the intensity of the heat flow in response to the magnitude of the deviation from the reference temperature at a boundary point. The system is known to undergo a Hopf bifurcation when the parameter exceeds a critical value. Results on the characterization of the maximal parameter range where the reference steady state is globally asymptotically stable are obtained by analyzing a closely related nonlinear Volterra integral equation. Its kernel is derived from the trace of a fundamental solution of a linear heat equation. A version of the Popov criterion is adapted and applied to the Volterra integral equation to obtain a sufficient condition for the asymptotic decay of its solutions.

Explicit multiobjective model predictive control for nonlinear systems with symmetries

SummaryModel predictive control is a prominent approach to construct a feedback control loop for dynamical systems. Due to real‐time constraints, solving model‐based optimal control problems in a very short amount of time can be challenging. For linear‐quadratic problems, Bemporad et al have proposed an explicit formulation where the underlying optimization problems are solved a priori in an offline phase. In this article, we present an extension of this concept in two significant ways. We consider nonlinear problems and—more importantly—problems with multiple conflicting objective functions. In the offline phase, we build a library of Pareto optimal solutions from which we then obtain a valid compromise solution in the online phase according to a decision maker's preference. Since the standard multiparametric programming approach is no longer valid in the nonlinear situation, we instead use interpolation between different entries of the library. To reduce the number of problems that have to be solved in the offline phase, we exploit symmetries in the dynamical system and the corresponding multiobjective optimal control problem. The results are verified using two different examples from autonomous driving.

Tuning monoclonal antibody galactosylation using Raman spectroscopy-controlled lactic acid feeding.

A key aspect of large-scale production of biotherapeutics is a well-designed and consistently-executed upstream cell culture process. Process analytical technology tools provide enhanced monitoring and control capabilities to support consistent process execution, and also have potential to aid in maintenance of product quality at desired levels. One such tool, Raman spectroscopy, has matured as a useful technique to achieve real-time monitoring and control of key cell culture process attributes. We developed a Raman spectroscopy-based nutrient control strategy to enable dual control of lactate and glucose levels for a fed-batch CHO cell culture process for monoclonal antibody (mAb) production. To achieve this, partial least squares-based chemometric models for real-time prediction of glucose and lactate concentrations were developed and deployed in feedback control loops. In particular, feeding of lactic acid post-metabolic shift was investigated based on previous work that has shown the impact of lactate levels on ammonium as well as mAb product quality. Three feeding strategies were assessed for impact on cell metabolism, productivity, and product quality: bolus-fed glucose, glucose control at 4 g/L, or simultaneous glucose control at 4 g/L and lactate control at 2 g/L. The third feeding strategy resulted in a significant reduction in ammonium levels (68%) while increasing mAb galactosylation levels by approximately 50%. This work demonstrated that when deployed in a cell culture process, Raman spectroscopy is an effective technique for simultaneous control of multiple nutrient feeds, and that lactic acid feeding can have a positive impact on both cell metabolism and mAb product quality.

An active meta-layer for optimal flexural wave absorption and cloaking

Flexural wave propagation is common in thin structures and plays a key role in vibrations of structures. Designs of flexural wave absorbers for vibration control have been constantly pursued for decades aiming to find structures that can best balance tradeoffs between small sizes or lightweights and broadband operations. However, their absorption performance has long been evaluated on a case-by-case basis, and the theoretical limit characterizing the relationship between the absorption spectrum and the sample thickness and mass density is missing. In this study, by adopting an inequality as its electromagnetism and acoustics counterparts, the theoretical limit of flexural wave absorption is established. An active meta-layer composed of piezoelectric sensors and actuators with feedback control loops is proposed for optimal wave absorption. We experimentally demonstrate the active meta-layer for optimal broadband wave and vibration control in the beam and acting as skin cloaks of large voids in the plate. The active meta-layer is electrically programmable and scalable without losing stability. The approach proposed sheds light on designs of reconfigurable dynamic control devices and enables alternative solutions for ultrasonic sensing of complex engineering structures.

Real-time plasma position reflectometry system development and integration on COMPASS tokamak

O-mode frequency-modulated continuous wave (FMCW) reflectometry provides an alternative to magnetic measurements in the determination of the plasma separatrix position for plasma position control. This type of measurement proves to be particularly attractive for the control of future fusion reactors where the harsh radiation environment may damage magnetic probes or induce non-compensable measurement drifts. Plasma position reflectometry (PPR), first demonstrated in ASDEX-Upgrade, is a control technique that is increasingly important to validate in diversified experimental devices and relevant plasma regimes. The COMPASS tokamak provides suitable conditions for such advanced demonstrations and regular PPR operation and development, thanks to its O-mode reflectometer and Multi-Threaded Application Real-Time executor (MARTe) based real-time control system. Herein we present the integration of a PPR system on COMPASS, both at hardware and software levels. Reflectometry swept measurements require signals to be acquired in bursts of data and streamed to the corresponding MARTe-PPR node through PCIe® fibre-optic links. The data transferred in real-time is used to reconstruct the radial density profiles from which the outer separatrix position is estimated. This estimate is then delivered to the central MARTe controller node via a dedicated Xilinx® Aurora® link at a rate matching COMPASS's 500 μs slow control cycle. The implemented system systematically met the required latency specifications, being able to deliver an estimation of the plasma radial position capable of successfully replacing the corresponding magnetic measurements in the plasma position feedback control loops.

Power-Electronic-Based Electric Machine Emulator Using Direct Impedance Regulation

Power-electronics-based emulators have been showing promising prospects in advanced testing of various applications of power electronics systems. For electric machine applications, typical machine emulators calculate the references of stator current in response to terminal voltages via mathematical models of the machine system, and then, the current behaviors of emulators are regulated by using feedback controls. However, the dynamic and high-frequency performances of these machine emulators could be distorted by the introduced control loops, thus compromising the emulating performances. In this article, the limits of typical machine emulators are analyzed, and a new approach is proposed for the real-time emulation of permanent magnet synchronous machines (PMSM). A linear regulator without feedback control loop is proposed and designed to reshape the frequency-domain characteristics of the converter and current filter inside the emulation system. Compared with typical solutions, the proposed approach has frequency-domain characteristics closer to the target PMSM. The dynamic performances can be more accurately recreated, and the applicable frequency range for emulation can be extended. Simulations and experimental validations are also conducted to verify the effectiveness of the proposed approach.

Combination of cascade and feed-forward constrained control for stable partial nitritation with biomass retention

Ammonium removal is a key step in wastewater treatment which can be accomplished biologically. An interesting process option for this purpose is coupling partial nitritation with the Anammox process. The goal of the partial nitritation process is to convert half of the ammonium in the influent stream into nitrite, so both can be later converted into dinitrogen gas by the Anammox reaction. To obtain a stable partial nitritation, ammonium oxidizing bacteria (AOB) have to prevail over nitrite oxidizing bacteria (NOB) so as to avoid further conversion of nitrite into nitrate. The dissolved oxygen concentration is a key variable for the functional group selection. In this study, a constrained combination of cascade and feedforward control is proposed for reactors with biomass retention, aimed at suppressing unwanted NOB while keeping a nitrite:ammonium ratio suitable for coupling with Anammox. The master controller, aimed to regulate this effluent ratio, generates the set-point for the dissolved oxygen concentration slave controller. In addition to the cascade controller feedback loop, a feed-forward controller calculates the optimal dissolved oxygen concentration based on the current influent stream flow rate and concentrations. The resulting dissolved oxygen concentration set-point is compared to constraints that guarantee the suppression of NOB and survival of AOB. The proposed control strategy is simple to apply in common wastewater treatment plants with biomass retention. A sensitivity analysis is performed to assess the effect of model parameters uncertainty on the controller constraints and to determine which parameters need to be identified with more precision to avoid instability or poor results. The performance and the effect of the uncertainty of the most sensitive parameters on the proposed control algorithm are assessed through simulation using realistic streams as inputs of the process.

Data-driven design of fault-tolerant control systems based on recursive stable image representation

Driven by the increasing needs in the process industry for designing fault-tolerant control systems based on process data and maintaining its performance during online operation, data-driven realization and design of feed-forward fault-tolerant control systems with embedded residual generation are studied. To this end, a parameterized and data-driven realization form of stable image representation in a feedback control loop is derived first. On this basis, a feed-forward controller design scheme is proposed for fault-tolerant purpose. It is followed by a recursive approach for online tuning the feed-forward controller in case of malfunctions, which is triggered by a fault detection scheme based on the so-called stable kernel representation. The effectiveness of the proposed fault-tolerant method is demonstrated by a case study on the laboratory three-tank system.

Managing Wireless Communications for Emergency Situations in Urban Environments through Cyber-Physical Systems and 5G Technologies

Currently, urban environments are the basic human habitat. Large and complex infrastructures coordinate urban life and make it possible in high-density scenarios. In this context, one basic infrastructure to be considered is communication networks. Nowadays, even emergency response teams (ERT) are dependent on those deployments. However, emergencies may cause important damage in those communication infrastructures and, then, a critical discoordination among ERT might appear, greatly affecting the ERT efficiency and response capacity. Different architectures to address this situation have been recently proposed, but none of them are able to dynamically adapt to highly variable situations such as emergency crisis. Therefore, in this paper, a new approach is proposed for ad hoc emergency wireless communications in urban environments based on 5G technologies and Cyber-Physical Systems (CPS). The proposed architecture consists of three layers, where different feedback control loops are defined and linked following the CPS paradigm. At physical level, the spectrum usage is monitored through CPS control loops, analyzing if power signals present a good quality. At network level, 5G virtualization technologies are employed to manage in a dynamic way the network configuration and user management. Finally, at service level, the global situation is analyzed to decide about what services from a catalogue, and according to their priority, can be deployed, including the amount of assigned resources. To evaluate the performance of the proposed solution, an experimental validation based on simulation techniques is also described.

A method for inverting the Laplace transforms of two classes of rational transfer functions in control engineering

A dependable approach for inverting two classes of rational Laplace transforms, involving regular polynomials and partial sums with non-integer exponents is developed. Such types of Laplace transforms frequently emerge as the system transfer functions in the analysis of feedback control loops or process dynamics. The proposed method systematically translates the Laplace inversion problem into an integer or fractional order differential equation and yields the analytical inverse Laplace transform function utilizing the Adomian decomposition method. The method is especially useful in dealing with high-order rational transfer functions; where approaches based on the partial fraction expansion and the residue inversion theorem lose their practicality. The ready-to-use inversion formulas are presented and their usability and reliability is demonstrated through a number of case studies.

Coherent feedback induced transparency

We propose a light transparency effect induced by coherent feedback. By studying a system comprising a linear optical cavity controlled by a linear coherent feedback loop, we show that the optical signal field passing through the system cavity exhibits novel transparency behaviors. Unidirectional coupling between the system and its feedback control loop enables the group velocity and transmission rate to be tuned separately, thus maintaining the unity transmission rate when the group velocity is significantly suppressed. Furthermore, we demonstrate that simply applying a certain phase shift to the output of the system cavity and feeding it back into the system can induce perfect transmission. Our proposal offers a simple and effective way to control light transmission and group velocity using only linear optics elements.