Behavior Of Controller Research Articles

Responsive Economic Model Predictive Control for Next-Generation Manufacturing

There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected conditions. Two types of unexpected conditions of relevance in the chemical process industries are anomalous conditions and the responses of operators and engineers to controller behavior. Enhancing responsiveness of an advanced control design known as economic model predictive control (EMPC) (which uses predictions of future process behavior to determine an economically optimal manner in which to operate a process) to unexpected conditions of these types would advance the move toward artificial intelligence properties for this controller beyond those which it has today and would provide new thoughts on interpretability and verification for the controller. This work provides theoretical studies which relate nonlinear systems considerations for EMPC to these higher-level concepts using two ideas for EMPC formulations motivated by specific situations related to self-modification of a control design after human perceptions of the process response are received and to controller handling of anomalies.

LVDC 배전망의 PV와 BESS 모델링과 제어기 설계

In this paper, the modeling and controller of PV and BESS, which are the core components of LVDC distribution network used for Gochang testbed, are designed and its performance is verified by simulation using PSCAD software. The simulation results show the modeling and dynamic behavior of PV and BESS system controllers. In LVDC distribution and DC microgrid, we think that this technology can be contributed not only based on customer practical use but also to the fault analysis, protection solution plan, and short circuit capacity calculation of DC circuit breaker.

Design-to-Test Approach for Programmable Controllers in Safety-Critical Automation Systems

This article presents a design-to-test (DTT) approach for enhancing black-box complete conformance testing of programmable controllers, where their specifications can be modeled as finite state machines. Given an automation system, the testing objective is to check whether its implemented controllers conform to the expected behavior with regard to the specification models. The DTT approach analyzes the specification models and, if necessary, automatically modifies them at the cost of limited design overhead, so that the testability of the final implemented controllers can be ensured/improved. By design, this approach also guarantees that the behavior of implemented controllers remains unchanged during normal execution (i.e., when not connected to a test bench).

Decentralised finite‐time consensus for second‐order multi‐agent system under event‐triggered strategy

In this technical note, the authors address the finite-time consensus problem of a second-order multi-agent system (SOMAS) under an event-triggered control strategy. This problem arises from the case where actuators in a SOMAS fail to follow the ideal controller behaviour exactly, due to either the failure of an embedded processor to maintain the desired update rate or a large time constant in the actuators, while still trying to maintain some performance merits from the finite-time control theory. A decentralised event-triggered non-linear protocol is proposed based on only local information for the undirected and connected communication graph. The rigorous proof is then presented and shows that the consensus can be achieved in finite time even under event-triggered schemes. Owing to the event-triggered strategy, they proposed a technique that bounds the steady errors of agent states into a small region around zero in finite time and reduces the update frequency of actuators while excluding the Zeno behaviour. Finally, simulation results are provided to validate the correctness and effectiveness of the proposed method and demonstrate that it can adjust a composed performance metrics with respect to the convergent rate, consensus accuracy, and update frequency of actuators by tuning the parameters in the control protocol.

Fabrication and Characterization of a Microfluidic Device with Vertically Aligned Multi Walled Carbon Nanotube Channels

Microfluidic devices are state of the art technology which are used for many applications especially as lab-on-chips. Manufacturing and characterization of these devices are reported in literature but process control aspects of vertically aligned multiwalled carbon nanotubes are rarely investigated. Furthermore, nano exchange capabilities with such structures are scarcely studied. In this paper, an industrial quality chemical vapor deposition system is designed, built and controlled. A nonlinear PI controller is employed to control the temperature of the chemical synthesis system, where precise temperature control is crucial. This controller behavior depends on the ratio between the error signal and the reference which enables the controller to act faster while avoiding overshoot. A microfluidic nanoexchanger device is manufactured, flow characteristics are modeled and its nanoexchange capability is tested and proven experimentally. These devices have many applications both in industry and biomedical field. One of the promising applications is building artificial organs such as lungs and kidneys where nanoexchanges occur naturally.

Development of coupling module between BHawC aeroelastic software and OrcaFlex for coupled dynamic analysis of floating wind turbines

Floating Offshore Wind Turbines (FOWTs) dynamic analysis can be quite challenging as it requires to model within the same calculation aerodynamics, hydrodynamics, controller, moorings and structure behaviour. Mooring and anchor design are strongly affecting FOWTs dynamic behaviour. Also, floater structural behaviour can be complex to model in a decoupled finite element analysis software. To do so, Innosea and Siemens Gamesa Renewable Energy developed a coupling between BHawC software and OrcaFlex software. BHawC is a nonlinear aeroelastic tool performing dynamic analysis of wind turbines. OrcaFlex is a generalist offshore marine engineering software that can perform the dynamic analysis of floaters and their mooring system. This paper describes the method and the mathematical background that is used to perform detailed time-domain simulations of a floating wind turbine coupling BHawC and OrcaFlex. The coupling is verified comparing time domain simulations on several load cases for rigid floaters coupled to a turbine with a rigid RNA. This shows a good agreement which confirms the correctness of the coupling.

Air Traffic Controller’s Behavior Recognition from Still Images by Transfer Learning

The fatigue problem of air traffic controllers is one of the important reasons that en-danger the safety of civil aviation. In this paper, we introduce behavior recognition into the field of fatigue monitoring of civil air traffic controllers. We investigate the method of automatic recognition of controller’s behaviors by using transfer learning and model fusion. The task of behavior recognition for controllers can be regarded as a multi-classification problem (Such as putting heads on desks for a nap, lay with face upward, nod to sleep, talking with others, directing planes normally, Hold up chin on left hand, writing notes on strips radio check, Resting hand on forehead ). Our study solve this problem from three aspects: (1) Set up a data set of controller behavior, including 18247 pictures of 10 actions; (2) Employ two-stream CNN(Resnet50,Inception V3) to extract different features; (3) We investigate different fusion strategy to improve the accuracy of action recognition of controllers. Experiments demonstrate that our method achieves a recognition accuracy of 94.2% and 93.7% on the CAFUC-Controller and Kaggle-Driving datasets.

Controlling the AP Controller: Controller Performance Assessment and Modification.

Despite recent advances in closed-loop control of blood glucose concentration (BGC) in people with type 1 diabetes (T1D), online performance assessment and modification of artificial pancreas (AP) control systems remain a challenge as the metabolic characteristics of users change over time. A controller performance assessment and modification system (CPAMS) analyzes the glucose concentration variations and controller behavior, and modifies the parameters of the control system used in the multivariable AP system. Various indices are defined to quantitatively evaluate the controller performance in real time. Controller performance assessment and modification system also incorporates online learning from historical data to anticipate impending disturbances and proactively counteract their effects. Using a multivariable simulation platform for T1D, the CPAMS is used to enhance the BGC regulation in people with T1D by means of automated insulin delivery with an adaptive learning predictive controller. Controller performance assessment and modification system increases the percentage of time in the target range (70-180) mg/dL by 52.3% without causing any hypoglycemia and hyperglycemia events. The results demonstrate a significant improvement in the multivariable AP controller performance by using CPAMS.

Fractional order sliding mode approach for chattering free direct power control of dc/ac converter

A control approach of sliding mode category is applied in this study for direct control of active and reactive power in a grid connected three-phase dc/ac converter. A fractional order sliding mode (FOSM) control is proposed to suppress chattering from power and current signals. The chattering reduction is achieved through fractional order mathematical modelling which has control over the fractional error tolerance and instantaneous error, while all attributes of conventional sliding mode remain intact. FOSM controller drastically reduces signal chattering that is a low order system noise in conventional sliding mode control (CSMC). The controller is designed using active–reactive power errors as input to get reference voltage vector under sliding mode fractional law. The controller uses stationary frame of reference and simplifies the design process in a manner to rule out extra proportional integral (PI)-controlled current loops. The FOSM reduces half of the switching losses as per the fractional reference to switching modulation. Lyapunov candidate function is investigated to prove stability of the proposed controller. Simulation and experiment are carried out to check chattering free response of the proposed controller as compared to CSMC. The transient behaviour and robustness of FOSM controller is investigated and compared to PI-based control.

Single-bit modulator for wireless power transfer system

<p>This paper proposes a single-bit ADC system based Proportional and Integral (PI) controller to maintain a desired level of power transfer efficiency in Capacitive Power Transfer (CPT) systems. In this paper, a simple single-bit ADC system i.e., Single-Bit Modulator (SBM) is considered as an alternative to the commonly used multi-bit ADC systems. Unique features of employing SBM are 1) its ability to convert analog signals into single-bit signals and 2) its easy integrability in digital chips with linear variable differential transformers (LVDTs) such as FPGAs. A SBM based PI (SBM-PI) controller is designed to judicially interface with the single-bit output of SBM. The proposed (SBM-PI) controller guarantees less hardware resources, latency and regulates the output voltage to provide the desired power transfer efficiency. The behavior of SBM-PI controller is compared to that of a conventional multi-bit controller, with the results of both controllers being identical. The effectiveness of the proposed controller with SBM is further demonstrated using the experimental prototype of CPT by implementing a SBM-PI controller using $16$ MHz ATmega8 microcontroller. The experimental results from a laboratory prototype illustrate that SBM-PI controller successfully regulates the output voltage of CPT to control the power flow.</p>

Behavior of a dual closed-loop controller of propofol and remifentanil guided by the bispectral index for postoperative sedation of adult cardiac surgery patients: a preliminary open study.

A dual-loop controller permits the automated titration of propofol and remifentanil during anesthesia; it has never been used in intensive care after cardiac surgery. The goal of this preliminary study was to determine the efficacy of this controller to provide postoperative sedation in 19 adult cardiac surgery patients with a Bispectral Index target of 50. Results are presented as numbers (percentages) or medians [25th-75th percentiles]. The sedation period lasted 139min [89-205] during which the Richmond Agitation Sedation Scale was at - 5 and the Behavioral Pain Scale score at three points for all patients and observation times but one (82 out of 83 assessments). Sedation time in the range 40-60 for the Bispectral Index was 87% [57-95]; one patient had a period of electrical silence defined as Suppression Ratio at least > 10% for more than 60s. The time between the end of infusions and tracheal extubation was 84min [63-129]. The Richmond Agitation Sedation Scale was 0 [0-0], 0 [- 1 to 0], and 0 [0-0] respectively during the 3h following extubation while the verbal numerical pain scores were 6 [4.5-7], 5 [4-6], and 2 [0-5]. Mean arterial pressure decreased during sedation requiring therapeutic interventions, mainly vascular filling in 15 (79%) patients. Automated sedation device was discontinued in two patients for hemodynamic instability. No patient had awareness of the postoperative sedation period. Dual closed-loop can provide postoperative sedation after cardiac surgery but the choice of the depth of sedation should take into account the risk of hypotension.

Continuous provision of synthetic inertia with wind turbines: implications for the wind turbine and for the grid

In future power systems with little system inertia, grid operators will require the provision of synthetic inertia (SI) from renewable energy sources. Unlike today, grid operators may require continuous provision of SI. This can lead to an unwanted disconnection of wind turbine generators (WTGs) from the grid, and has the potential to cause a significant decrease of the energy yield and financial losses for the turbine operator. In order to avoid such situations a controller is proposed, which interprets the grid codes to the benefit of all parties involved. This can be achieved by a variable inertia constant, which changes with the operating point of the WTG. In this study, the behaviour of the variable inertia constant controller is described, assessed and verified with time domain simulations.

SPERT: A Speed Limit Strategy for Recurrent Traffic Jams

This paper proposes and simulates a speed limit controller for recurrent traffic jams (SPERT). SPERT is a simple yet efficient variable speed limit (VSL) control strategy based on the behavior of the optimal controller without any need for online optimization. The online implementation of SPERT is a simple rule-based controller that activates and deactivates the corresponding variable speed limit when the densities of the dominant bottlenecks (which are found offline) reach predefined thresholds. These thresholds are defined in order to activate and deactivate the speed limits at the same bottleneck density at which they would be activated or deactivated in the nominal case. The simulation results show that SPERT is able to approach the optimal behavior while eliminating online computational cost, increasing robustness, and outperforming previously proposed easy-to-implement VSL control algorithms.

Dynamically Weighted Optimal Switching Vector Model Predictive Control of Power Converters

In this paper, new techniques are presented to improve the performance of the optimal switching vector model predictive control. A well-defined analytic technique is proposed for the real-time adjustment of dynamic weighting factors, as well as a new objective function formulation. These techniques provide a dynamic controller behavior, automatically adapted to distinct operating points. This ensures better steady-state performance in different conditions while improving simultaneously the dynamic response. The proposed controller presents a lower computational load than the conventional formulation and its design requires less extensive testing. General guidelines are presented to guide the user in the controller design. Simulation and experimental results are presented, demonstrating the advantages and superior performance of the proposed controller.

Hardware-in-the-loop simulation of trajectory following control for a light armoured vehicle optimised with particle swarm optimisation

Naturally, the unmanned armoured vehicle is important in military missions and to minimise the casualty of military personnel. Steering control is one of the most important aspects of unmanned vehicles. Therefore, in this research, a trajectory following control from Stanley autonomous vehicle is employed and optimised for a light armoured vehicle (LAV) to follow a pre-defined trajectory. The proposed controller is developed on a validated armoured vehicle model which consists of a 7-degree-of-freedom handling model and other vehicle interactions. To study the controller's behaviour with respect to each parameter, the sensitivity analysis was carried out. The controller is then optimised using particle swarm optimisation (PSO) algorithm and then tested on a physical Pitman arm steering actuator system through hardware-in-the-loop (HiL) simulation. It was shown that the PSO-tuned Stanley controller is able to automatically steer the vehicle to follow the pre-defined path with an average lateral cross-track error of 0.26 m.

Design and Application of a Database-Driven PID Controller based on Sparse Modeling

This paper considers a group method of data handling based PID (GMDH-PID) controller using LASSO that is one of the sparse modeling methods. A database-driven PID (DD-PID) controller is one of the effective nonlinear PID controller design methods. However, some electrical control units in industrial systems cannot implement its algorithm because the DD-PID control scheme requires a large amount of memory capacity and high-performance processor. In this paper, a GMDH-PID controller that approximately expresses the behavior of the DD-PID controller by combinations of simple nonlinear functions is proposed to solve the above problem. The proposed method employs LASSO as a coefficient calculation method of the GMDH in which some coefficients can be calculated as zero in order to avoid the influence of the multicollinearity. The usefulness of the proposed method is evaluated by an experimental result of a helicopter model.

Study of the Intelligent Behavior of a Maximum Photovoltaic Energy Tracking Fuzzy Controller

The Maximum Power Point Tracking (MPPT) strategy is commonly used to maximize the produced power from photovoltaic generators. In this paper, we proposed a control method with a fuzzy logic approach that offers significantly high performance to get a maximum power output tracking, which entails a maximum speed of power achievement, a good stability, and a high robustness. We use a fuzzy controller, which is based on a special choice of a combination of inputs and outputs. The choice of inputs and outputs, as well as fuzzy rules, was based on the principles of mathematical analysis of the derived functions (slope) for the purpose of finding the optimum. Also, we have proved that we can achieve the best results and answers from the system photovoltaic (PV) with the simplest fuzzy model possible by using only 3 sets of linguistic variables to decompose the membership functions of the inputs and outputs of the fuzzy controller. We compare this powerful controller with conventional perturb and observe (P&O) controllers. Then, we make use of a Matlab-Simulink® model to simulate the behavior of the PV generator and power converter, voltage, and current, using both the P&O and our fuzzy logic-based controller. Relative performances are analyzed and compared under different scenarios for fixed or varied climatic conditions.

Improved linearised models of wind turbine aerodynamics and control system dynamics using harmonic linearisation

Where non-linearities are not too strong, linearised frequency-domain approaches offer fast calculations, which can be valuable for preliminary design of wind turbine blades, foundations and floating platforms. But the aerodynamic and control system behaviour of a wind turbine is noticeably non-linear. Here we show for the first time that the technique of harmonic linearisation can reduce error in the approximation of aerodynamic and control system non-linearities, compared to the more common tangent linearisation. After deriving the linearised models, comparing linearised results to non-linear simulations for the NREL 5 MW turbine shows that: (1) harmonic linearisation captures aero-elastic effects and non-linearity in aerodynamic forces, giving a 2–4x reduction in error compared to the tangent linearisation; (2) harmonic linearisation can capture non-linear wake dynamics; and (3) the torque and pitch controller behaviour can be approximated with good results away from the rated wind speed but with some challenges when the two controllers interact. Further improvements in the linearised model of the control system have been identified. By improving the accuracy of linearised models, harmonic linearisation is a promising means to extend the applicability of frequency-domain approaches for initial design and optimisation of wind turbines.

Optimal Design of a Stable Fuzzy Controller for Beyond Pull-In Stabilization of Electrostatically Actuated Circular Microplates

The current paper aims to provide an optimal stable fuzzy controller to extend the travel range of a pair of flexible electrostatically actuated circular microplates beyond their pull-in limit. The single mode assumption is utilized to derive the equation of motion of the system based on a Lagrangian approach. The static behavior of the system is studied using the proposed model, and the utilized assumption and the relevant results are closely verified by nonlinear finite element simulations. The open-loop dynamic analysis is also performed to derive the linguistic rules governing the voltage-deflection behavior of the system. The mentioned rules are then employed for designing a fuzzy controller, which controls the deflection of the microplates. The controller is then optimized to provide better response specifications. The performance of the optimal fuzzy controller is compared with that of the optimal proportional–integral–derivative (PID) controller and obvious superiorities in terms of noise suppression and stability enhancement are observed. To guarantee the stability of the closed-loop system, another higher level controller is designed to oversee the behavior of the fuzzy controller. Simulation results reveal that the superintended fuzzy controller can prevent instability, while fairly extending the travel range of system and providing it with a better transient response. The suggested design approach proposed in this paper may be used to improve the performance of many nano/micro devices and nano/micro positioning systems.

Small-Signal Stability Analysis of an Inverter-Based Microgrid With Internal Model-Based Controllers

Several microgrid control strategies are proposed and studied in the literature. However, there are still gaps in improving their transient behavior and studying their stability. This paper uses small-signal analysis to explore the behavior of internal model-based current and voltage controllers by deriving a state-space model and performing eigenvalue and sensitivity analysis on an islanded inverter-based microgrid system. The results are compared with those of the same microgrid but with PI-based current and voltage controllers. Simulation case studies are performed in the PSCAD/EMTDC environment to compare the transient behavior of both methods. Results show that internal model-based controllers have superior eigenvalue patterns that lead to increased stability and improved transient behavior.