Control Theoretic Model Research Articles

Control theoretical models for visuomotor control explains brain activity during naturalistic driving

Control theoretical models for visuomotor control explains brain activity during naturalistic driving

Crime Hallmark Nexus Between Tourism Support and Destination: Empirical Standpoint of Social Control Theory

The focus of the study is on types of crime and their relationship with tourism destinations and tourism support among northern tourist areas. The main objective of the study was to shed light on the types of crime and their association with tourism destinations and tourism support with the framework of the social control theoretical model (inner and outer control). Face-to-face quantitative data was collected from (n=501) respondents. The study analyzed data with partial least squares structural equation modeling (PLS-SEM version 4). The path analysis showed that crimes against persons, property, and victimless crime significantly decreased tourism support. A similar phenomenon, such as crimes against person and property, decreased tourism destinations, and victimless crime was insignificant. Based on the study’s findings, the results concluded that types of crime have made unsuccessful tourism support and tourism destination in the northern region. The study put forward recommendations to policymakers that criminal activities should be controlled through crime control systems among different tourist destinations in northern areas.

Enhancing TCP via Hysteresis Switching: Theoretical Analysis and Empirical Evaluation

In this paper we study the relationship between the TCP packet loss cycle and the performance of time-sensitive traffic in data centers. Using real traffic measurements and analysis, we find that such loss cycles are not long enough to enable most partition-aggregate time-sensitive TCP applications to recover their packet losses via the TCP 3-dup ACKs mechanism. As a result, the Timeout (RTO) mechanism is frequently triggered, leading to the expansion of the flow completion times (FCT) of such applications by orders of magnitude. Hence, we seek an alternative method that does not change the virtual machines and that can effectively expand the loss cycle duration to enable short flows to finish their transfer without incurring the cost of the RTO. To this end, we propose a novel TCP-AQM mechanism that alternates between a slow constant bitrate (CBR) mode and a fast TCP rate via hysteresis switching to expand the loss cycle. We prove the stability of the proposed TCP-AQM via a control theoretic model, then evaluate its performance gains via small and large scale NS2 simulation and by real FPGA implementation of a prototype on the NetFPGA platform. The results show considerable improvements in FCT distribution and reduction of missed deadlines in simulation and real experiments.

A Control-Theoretic Model for Bidirectional Molecular Communication Systems

A Control-Theoretic Model for Bidirectional Molecular Communication Systems

Modeling driver steering behavior in restricted-preview boundary-avoidance tasks

In the design of human-like steering support systems, driver models are essential for matching the supporting automation's behavior to that of the human driver. However, current driver models are very limited in capturing the driver's adaptation to key task variables such as road width and visibility (i.e., ‘preview’ of the road ahead). This paper uses a recently proposed, novel control-theoretical model for centerline tracking to investigate driver steering in lane-keeping tasks with restricted and unrestricted preview, in an attempt to substantially extend this model's validity. Using data from a tailored driving simulator experiment, three driver control loops (feedforward, heading and position feedback) are separately quantified using system identification techniques. The results show that when preview is restricted, drivers use all of the remaining preview to anticipate the curves of the road ahead, and are no longer able to ‘smooth’ tight curves in the road trajectory (i.e., corner cutting). When sufficient preview and lane width are available, the time to line crossing increases, and steering behavior is less aggressive and more intermittent, or more ‘satisficing’. The novel driver steering model captures these adaptations very well (over 95% of the steering actions) and can thereby be instrumental in realizing human-like steering automation and support systems.

Identification of residual disease followed by trade-off analysis between drug optimisation, MRD and sustenance of normal haematopoiesis under maintenance chemotherapy in childhood ALL

ALL, an acute lymphoblastic leukaemia commonly occurring cancer in children, relapses in many cases. Hence to remove (minimal) residual leukaemia or disease (MRD), a maintenance chemotherapy schedule is conducted for two years after intensive chemotherapy. MRD detection occasionally fails due to mutability behaviour of leukemic cells or their aberrant marker expression and presence of MRD in very minor amount enhances the chances of disease relapse in long-term. Application of higher drug dose during maintenance phase could remove MRD but produces drug related toxicity. Bone marrow biopsy is required for MRD detection. Here, a peripheral blood-based control theoretic model is proposed to detect the presence of MRD. Moreover, the model-based eigenvalue and trade-off analysis could provide a guidance in clinical decision making to optimise the maintenance chemotherapeutic regime (both dose and duration) for individual ALL patients.

Prediction of Crash Risk based on Driving Behaviour

Abstract: The major interest which is increasing for many kinds of applications includes human driver’s characterisation. There are different promising approaches in order to characterise the drivers by means of control theoretic driver models. The driver state is monitored by applying features of driver model from survey till real road distraction experiment. The dataset for the experiment consists of driving behavior with visuomotor and even few secondary tasks like auditory and even driving reference. The individual estimation of model parameters uses data of driving of nearly eleven drivers for error prediction identification. Few hand gestures and head movements are gentle way of getting distracted by drivers which covers many states like eye closure either short or long term. This paper represents the distraction detection system with the help of attention strategy. By matching the scaled features, the transformation of frontal face of the driver, driver recognition can be made. The severity of accident zone is found in particular area based on dataset. Driver behavior at particular hotspot location is found which is considered as the accident hotspot in order to gain better accuracy. The results help in validation of robustness and effectiveness of the model. Th

Developmental maturation of causal signaling hubs in voluntary control of saccades and their functional controllability.

The ability to adaptively respond to behaviorally relevant cues in the environment, including voluntary control of automatic but inappropriate responses and deployment of a goal-relevant alternative response, undergoes significant maturation from childhood to adulthood. Importantly, the maturation of voluntary control processes influences the developmental trajectories of several key cognitive domains, including executive function and emotion regulation. Understanding the maturation of voluntary control is therefore of fundamental importance, but little is known about the underlying causal functional circuit mechanisms. Here, we use state-space and control-theoretic modeling to investigate the maturation of causal signaling mechanisms underlying voluntary control over saccades. We demonstrate that directed causal interactions in a canonical saccade network undergo significant maturation between childhood and adulthood. Crucially, we show that the frontal eye field (FEF) is an immature causal signaling hub in children during control over saccades. Using control-theoretic analysis, we then demonstrate that the saccade network is less controllable in children and that greater energy is required to drive FEF dynamics in children compared to adults. Our findings provide novel evidence that strengthening of causal signaling hubs and controllability of FEF are key mechanisms underlying age-related improvements in the ability to plan and execute voluntary control over saccades.

Management of High-Risk Atherosclerotic Patients by Statins May Be Supported by Logistic Model of Intima-Media Thickening.

While the use of statins in treating patients with atherosclerosis is an undisputed success, the questions regarding an optimal starting time for treatment and its strength remain open. We proposed in our earlier paper published in Int. J. Mol. Sci. (2019, 20) that the growth of intima-media thickness of the carotid artery follows an S-shape (i.e., logistic) curve. In our subsequent paper in PLoS ONE (2020, 15), we incorporated this feature into a logistic control-theoretic model of atherosclerosis progression and showed that some combinations of patient age and intima-media thickness are better suited than others to start treatment. In this study, we perform a new and comprehensive calibration of our logistic model using a recent clinical database. This allows us to propose a procedure for inferring an optimal age to start statin treatment for a particular group of patients. We argue that a decrease in the slope of the IMT logistic growth curve, induced by statin treatment, is most efficient where the curve is at its steepest, whereby the efficiency means lowering the future IMT levels. Using the procedure on an aggregate group of severely sick men, 38 years of age is observed to correlate with the steepest point of the logistic curve, and, thus, it is the preferred time to start statin treatment. We believe that detecting the logistic curve’s steepest fragment and commencing statin administration on that fragment are courses of action that agree with clinician intuition and may support decision-making processes.

Hexagonal fuzzy approximation of fuzzy numbers and its applications in MCDM

Numerous research papers and several engineering applications have proved that the fuzzy set theory is an intelligent effective tool to represent complex uncertain information. In fuzzy multi-criteria decision-making (fuzzy MCDM) methods, intelligent information system and fuzzy control-theoretic models, complex qualitative information are extracted from expert’s knowledge as linguistic variables and are modeled by linear/non-linear fuzzy numbers. In numerical computations and experiments, the information/data are fitted by nonlinear functions for better accuracy which may be little hard for further processing to apply in real-life problems. Hence, the study of non-linear fuzzy numbers through triangular and trapezoidal fuzzy numbers is very natural and various researchers have attempted to transform non-linear fuzzy numbers into piecewise linear functions of interval/triangular/trapezoidal in nature by different methods in the past years. But it is noted that the triangular/trapezoidal approximation of nonlinear fuzzy numbers has more loss of information. Therefore, there is a natural need for a better piecewise linear approximation of a given nonlinear fuzzy number without losing much information for better intelligent information modeling. On coincidence, a new notion of Generalized Hexagonal Fuzzy Number has been introduced and its applications on Multi-Criteria Decision-Making problem (MCDM) and Generalized Hexagonal Fully Fuzzy Linear System (GHXFFLS) of equations have been studied by Lakshmana et al. in 2020. Therefore, in this paper, approximation of nonlinear fuzzy numbers into the hexagonal fuzzy numbers which includes trapezoidal, triangular and interval fuzzy numbers as special cases of Hexagonal fuzzy numbers with less loss/gain of information than other existing methods is attempted. Since any fuzzy information is satisfied fully by its modal value/core of that concept, any approximation of that concept is expected to be preserved with same modal value/core. Therefore, in this paper, a stepwise procedure for approximating a non-linear fuzzy number into a new Hexagonal Fuzzy Number that preserves the core of the given fuzzy number is proposed using constrained nonlinear programming model and is illustrated numerically by considering a parabolic fuzzy number. Furthermore, the proposed method is compared for its efficiency on accuracy in terms of loss of information. Finally, some properties of the new hexagonal fuzzy approximation are studied and the applicability of the proposed method is illustrated through the Group MCDM problem using an index matrix (IM).

Embodied skillful performance: where the action is

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory (OMCT), as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed—a motor command. This paper aims to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference—behavioral modeling frameworks that descend, but are distinct, from OMCT—and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference.

Control-Theoretic Modeling and Prediction of Blood Clot Viscoelasticity in Trauma Patients

Control-Theoretic Modeling and Prediction of Blood Clot Viscoelasticity in Trauma Patients

Cancer detection through Electrical Impedance Tomography and optimal control theory: theoretical and computational analysis.

The Inverse Electrical Impedance Tomography (EIT) problem on recovering electrical conductivity tensor and potential in the body based on the measurement of the boundary voltages on the $ m $ electrodes for a given electrode current is analyzed. A PDE constrained optimal control framework in Besov space is developed, where the electrical conductivity tensor and boundary voltages are control parameters, and the cost functional is the norm difference of the boundary electrode current from the given current pattern and boundary electrode voltages from the measurements. The novelty of the control-theoretic model is its adaptation to the clinical situation when additional "voltage-to-current" measurements can increase the size of the input data from $ m $ up to $ m! $ while keeping the size of the unknown parameters fixed. The existence of the optimal control and Fréchet differentiability in the Besov space along with optimality condition is proved. Numerical analysis of the simulated model example in the 2D case demonstrates that by increasing the number of input boundary electrode currents from $ m $ to $ m^2 $ through additional "voltage-to-current" measurements the resolution of the electrical conductivity of the body identified via gradient method in Besov space framework is significantly improved.

The Synergy Between Neuroscience and Control Theory: The Nervous System as Inspiration for Hard Control Challenges

Here, we review the role of control theory in modeling neural control systems through a top-down analysis approach. Specifically, we examine the role of the brain and central nervous system as the controller in the organism, connected to but isolated from the rest of the animal through insulated interfaces. Though biological and engineering control systems operate on similar principles, they differ in several critical features, which makes drawing inspiration from biology for engineering controllers challenging but worthwhile. We also outline a procedure that the control theorist can use to draw inspiration from the biological controller: starting from the intact, behaving animal; designing experiments to deconstruct and model hierarchies of feedback; modifying feedback topologies; perturbing inputs and plant dynamics; using the resultant outputs to perform system identification; and tuning and validating the resultant control-theoretic model using specially engineered robophysical models.

The feasibility of Follow-the-Greens for 4-dimensional trajectory based airport ground movements

Safer and more efficient airport ground movements can be planned by routing and scheduling systems based on the 4-dimensional trajectory (4DT). In order to achieve the benefits envisioned in the planning stage, an effective taxiing guidance system is indispensable. The Follow-the-Greens (FtG) guidance concept provides an augmented means for 4DT based taxiing with pilot in the loop, which is expected to guide the piloted aircraft by dynamically adjusting the lit position of green ground navigation lamps according to the assigned 4DTs. This paper presents a simulation study to investigate the feasibility of FtG based on a control theoretic modeling of the taxiing system. The 4DT conformance errors with different navigation lamp control strategies are investigated. The key performance indices, including temporal constraint violation and fuel consumption, are analysed. The results demonstrate that it is feasible to follow conflict-free 4DTs through FtG if an appropriate lamp controller is available. The results also highlight the need to proactively handle the potential conformance errors in the routing and scheduling stage.

Case Study on the Neuropsychology of Hypersexual Behavior

The literature on hypersexual behavior following acquired brain injury consists of single or small case series with findings often difficult to reconcile, due to non-systematic, clinical descriptions of the behavior and its associated neurocognitive factors across authors. The objective of this study was to advance an understanding of the behavioral manifestations and neuropathology of acquired hypersexual behavior via literature review with an illustrative case study including pre- and post-onset neuropsychological test results. The case involved acquired hypersexual behavior with an increased ease of arousal manifested as constant verbal demands upon his wife, sexually explicit talk, and insatiable performance followed bithalamic strokes in a 44-year-old male. Neuropsychological testing showed a dense anterograde amnesia and less severe executive impairment. Co-occurring compulsive eating and anosognosia were also observed. The hypersexual behavior and compulsive eating were interpreted as resulting from a disconnection syndrome that separated mesiotemporal limbic structures from orbitofrontal control. It was not part of a generalized disinhibition, as the behaviors that showed a post-injury increase were highly specific. This is consistent with dual control theoretical models of human sexuality whereby the human sexual response involves an interaction between independent sexual excitatory and inhibitory processes. Many questions about acquired hypersexual behavior remain, especially why it so rarely occurs even in cases of bilateral orbitofrontal and temporal injury. A large-scale, multi-site, prospective study to measure prevalence within the overall context of acute frontotemporal injury, although practically difficult to organize, would be informative.

Frequency response analysis of inventory variation in production networks with information sharing

Previous discrete event simulation studies have found that information exchange can be beneficial to the various stakeholders in resource sharing networks. However, the fundamental dynamic behavior that produces these benefits has yet to be theoretically characterized and quantified. In this paper, frequency response analysis is used to predict the magnitude of inventory variations that result from different options for information sharing between and within entities in a production network. An example from the steel industry is used to illustrate how control theoretical models can be constructed and used to explain how variations in demand propagate through a production network.

Aircraft Ground Braking Assistant Control Based on Pilot Control Model

Aircraft ground braking control is a complex time-varying dynamic problem, especially when there are unexpected disturbances from lateral wind or visual error. Therefore, under some extreme conditions, it is hard for the pilot to control aircraft braking as well as usual without assistant control. This paper solves this problem by proposing a novel assistant control for aircraft ground braking, mainly based on the pilot control model and the LPV theory. And in order to reflect the control characteristics of the pilot, the sensory and control-theoretic model were combined together for controller designing. To test the performance of proposed control method, a real time pilot-in-loop simulation system is constructed. According to experiment results, the proposed assistant control shows better performance than pilot control, for it not only help the pilot to resist disturbance, but also hardly run counter to the pilot’s intent.

Control-Theoretic Models of Environmental Crime

We present two models of perpetrators' decision-making in extracting resources from a protected area. It is assumed that the authorities conduct surveillance to counter the extraction activities, a...

Visual-Olfactory Integration in the Human Disease Vector Mosquito Aedes aegypti

Mosquitoes rely on the integration of multiple sensory cues, including olfactory, visual, and thermal stimuli, to detect, identify, and locate their hosts [1-4]. Although we increasingly know more about the role of chemosensory behaviors in mediating mosquito-host interactions [1], the role of visual cues is comparatively less studied [3], and how the combination of olfactory and visual information is integrated in the mosquito brain remains unknown. In the present study, we used a tethered-flight light-emitting diode (LED) arena, which allowed for quantitative control over the stimuli, and a control theoretic model to show that CO2 modulates mosquito steering responses toward vertical bars. To gain insight into the neural basis of this olfactory and visual coupling, we conducted two-photon microscopy experiments in a new GCaMP6s-expressing mosquito line. Imaging revealed that neuropil regions within the lobula exhibited strong responses to objects, such as a bar, but showed little response to a large-field motion. Approximately 20% of the lobula neuropil we imaged were modulated when CO2 preceded the presentation of a moving bar. By contrast, responses in the antennal (olfactory) lobe were not modulated by visual stimuli presented before or after an olfactory stimulus. Together, our results suggest that asymmetric coupling between these sensory systems provides enhanced steering responses to discrete objects.