Behavioral Systems Theory Research Articles

Bipedal Stepping Controller Design Considering Model Uncertainty: A Data-Driven Perspective.

This article introduces a novel perspective on designing a stepping controller for bipedal robots. Typically, designing a state-feedback controller to stabilize a bipedal robot to a periodic orbit of step-to-step (S2S) dynamics based on a reduced-order model (ROM) can achieve stable walking. However, the model discrepancies between the ROM and the full-order dynamic system are often ignored. We introduce the latest results from behavioral systems theory by directly constructing a robust stepping controller using input-state data collected during flat-ground walking with a nominal controller in the simulation. The model uncertainty discrepancies are equivalently represented as bounded noise and over-approximated by bounded energy ellipsoids. We conducted extensive walking experiments in a simulation on a 22-degrees-of-freedom small humanoid robot, verifying that it demonstrates superior robustness in handling uncertain loads, various sloped terrains, and push recovery compared to the nominal S2S controller.

Do fear-of-COVID-19 and regional identity matter for the linkage between perceived CSR and brand evangelism? A comparative analysis in South Asia

PurposeThere is a dearth of evidence on how and when perceived corporate social responsibility (PCSR) contributes to brand evangelism in the consumer behavioural literature, especially during a pandemic situation. In an attempt to examine this phenomenon, this study investigates the effect of fear-of-COVID-19 (Coronavirus disease 2019) and regional identity on PCSR and brand evangelism effect in the South Asian retail context. It theorises linkages mainly from behavioural inhabitation system theory and social identity theory.Design/methodology/approachA survey was administered to a representative sample of 2,242 retail consumers representing Sri Lanka, Bangladesh, Pakistan and India.FindingsThe results revealed a positive impact of PCSR on brand evangelism, but interestingly varying levels of strength of the key relationships based on country-wise fear-of-COVID-19 and regional identity during the pandemic.Practical implicationsFor the first time, the results of this research shed light on incorporating consumers’ regional identity as well as consumer fear as cultural predictors for better explaining the PCSR and brand evangelism link of nations within a region. This has implications for both theory and practice in the domain of consumer behaviour.Originality/valueThe study reflects its originality by revealing the relevance of country level social identity and negative emotions of nations that can manipulate the business results of corporate ethical responsiveness from a consumer culture theory perspective, especially during and just after a crisis. These results underlie what is active inside consumer black box by explaining as to what external stimuli drive consumer collective and moral mind set in a given culture. This adds to the body of knowledge on ethical consumption behaviour more specific to consumer–brand interaction in market crises.

Tolerating injustice when feeling in control: Personal control enhances the link between collectivism and coercion in the face of disease threats

Amid the COVID-19 pandemic, authorities worldwide imposed coercive regulations aimed at curbing the virus’s spread, often at the expense of individuals who were considered potential threats to public health. We argue that individual differences in their support for such actions can be understood from the perspective of an evolved “behavioral immune system”. We conducted two studies within the context of the “zero-COVID” policy in Mainland China. Study 1 recruited 819 Shanghai residents during a strict citywide lockdown and found that individuals’ collectivistic orientation and personal control over their lives predicted their tolerance of injustices involved in disease-control measures. Moreover, the effect of psychological collectivism was enhanced by personal control. Study 2 (N = 403) partly replicated these findings using hypothetical scenarios related to various fictitious viruses. Notably, the effects found in Study 1 only manifested in scenarios involving ambivalent pathogens, which are seldom fatal but highly contagious. Building on the functional flexibility principle of the behavioral immune system theory, we discussed the unique role of ambivalent pathogen signals in generating within-society variability and fine-tuning behavioral immune responses.

Robust data-driven predictive control for unknown linear time-invariant systems

This paper presents a new robust data-driven predictive control scheme for unknown linear time-invariant systems by using input–state–output or input–output data based on whether the state is measurable. To remove the need for the persistently exciting (PE) condition of a sufficiently high order on pre-collected data, a set containing all systems capable of generating such data is constructed. Then, at each time step, an upper bound on a given objective function is derived for all systems in the set, and a feedback controller is designed to minimize this bound. The optimal control gain at each time step is determined by solving a set of linear matrix inequalities. We prove that if the synthesis problem is feasible at the initial time step, it remains feasible for all future time steps. Unlike current data-driven predictive control schemes based on behavioral system theory, our approach requires less stringent conditions for the pre-collected data, facilitating easier implementation. The effectiveness of our proposed methods is demonstrated through application to an unknown and unstable batch reactor.

When pandemic threat does not stoke xenophobia: evidence from a panel survey around COVID-19

ABSTRACT Studies have found that pandemics can heighten xenophobia among host citizens, often explained by the behavioral immune system theory or elite-driven scapegoating. However, most research has overlooked the role of pandemic-related economic restrictions and job loss on sentiment toward immigrants. To isolate this economic mechanism, we examine the case of Venezuelan migrants in Colombia before and during COVID-19. Despite the Colombian government's severe economic lockdown, few politicians blamed Venezuelans for the pandemic. Thus, any economic impact on xenophobia should be evident. Using a panel experimental survey of 374 Colombians, supplemented with 550 new respondents at endline, we find no evidence that exposure to COVID-19 changed attitudes towards Venezuelans, even for those directly affected by the pandemic. Yet, those who did not lose their jobs viewed Venezuelan migration more positively at endline, providing support for the economic effects of pandemics.

Finances and Fights: How Military Members’ Financial Attitudes and Behaviors Are Linked to Romantic Relationship Processes and Outcomes

Grounded in the theory of planned behavior and family systems theory, this study examined the notion that financial attitudes are a driving force in financial management behaviors and healthy financial behaviors, in turn, have implications for couple relationship processes and outcomes. This study was based on the experiences of a sample of service members, who may be at elevated financial and relational risk given the transitional nature of military life (N= 255 U.S. service members). Evidence from a path model largely supported study hypotheses and suggested that financial attitudes were directly and indirectly associated with a range of relationship processes and outcomes via financial management behaviors. When service members reported positive attitudes toward financial management behaviors, they tended to engage in healthier financial behaviors, and healthier financial behaviors were related to salient relational factors, such as greater agreement on spending with partners, better relationship satisfaction, and greater relationship commitment.

The ‘Coronavirus Crisis’ and xenophobia in South Africa: How did the pandemic affect anti‐immigrant sentiment?

AbstractThe impact of the COVID‐19 pandemic on xenophobia in South Africa is little understood. The Behavioural Immune System (BIS) theory would predict that hostility towards immigrants increases during periods of heightened pathogen stress. This BIS‐hypothesis is tested against the relative strength of three other possible drivers of anti‐immigrant sentiment. These included anger at the national lockdown system, intertemporal relative deprivation, and racial transformation ideology. For these tests nationally representative data (N = 2996), gathered during the height of the ‘Omicron’ wave, were used. Multivariate analysis showed that COVID‐19 exposure was not associated with more negative sentiments towards immigrants. Fear‐based reactions to the Coronavirus were, in fact, correlated with pro‐immigrant attitudes. Intertemporal relative deprivation and transformation orientations were much better predictors of anti‐immigrant sentiment than pathogen stress. These findings raised questions about the applicability of the BIS‐hypothesis in the context of the Coronavirus and suggest new avenues of academic inquiry.

Data-driven adaptive predictive frequency control for power systems with unknown and time-varying inertia

This paper proposes a novel data-based adaptive predictive frequency control method for multi-area power systems with unknown and time-varying inertia. Firstly, a data-based representation is built and updated at each instant based on behavioural system theory by using historical input–output data, where a moving horizon estimation method is used to deal with the unknown time-varying inertia issue adaptively. Then, the optimal frequency control signal is computed by solving an optimization problem under the framework of data-based predictive control. Simulation results on a power system with three control areas demonstrate the effectiveness of the proposed method.

Balancing work and family when family is work: a reconceptualization of work–family integration, burnout and detachment in family business

PurposeBuilding from calls for greater interdisciplinary research in interpreting family business phenomena, we integrate research on work–family conflict, detachment and burnout from both organizational and family studies. Using the characteristic work–family integration of family business settings as a backdrop we develop theoretical arguments that emphasize the reconciliatory role of interdisciplinary perspectives to explain the ostensibly contradictory findings in extant research. The diminishing barriers separating work and life spheres occurring in most global industries illustrate the importance of conceiving the study of work–life phenomena through recursive, rather than linear, logics and emphasizing the relevance of family business research in providing a contextual foundation for interdisciplinary discussions.Design/methodology/approachThis theoretical paper integrates perspectives from the literatures on organizational behavior and family systems theory to form six propositions on the relationship between work–life integration and the antecedents and consequences of burnout and psychological detachment.FindingsThis paper explores the nuances that overlapping work and family roles might be a source of both harmony and discord in family firms. In doing so, our research contributes to the growing relationship between family systems theory and family business research, and creates the foundation for future empirical studies on the psychological dynamics that underlie work–family integration.Originality/valueThis research advances a novel perspective on the interactions between work–family integration and burnout and detachment, and does so by noting that the way the family business literature treats work–family integration may apply to any employee that experiences tension between these different spheres of their identity.

Money or health? The effect of pathogen avoidance motives and life history strategies on health‐economic trade‐offs during the COVID‐19 pandemic

AbstractThe COVID‐19 pandemic has caused governments and individuals to face important but difficult trade‐offs between health and the economy. How do individuals choose between health and economic outcomes during the pandemic? Based on the behavioural immune system (BIS) theory and the life history (LH) theory, the present study examined the effects of individual differences in pathogen disgust sensitivity and life history strategy on people's health‐economic trade‐offs during the COVID‐19 pandemic. Results of an online study (N = 300) showed that people with higher pathogen disgust sensitivity felt less sense of control during the pandemic, and therefore chose health‐related options over economic‐related options. In addition, the association between pathogen disgust sensitivity and health outcome preference only existed in people with relatively faster life history strategies. Further, people's health‐economic trade‐offs were not influenced by their current economic status. Findings have important implications for policymakers and the public to understand people's health‐economic choices during the pandemic.

Least Squares Projection Onto the Behavior for SISO LTI Models

We consider the least squares projection onto the behavior for linear time-invariant (LTI) single-input single-output (SISO) models, in which the observed input-output data are modified in a least squares (LS) sense by subtracting so-called misfits, so that the modified data satisfy a given linear dynamic relation. We show that the LS-criterion of the projection problem induces an orthogonal decomposition of the ambient data space and we characterize this decomposition by means of banded block-Toeplitz matrices, the elements of which are the coefficients of the difference equation describing the SISO LTI dynamics. We thereby generalize earlier results in the literature on autonomous LTI models to the more complicated SISO case. Additionally, we illustrate that the novel characterization is equivalent (up to a change of model representation) to results derived using (isometric) state-space representations in the literature on behavioral systems theory.

Looking beyond vaccines: Cultural tightness-looseness moderates the relationship between immunization coverage and disease prevention vigilance.

Advancements in vaccination technologies mitigate disease transmission risks but may inadvertently suppress the behavioral immune system, an evolved disease avoidance mechanism. Applying behavioral immune system theory and utilizing robust big data analytics, we examined associations between rising vaccination coverage and government policies, public mobility, and online information seeking regarding disease precautions. We tested whether cultural tightness-looseness moderates the relationship between mass immunization and disease prevention vigilance. Comprehensive time series analyses were conducted using American data (Study 1) and international data (Study 2), employing transfer function modeling, cross-correlation function analysis, and meta-regression analysis. Across both the US and global analyses, as vaccination rates rose over time, government COVID-19 restrictions significantly relaxed, community mobility increased, and online searches for prevention information declined. The relationship between higher vaccination rates and lower disease prevention vigilance was stronger in culturally looser contexts. Results provide initial evidence that mass immunization may be associated with attenuated sensitivity and enhanced flexibility of disease avoidance psychology and actions. However, cultural tightness-looseness significantly moderates this relationship, with tighter cultures displaying sustained vigilance amidst immunization upticks. These findings offer valuable perspectives to inform nuanced policymaking and public health strategies that balance prudent precautions against undue alarm when expanding vaccine coverage worldwide.

Integration of sexual and relational mental representations in autobiographical memories is associated with sexual well-being

Determinants of sexual well-being have often been identified as sexual and relational satisfaction, which both include a focus on partner relationship. Such a conceptualization excludes sexually active single individuals, while confusing sexual and relational satisfaction with sexual well-being as both determinant and outcome. In this research, we propose an intrapersonal perspective focused on cognitive sexual and relational mental representations as determinants of sexual well-being. Based on behavioral systems theory, we suggest that a high level of integration of sexual and relational mental representations should be associated with sexual well-being indicators, whereas a weaker level of integration should correspond to a lower level of sexual well-being. We developed a novel codification scheme to measure the cognitive integration of sexual and relational mental representations in narratives of sexual autobiographical memories. We examined its associations with sexual well-being indicators (satisfaction, passion, and sociosexuality). In a sample of 142 students, results showed that integration of sexual and relational representations in memories was positively associated with sexual satisfaction and harmonious passion, and negatively with obsessive passion and sociosexual desire. Results suggest that an integrated cognitive organization of sexual and relational mental representations in autobiographical memories can reflect a greater sexual well-being. Clinical implications are discussed.

Stability of forced higher-order continuous-time Lur'e systems: a behavioural input-output perspective

We consider a class of forced continuous-time Lur'e systems obtained by applying nonlinear feedback to a higher-order linear differential equation which defines an input-output system in the sense of behavioural systems theory. This linear system directly relates the input and output signals and does not involve any internal, latent or state variables. A stability theory subsuming results of circle criterion type is developed, including criteria for input-to-output stability and strong integral input-to-output stability, concepts which are very much reminiscent of input-to-state stability and strong integral input-to-state stability, respectively. The methods used in the paper combine ideas from the behavioural approach to systems and control, absolute stability theory and input-to-state stability theory.

Does Social Media Exposure Shape Consumer Response in the Form of Panic Buying?

This study took an effort to analyse the impact of social media exposure on the panic buying behaviour of people towards health and personal care products during COVID-19 times. The study also analyses the mediating role of anxiety between social media exposure and panic buying. This study attempts to explain the connection between social media exposure, anxiety, and panic buying using the social proof theory, the S–O–R model, and the behavioural inhibition system theory. The study includes a sample of 433 people. The data was collected from 24 items structured questionnaire distributed online. A total of 433 responses were collected online. The relationship between variables was analysed through structural equation modelling using Smart PLS-3. The results revealed that there is a direct effect of social media exposure on panic buying but when anxiety mediates the relationship between media and panic buying then a condition of partial mediation was observed. The result suggests that social media exposure directly affects panic buying among customers but it also affects generating anxiety among the customer. The study contributes by exploring the relationship between social media exposure, anxiety and panic buying. This study has a practical implication towards policymaking and the functioning of appropriate social media communication during an unstructured and disastrous situation.

Robust Stability Analysis of a Simple Data-Driven Model Predictive Control Approach

In this paper, we provide a theoretical analysis of closed-loop properties of a simple data-driven model predictive control (MPC) scheme. The formulation does not involve any terminal ingredients, thus allowing for a simple implementation without (potential) feasibility issues. The proposed approach relies on an implicit description of linear time-invariant systems based on behavioral systems theory, which only requires one input-output trajectory of an unknown system. For the nominal case with noise-free data, we prove that the data-driven MPC scheme ensures exponential stability for the closed loop if the prediction horizon is sufficiently long. Moreover, we analyze the robust data-driven MPC scheme for noisy output measurements for which we prove closed-loop practical exponential stability. The advantages of the presented approach are illustrated with a numerical example.

Effects of Ginger on Disgust, Sexual Arousal, and Sexual Engagement: A Placebo-Controlled Experiment

ABSTRACT Sexual problems are common complaints across countries and cultures, and behavioral immune system theory suggests disgust plays an essential role in sexual functioning. The current study investigated 1) if disgust induced by sexual body fluids would reduce sexual arousal, reduce the likelihood of sexual engagement, and enhance disgust toward subsequent erotic stimuli, and 2) if the administration of ginger would affect these reactions. We administered either ginger or placebo pills to a sample of 247 participants (M age = 21.59, SD = 2.52; 122 women) and asked them to complete either behavioral approach tasks with sexual body fluids or with neutral fluids. Next, participants viewed and responded to questions concerning erotic stimuli (nude and seminude pictures of opposite-sex models). As expected, the sexual body fluids tasks induced disgust. The elevated disgust induced by sexual body fluids tasks resulted in lower sexual arousal in women, whereas ginger consumption counteracted this inhibiting effect of disgust on sexual arousal. Disgust elicited by sexual body fluids also increased disgust toward the subsequent erotic stimuli. Ginger increased sexual arousal toward the erotic stimuli in both men and women who had completed the neutral fluids tasks. Findings provide further evidence of the role of disgust in sexual problems, and, importantly, that ginger may improve the sexual function of individuals via its sexual arousal-enhancing effect.

Bridging Direct and Indirect Data-Driven Control Formulations via Regularizations and Relaxations

In this article, we discuss connections between sequential system identification and control for linear time-invariant systems, often termed indirect data-driven control, as well as a contemporary direct data-driven control approach seeking an optimal decision compatible with recorded data assembled in a Hankel matrix and robustified through suitable regularizations. We formulate these two problems in the language of behavioral systems theory and parametric mathematical programs, and we bridge them through a multicriteria formulation trading off system identification and control objectives. We illustrate our results with two methods from subspace identification and control: namely, subspace predictive control and low-rank approximation, which constrain trajectories to be consistent with a nonparametric predictor derived from (respectively, the column span of) a data Hankel matrix. In both cases, we conclude that direct and regularized data-driven control can be derived as convex relaxation of the indirect approach, and the regularizations account for an implicit identification step. Our analysis further reveals a novel regularizer and a plausible hypothesis explaining the remarkable empirical performance of direct methods on nonlinear systems.

Behavioral theory for stochastic systems? A data-driven journey from Willems to Wiener and back again

The fundamental lemma by Jan C. Willems and co-workers is deeply rooted in behavioral systems theory and it has become one of the supporting pillars of the recent progress on data-driven control and system analysis. This tutorial-style paper combines recent insights into stochastic and descriptor-system formulations of the lemma to further extend and broaden the formal basis for behavioral theory of stochastic linear systems. We show that series expansions – in particular Polynomial Chaos Expansions (PCE) of L2-random variables, which date back to Norbert Wiener’s seminal work – enable equivalent behavioral characterizations of linear stochastic systems. Specifically, we prove that under mild assumptions the behavior of the dynamics of the L2-random variables is equivalent to the behavior of the dynamics of the series expansion coefficients and that it entails the behavior composed of sampled realization trajectories. We also illustrate the short-comings of the behavior associated to the time-evolution of the statistical moments. The paper culminates in the formulation of the stochastic fundamental lemma for linear time-invariant systems, which in turn enables numerically tractable formulations of data-driven stochastic optimal control combining Hankel matrices in realization data (i.e. in measurements) with PCE concepts.

An Online Adaptation Strategy for Direct Data-driven Control

The fundamental lemma from behavioral systems theory yields a data-driven non-parametric system representation that has shown great potential for the data-efficient control of unknown linear and weakly nonlinear systems, even in the presence of measurement noise. In this work, we strive to extend the applicability of this paradigm to more strongly nonlinear systems by updating the system representation during control. Unlike existing approaches, our method does not impose suitable excitation to the control inputs, but runs as an observer parallel to the controller. Whenever a rank condition is deemed to be fulfilled, the system representation is updated using newly available datapoints. In a reference tracking simulation of a two-link robotic arm, we showcase the performance of the proposed strategy in a predictive control framework.