Novel model reference adaptive control laws for improved transient dynamics and guaranteed saturation constraints

In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.     

Early manifestations of intellectual performance: Evidence that genetic effects on later academic test performance are mediated through verbal performance in early childhood

Intellectual performance is highly heritable and robustly predicts lifelong health and success but the earliest manifestations of genetic effects on this asset are not well understood. This study examined whether early executive function (EF) or verbal performance mediate genetic influences on subsequent intellectual performance, in 561 U.S.-based adoptees (57% male) and their birth and adoptive parents (70% and 92% White, 13% and 4% African American, 7% and 2% Latinx, respectively), administered measures in 2003–2017. Genetic influences on children's academic performance at 7 years were mediated by verbal performance at 4.5 years (β = .22, 95% CI [0.08, 0.35], p = .002) and not via EF, indicating that verbal performance is an early manifestation of genetic propensity for intellectual performance.     

Developmental trajectories of behavioral inhibition from infancy to age seven: The role of genetic and environmental risk for psychopathology

The present study leveraged data from a longitudinal adoption study of 361 families recruited between 2003 and 2010 in the United States. We investigated how psychopathology symptoms in birth parents (BP; M_age = 24.1 years; 50.5–62.9% completed high school) and adoptive parents (AP; M_age = 37.8 years; 80.9% completed college; 94% mother–father couples) influenced children's behavioral inhibition (BI) trajectories. We used latent growth models of observed BI at 18 and 27 months, and 4.5 and 7 years in a sample of adopted children (Female = 42%, White = 57%, Black = 11%, Multi-racial = 21%, Latinx = 9%). BI generally decreased over time, yet there was substantial variability in these trajectories. Neither BP nor AP psychopathology symptoms independently predicted systematic differences in BI trajectories. Instead, we found that AP internalizing symptoms moderated the effects of BP psychopathology on trajectories of BI, indicating a gene by environment interaction.     

Bridge21: teamwork,technology and learning. A pragmatic model for effective twenty-first-century team-based learning

There have been calls for decades by many educational writers and commentators for a new model of learning to facilitate what is generally described as twenty-first-century learning. Central to this challenge is the required shift in responsibility for who leads and owns the learning – from teacher to student. Such a shift requires a pragmatic pedagogical model to facilitate the transfer of control and ownership of learning. Vygotsky’s ‘more able other’ identified the peer as a key figure in learning. Teamwork facilitates project-based learning and, when mediated with technology, proves an effective partner in creating an engaging and autonomous learning experience. This paper describes the rationale for the design of a team-based model of twenty-first-century learning, particularly drawing upon the team-based learning model of the World Scout Movement. Results from a year-long study of the implementation of the model in an out-of-school context with 288 second-level students are presented. The authors argue that Bridge21 is a candidate learning model for effective, implementable, twenty-first-century, team-based learning.