Impaired online control in children with developmental coordination disorder reflects development immaturity

The present study aimed to clarify whether a reduced ability to correct movements in-flight observed in children with developmental coordination disorder (DCD) reflects a developmental immaturity or deviance from the typical trajectory. Eighteen children with DCD (8–12 years), 18 age-matched controls, and 12 younger controls (5–7 years) completed a double-step reaching task. Compared to older controls, children with DCD and younger controls showed similarly prolonged reaching when the target unexpectedly shifted at movement onset and were equally slow to correct their reaching trajectory. These results suggest that impaired online control in DCD reflects developmental immaturity, possibly implicating the parietal-cerebellar cortices.

Executive Systems Constrain the Flexibility of Online Control in Children During Goal-Directed Reaching

We examined the influence of inhibitory load on online motor control in children. A sample of 129 school children was tested: younger, mid-age, and older children. Online control was assessed using a double-step perturbation paradigm across three trail types: non-jump, jump, and anti-jump. Results show that mid-aged children were able to implement online adjustments to jump trials as quickly as older children, but their performance on anti-jump trials regressed toward younger children. This suggests that rapid unfolding of executive systems during middle childhood may constrain the flexibility with which online control can be implemented, particularly when inhibitory demands are imposed.

Coupling online control and inhibitory systems in children with developmental coordination disorder: goal-directed reaching

For children with Developmental Coordination Disorder (DCD), the real-time coupling between frontal executive function and online motor control has not been explored despite reported deficits in each domain. The aim of the present study was to investigate how children with DCD enlist online control under task constraints that compel the need for inhibitory control. A total of 129 school children were sampled from mainstream primary schools. Forty-two children who met research criteria for DCD were compared with 87 typically developing controls on a modified double-jump reaching task. Children within each skill group were divided into three age bands: younger (6-7 years), mid-aged (8-9), and older (10-12). Online control was compared between groups as a function of trial type (non-jump, jump, anti-jump). Overall, results showed that while movement times were similar between skill groups under simple task constraints (non-jump), on perturbation (or jump) trials the DCD group were significantly slower than controls and corrected trajectories later. Critically, the DCD group was further disadvantaged by anti-jump trials where inhibitory control was required; however, this effect reduced with age. While coupling online control and executive systems is not well developed in younger and mid-aged children, there is evidence of age-appropriate coupling in older children. Longitudinal data are needed to clarify this intriguing finding. The theoretical and applied implications of these results are discussed.

Reduced motor imagery efficiency is associated with online control difficulties in children with probable developmental coordination disorder

Recent evidence indicates that the ability to correct reaching movements in response to unexpected target changes (i.e., online control) is reduced in children with developmental coordination disorder (DCD). Recent computational modeling of human reaching suggests that these inefficiencies may result from difficulties generating and/or monitoring internal representations of movement. This study was the first to test this putative relationship empirically. We did so by investigating the degree to which the capacity to correct reaching mid-flight could be predicted by motor imagery (MI) proficiency in a sample of children with probable DCD (pDCD). Thirty-four children aged 8 to 12 years (17 children with pDCD and 17 age-matched controls) completed the hand rotation task, a well-validated measure of MI, and a double-step reaching task (DSRT), a protocol commonly adopted to infer one's capacity for correcting reaching online. As per previous research, children with pDCD demonstrated inefficiencies in their ability to generate internal action representations and correct their reaching online, demonstrated by inefficient hand rotation performance and slower correction to the reach trajectory following unexpected target perturbation during the DSRT compared to age-matched controls. Critically, hierarchical moderating regression demonstrated that even after general reaching ability was controlled for, MI efficiency was a significant predictor of reaching correction efficiency, a relationship that was constant across groups. Ours is the first study to provide direct pilot evidence in support of the view that a decreased capacity for online control of reaching typical of DCD may be associated with inefficiencies generating and/or using internal representations of action.

Online motor control in children with developmental coordination disorder: chronometric analysis of double-step reaching performance

Background
Although there are a number of plausible accounts to explain movement clumsiness in children [or developmental coordination disorder (DCD)], the cause(s) of the disorder remain(s) an issue of debate. One aspect of motor control that is particularly important to the fluid expression of skill is rapid online control (ROC). Data on DCD have been conflicting. While some recent work using double-step reaching suggests no difficulty in online control, others suggest deficits (e.g. based on sequential pointing). To help resolve this debate, we suggest two things: use of recent neuro-computational models as a framework for investigating motor control in DCD, and more rigorous investigation of double-step reaching. Our working assumption here is that ROC is only viable through the seamless integration of predictive (or forward) models of movement and feedback-based mechanisms.

Aim
The aim of this chronometric study was to explore ROC in children with DCD using a double-step reaching paradigm. We predicted slower online adjustments in DCD based on the argument that these children manifest a core difficulty in predictive control.

Methods
Participants were a group of 17 children with DCD and 27 typically developing children aged between 7 and 12 years. Visual targets were presented on a 17-inch LCD touch screen, inclined to an angle of 15° from horizontal. The children were instructed to press each target as it appeared as quickly and accurately as possible. For 80% of the trials, the central target location remained unchanged for the duration of the movement (non-jump trials), while for the remaining 20% of trials, the target jumped at movement onset to one of the two peripheral locations (jump trials). Reaction time (RT), movement time (MT) and reaching errors were recorded.

Results
For both groups, RT did not vary according to trial condition, while children with DCD were slower to initiate movement. Further, the MT of children with DCD was prolonged to a far greater extent on jump trials relative to controls, with a large effect size. As well, children with DCD committed significantly more errors, notably a reduced ability to inhibit central responses on jump trials.

Conclusion
Our findings help reconcile some disparate findings in the literature using similar tasks. The pattern of performance in children with DCD suggests impairment in the ability to make rapid online adjustments that are based on a predictive (or internal) model of the action. These results pave the way for future kinematic investigation.

Control of dynamical systems with temporal logic specifications

This thesis is motivated by safety-critical applications involving autonomous air, ground, and space vehicles carrying out complex tasks in uncertain and adversarial environments. We use temporal logic as a language to formally specify complex tasks and system properties. Temporal logic specifications generalize the classical notions of stability and reachability that are studied in the control and hybrid systems communities. Given a system model and a formal task specification, the goal is to automatically synthesize a control policy for the system that ensures that the system satisfies the specification. This thesis presents novel control policy synthesis algorithms for optimal and robust control of dynamical systems with temporal logic specifications. Furthermore, it introduces algorithms that are efficient and extend to high-dimensional dynamical systems.

The first contribution of this thesis is the generalization of a classical linear temporal logic (LTL) control synthesis approach to optimal and robust control. We show how we can extend automata-based synthesis techniques for discrete abstractions of dynamical systems to create optimal and robust controllers that are guaranteed to satisfy an LTL specification. Such optimal and robust controllers can be computed at little extra computational cost compared to computing a feasible controller.

The second contribution of this thesis addresses the scalability of control synthesis with LTL specifications. A major limitation of the standard automaton-based approach for control with LTL specifications is that the automaton might be doubly-exponential in the size of the LTL specification. We introduce a fragment of LTL for which one can compute feasible control policies in time polynomial in the size of the system and specification. Additionally, we show how to compute optimal control policies for a variety of cost functions, and identify interesting cases when this can be done in polynomial time. These techniques are particularly relevant for online control, as one can guarantee that a feasible solution can be found quickly, and then iteratively improve on the quality as time permits.

The final contribution of this thesis is a set of algorithms for computing feasible trajectories for high-dimensional, nonlinear systems with LTL specifications. These algorithms avoid a potentially computationally-expensive process of computing a discrete abstraction, and instead compute directly on the system's continuous state space. The first method uses an automaton representing the specification to directly encode a series of constrained-reachability subproblems, which can be solved in a modular fashion by using standard techniques. The second method encodes an LTL formula as mixed-integer linear programming constraints on the dynamical system. We demonstrate these approaches with numerical experiments on temporal logic motion planning problems with high-dimensional (10+ states) continuous systems.

A dedicated binding mechanism for the visual control of movement.

The human motor system is remarkably proficient in the online control of visually guided movements, adjusting to changes in the visual scene within 100 ms [1-3]. This is achieved through a set of highly automatic processes [4] translating visual information into representations suitable for motor control [5, 6]. For this to be accomplished, visual information pertaining to target and hand need to be identified and linked to the appropriate internal representations during the movement. Meanwhile, other visual information must be filtered out, which is especially demanding in visually cluttered natural environments. If selection of relevant sensory information for online control was achieved by visual attention, its limited capacity [7] would substantially constrain the efficiency of visuomotor feedback control. Here we demonstrate that both exogenously and endogenously cued attention facilitate the processing of visual target information [8], but not of visual hand information. Moreover, distracting visual information is more efficiently filtered out during the extraction of hand compared to target information. Our results therefore suggest the existence of a dedicated visuomotor binding mechanism that links the hand representation in visual and motor systems.

Does implicit motor imagery ability predict reaching correction efficiency? A test of recent models of human motor control

Neurocomputational models of reaching indicate that efficient purposive correction of movement midflight (e.g., online control) depends on one's ability to generate and monitor an accurate internal (neural) movement representation. In the first study to test this empirically, the authors investigated the relationship between healthy young adults’ implicit motor imagery performance and their capacity to correct their reaching trajectory. As expected, after controlling for general reaching speed, hierarchical regression demonstrated that imagery ability was a significant predictor of hand correction speed; that is, faster and more accurate imagery performance associated with faster corrections to reaching following target displacement at movement onset. They argue that these findings provide preliminary support for the view that a link exists between an individual's ability to represent movement mentally and correct movement online efficiently.

LOCAL DIGITAL CONTROL OF POWER ELECTRONIC CONVERTERS IN A DC MICROGRID BASED ON A-PRIORI DERIVATION OF SWITCHING SURFACES

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.

Automated symbolic and numeric procedure for manipulator rigid-body dynamic significance analysis and simplification

This paper describes an automated procedure for analysing the significance of each of the many terms in the equations of motion for a serial-link robot manipulator. Significance analysis provides insight into the rigid-body dynamic effects that are significant locally or globally in the manipulator's state space. Deleting those terms that do not contribute significantly to the total joint torque can greatly reduce the computational burden for online control, and a Monte-Carlo style simulation is used to investigate the errors thus introduced. The procedures described are a hybrid of symbolic and numeric techniques, and can be readily implemented using standard computer algebra packages.

MWCNT操作的动力学运动学建模研究

为实现MWCNT操作运动过程的视觉显示,本文建立了MWCNT的动力学模型,据此可推导出推动MWCNT所需施加力的大小,并根据探针的实际受力判断其能否运动;同时还建立了MWCNT的运动学模型,根据探针的实际位置可获得探针操作下MWCNT的新位置与姿态,并借助虚拟现实技术对视觉界面进行实时更新,实现了MWCNT运动过程的实时视觉显示。基于上述视觉显示,操作者可在线控制探针的作用位置与运动轨迹、以及施加在探针上作用力的大小与方向,实现对MWCNT操作过程及结果的在线控制。MWCNT的操作实验初步验证了该模型的有效性。

A comparison of real catching with catching using stereoscopic visual displays

To date, the usefulness of stereoscopic visual displays in research on manual interceptive actions has never been examined. In this study, we compared the catching movements of 8 right-handed participants (6 men, 2 women) in a real environment (with suspended balls swinging past the participant, requiring lateral hand movements for interception) with those in a situation in which similar virtual ball trajectories were displayed stereoscopically in a virtual reality system (Cave Automated Virtual Environment [CAVE]; Cruz-Neira, Sandin, DeFranti, Kenyon, & Hart, 1992) with the head fixated. Catching the virtual ball involved grasping a lightweight ball attached to the palm of the hand. The results showed that, compared to real catching, hand movements in the CAVE were (a) initiated later, (b) less accurate, (c) smoother, and (d) aimed more directly at the interception point. Although the latter 3 observations might be attributable to the delayed movement initiation observed in the CAVE, this delayed initiation might have resulted from the use of visual displays. This suggests that stereoscopic visual displays such as present in many virtual reality systems should be used circumspectly in the experimental study of catching and should be used only to address research questions requiring no detailed analysis of the information-based online control of the catching movements.