Explore the vast range of titles available.

The time course of the center of pressure (CoP) during human quiet standing, corresponding to body sway, is a stochastic process, influenced by a variety of features of the underlying neuro‐musculo‐skeletal system, such as postural stability and flexibility. Due to complexity of the process, sway patterns have been characterized in an empirical way by a number of indices, such as sway size and mean sway velocity. Here, we describe a statistical approach with the aim of estimating “universal” indices, namely parameters that are independent of individual body characteristics and thus are not “hidden” by the presence of individual, daily, and circadian variations of sway; in this manner it is possible to characterize the common aspects of sway dynamics across healthy young adults, in the assumption that they might reflect underlying neural control during quiet standing. Such universal indices are identified by analyzing intra and inter‐subject variability of various indices, after sorting out individual‐specific indices that contribute to individual discriminations. It is shown that the universal indices characterize mainly slow components of sway, such as scaling exponents of power‐law behavior at a low‐frequency regime. On the other hand, most of the individual‐specific indices contributing to the individual discriminations exhibit significant correlation with body parameters, and they can be associated with fast oscillatory components of sway. These results are consistent with a mechanistic hypothesis claiming that the slow and the fast components of sway are associated, respectively, with neural control and biomechanics, supporting our assumption that the universal characteristics of postural sway might represent neural control strategies during quiet standing. The time course of the center of pressure (CoP) during human quiet standing, corresponding to body sway, is a stochastic process, influenced by a variety of features of the underlying neuro‐musculo‐skeletal system, such as postural stability and flexibility. Here, we describe a statistical approach with the aim of estimating “universal” indices, namely parameters that are independent of individual body characteristics and thus are not “hidden” by the presence of individual, daily, and circadian variations of sway, to characterize the common aspects of sway dynamics across healthy young adults in the assumption that they might reflect underlying neural control during quiet stance. It is shown that the universal indices characterize mainly slow components of sway, such as scaling exponents of power‐law behavior at a low‐frequency regime.

In this manuscript, time-triggered and event-triggered aperiodic intermittent controls are proposed for asymptotic stabilization of unstable discrete-time systems. The time-triggered aperiodic intermittent controls (T-APICs) are designed respectively by imposing conditions on the average dwell-time and the minimum of the active control width. For event-triggered aperiodic intermittent controls (E-APICs), when the norm of the state violates the defined inequality, the control is triggered. For one proposed E-APIC mechanism, it is demanded that the control length should be bigger than a given constant. Then for another E-APIC mechanism, we impose a condition related to the state on the control length. By relaxing the constraints on the control gain matrix, the third E-APIC mechanism is proposed. For these control plans, the control continuously updates during the active control time interval. Then we propose another E-APIC for asymptotic stabilization of the discussed discrete-time system by using the concept of input -to-state stability (ISS) and imposing the conditions on the norm of the state. In order to exemplify the effectiveness of the proposed aperiodic intermittent control mechanisms, asymptotic stabilizations of three examples are discussed by the proposed theorems.

Human postural sway during stance arises from coordinated multi-joint movements. Thus, a sway trajectory represented by a time-varying postural vector in the multiple-joint-angle-space tends to be constrained to a low-dimensional subspace. It has been proposed that the subspace corresponds to a manifold defined by a kinematic constraint, such that the position of the center of mass (CoM) of the whole body is constant in time, referred to as the kinematic uncontrolled manifold ( ). A control strategy related to this hypothesis ( ) claims that the central nervous system (CNS) aims to keep the posture close to the kinematic-UCM using a continuous feedback controller, leading to sway patterns that mostly occur within the kinematic-UCM, where no corrective control is exerted. An alternative strategy proposed by the authors ( ) claims that the CNS stabilizes posture by intermittently suspending the active feedback controller, in such a way to allow the CNS to exploit a stable manifold of the saddle-type upright equilibrium in the state-space of the system, referred to as the , when the state point is on or near the manifold. Although the mathematical definitions of the kinematic- and dynamic-UCM are completely different, both UCMs play similar roles in the stabilization of multi-joint upright posture. The purpose of this study was to compare the dynamic performance of the two control strategies. In particular, we considered a double-inverted-pendulum-model of postural control, and analyzed the two UCMs defined above. We first showed that the geometric configurations of the two UCMs are almost identical. We then investigated whether the UCM-component of experimental sway could be considered as passive dynamics with no active control, and showed that such UCM-component mainly consists of high frequency oscillations above 1 Hz, corresponding to anti-phase coordination between the ankle and hip. We also showed that this result can be better characterized by an eigenfrequency associated with the dynamic-UCM. In summary, our analysis highlights the close relationship between the two control strategies, namely their ability to simultaneously establish small CoM variations and postural stability, but also make it clear that the intermittent control hypothesis better explains the spectral characteristics of sway.

In this paper, we consider the finite-time stability (FIS) and fixed-time stability (FXS) problems for nonlinear systems by employing aperiodically intermittent control. Through the application of an iterative method, several general Lyapunov theorems, along with settling-time estimates of FIS and FXS, are established for aperiodically intermittent controlled nonlinear systems. Furthermore, aperiodically intermittent FIS and FXS control strategies are designed based on our theoretical findings. Additionally, when the uncontrolled time period approaches zero, the aperiodically intermittent controlled system transitions to a continuously controlled nonlinear system. Our results not only extend classical FIS and FXS findings for continuous controlled nonlinear systems but also generalize and enhance existing FIS and FXS results for aperiodically intermittent controlled nonlinear systems. The effectiveness of the proposed method is demonstrated through numerical examples.

This paper investigates the problem of pinning cluster synchronization for colored community networks via adaptive aperiodically intermittent control. Firstly, a general colored community network model is proposed, where the isolated nodes can interact through different kinds of connections in different communities and the interactions between different pair of communities can also be different, and moreover, the nodes in different communities can have different state dimensions. Then, an adaptive aperiodically intermittent control strategy combined with pinning scheme is developed to realize cluster synchronization of such colored community network. By introducing a novel piecewise continuous auxiliary function, some globally exponential cluster synchronization criteria are rigorously derived according to Lyapunov stability theory and piecewise analysis approach. Based on the derived criteria, a guideline to illustrate which nodes in each community should be preferentially pinned is given. It is noted that the adaptive intermittent pinning control is aperiodic, in which both control width and control period are allowed to be variable. Finally, a numerical example is provided to show the effectiveness of the theoretical results obtained.

This paper proposes a fixed-time distributed robust optimization approach for solving economic dispatch problems. Based on an integral sliding mode control scheme, the proposed multi-agent system converges to an optimal solution to an economic dispatch problem before a fixed time. In addition, the proposed multi-agent system can suppress the disturbance in a fixed time. To reduce the cost of sliding mode controls, we propose a distributed event-triggered intermittent control which reduces the sliding mode control time by setting a control triggering rule on the basis of two boundary functions of a Lyapunov function. The simulation results of three power systems illustrate the characteristics and effectiveness of the theoretical results.

In this paper, a new class of periodic self-triggered intermittent control with sampled-data (PSICS) is designed to tackle the stabilization issue for stochastic complex networks with time delays and Lévy noise (SCNTL). Therein, the self-triggered scheme is propounded with regard to intermittent control which is periodic judgment, and there exists a sampled-data control in every intervals of periodic judgment in the control time (work time) of intermittent control. It is worth pointing out that PSICS possesses more flexibility in terms of applications and simpler design of triggered conditions, compared with some previously reported control strategies such as the control combines the advantages of the periodic sampling and self-triggered control. Meanwhile, by means of stability analysis, sampled-data control, intermittent control and event-driven control theory, a useful criterion is established to guarantee the exponential stability in mean square of SCNTL. Notably, the stabilization issue of single-link robot arms with time delays and Lévy noise via PSICS is studied, as a practical application of SCNTL. Ultimately, numerical simulations are utilized for illustration.

This paper investigates the output scaled consensus problem for networked heterogeneous robotic systems (NHRSs) in the presence of aperiodically intermittent communication, time-varying transmission delays, and uncertain dynamic terms. Compared to those traditional results that study scaled consensus, this paper can provide the following advantages and novelty: (i) Due to the interdependence of multidimensional states among individuals in many practical scenarios, this paper is the first to discuss the scaled consensus of matrix-weighted NHRSs. (ii) In this paper, we consider the case where individuals are supposed to aperiodically communicate with each other at some disconnected time intervals, thus the proposed control algorithm guarantees that the output scaled consensus of NHRSs with aperiodically intermittent communication can be achieved. (iii) A novel hierarchical aperiodically intermittent control (HAIC) framework containing two layers is proposed, which allows the considered issue to be solved in two parts and facilitates the design of the control algorithm. Based upon the Lyapunov stability, input-to-state stable property, the nearest neighbor-interactions rules, several sufficient criteria for realizing output scaled consensus are established. Furthermore, the obtained theoretical results will be extended to the case of joint-space scaled consensus for networked robotic systems, which shows the versatility of the HAIC algorithm. Finally, numerical simulation examples are performed to validate the validity of the theoretical results provided.

Even in unperturbed upright standing of healthy young adults, body sway involves concurrent oscillations of the ankle and hip joints, thus suggesting to use biomechanical models with at least two degrees of freedom, namely a Double Inverted Pendulum (DIP) framework. However, in a previous study, it was demonstrated that the observed coordinated ankle-hip patterns do not necessarily require the independent active control of the two joints but can be explained by a simpler hybrid control system, with a single active component (intermittent, delayed sensory feedback of the ongoing sway) applied to the ankle joint and a passive component (stiffness control) applied to the hip joint. In particular, the proposed active component was based on the internal representation of a Virtual Inverted Pendulum (VIP) that links the ankle to the current position of the global Center of Mass (CoM). This hybrid control system, which can also be described as an ankle strategy, is consistent with the known kinematics of the DIP and, in particular, with the anti-phase correlation of the acceleration profiles of the two joints. The purpose of this study is to extend the hybrid control model in order to be applicable to both the ankle and hip strategy, clarifying as well the rationale of mixed strategies. The extension consists of applying the hybrid control scheme to both joints: a passive stiffness component and an active intermittent component, based on the same feedback signals derived from the common VIP but with independent parameter gains for the two joints. Thus, the hip gains are null in the pure ankle strategy, the ankle gains are null in the pure hip strategy, and both ankle and hip gains are specifically tuned in mixed strategies. The simulation of such an extended model shows that it can reproduce both strategies; moreover, the pure ankle strategy is more robust than the hip strategy, because the RoV (Range of Variation) of the intermittent control gains is larger in the former case than in the latter, and the pure ankle strategy is also more energy efficient.

This paper proposes an adaptive distributed hybrid control approach to investigate the output containment tracking problem of heterogeneous wide-area networks with intermittent communication. First, a clustered network is modeled for a wide-area scenario. An aperiodic intermittent communication mechanism is exerted on the clusters such that clusters only communicate through leaders. Second, in order to remove the assumption that each follower must know the system matrix of the leaders and achieve output containment, a distributed adaptive hybrid control strategy is proposed for each agent under the internal model and adaptive estimation mechanism. Third, sufficient conditions based on average dwell-time are provided for the output containment achievement using a Lyapunov function method, from which the exponential stability of the closed-loop system is analyzed. Finally, simulation results are presented to demonstrate the effectiveness of the proposed adaptive distributed intermittent control strategy.