Owing to high compliance, adaptiveness, and easy controllability, soft actuators are widely adopted in soft grippers to grasp irregularly shaped or fragile objects. The specific motions can be preprogrammed into the flexible and constrained structures of the actuator, which provides an inexpensive and convenient method for desired motions. However, most preprogrammed structures cannot change the constraints on the actuator to achieve different kinds of deformations, which limits the motion diversities of actuators. This article proposes a scaffold reinforcement mechanism, where rotatable scaffolds distribute on the surface of the soft structure. The orientation adjustments of the scaffolds can change the deformation constraint of the actuator, which results in different kinds of motions. Based on the scaffold reinforcement mechanism, a scaffold-reinforced actuator is proposed, which can achieve bending motion and complex helical motion in the 3-D space by properly adjusting the orientation of the scaffolds. In addition, both the kinematic and mechanical models are proposed to forecast the behavior of the actuator when driven by cable displacement or tension force. Experimental results verify the validity of the theoretical model, and the actuator can achieve an independent control of bending and helical motion, which can be adopted in applications where both high dexterity and flexibility are required.

Cooperative sweep coverage of multiagent systems (MASs) has found broad applications in various fields. This article proposes a scheme to address the sweep coverage problem of MASs within uncertain environments. In the proposed formulation, the coverage region is divided into multiple stripes, of which each has the workload completed by MASs in sequence. When the workload on the current stripe is completed, all the agents switch to the next together. The temporal dependence between the switching time computation and the sweep coverage operation is taken into account, and an online learning strategy is designed to handle environmental uncertainties and balance the workload among agents on the same stripe. Thereby, the distributed sweep coverage algorithm is developed to guarantee the complete sweep coverage, which consists of three operations, i.e., communication, workload partition, and sweeping. Theoretical analysis is afterward conducted to estimate the upper bound for the error between the actual and optimal coverage time. Finally, numerical simulations are carried out to substantiate the effectiveness and superiority of the proposed scheme.

Soft continuum robots have many applications such as medical surgeries, service industries, rescue tasks, and underwater exploration. Flexibility and good accessibility of such robots are the key reasons for their popularity. However, the complexity of their structural design and control systems limit their broader applications. In this paper, a novel variable stiffness soft continuum robot based on pre-charged air, particle jamming, and origami is proposed. The robot is a bellow-like origami structure with internal chambers. A spine-like chamber is filled with particles, and three identical chambers surrounding the spine chamber are filled with pressurized air. When the origami structure is compressed, the particles are jammed by the compression force and the increased pressure of the three air chambers, thus increasing the overall stiffness of the robot. The robot expansion-contraction and bending are controlled by three tendons. An analytical model of the proposed stiffness variation mechanism has been developed. The effects of various parameters on the lateral and axial stiffness of the soft continuum robot have been investigated by experimental studies. A prototype robot has been fabricated to demonstrate grasping operations.

In this paper, the global pinning synchronization problem is studied for a complex dynamical network to follow a dynamic target system. A distinguished feature of the present network model is that the target system may have some predesigned control inputs. This implies that, when pinning synchronization is guaranteed, the states of the nodes within such a pinning-controlled dynamical network may approach a specified trajectory which does not satisfy the system equation of the uncoupling individual node system within the network. The practical constraint that the external control inputs acting on the target system are unknown to any node in the considered network poses a big challenge in solving such a pinning synchronization problem. The designed scheme for achieving pinning synchronization is executed in two steps. Specifically, the first step is to select some nodes to pin such that the augmented interaction topology has at least one directed spanning tree rooted at the node describing the target system, while the second step is to construct a coupling law to synchronize all the states of nodes within the network. Moreover, two kinds of discontinuous coupling laws with static and adaptive coupling gains are, respectively, proposed to achieve pinning synchronization. Meanwhile, by utilizing nonsingular ${M}$ -matrix theory and Lyapunov stability analysis for nonsmooth system, some efficient criteria are established for guaranteeing synchronization in the pinning-controlled networks. Numerical simulations on pinning synchronization of networking Chua's circuit systems are finally given to verify the analytic results.

This paper investigates the joint effect of quantization, sampled data, and general Markovian interaction links on consensus networks with a leader under directed graphs. The diversity of edges formed by all the followers and the leader is also considered. Each agent in the network possesses continuous-time general linear dynamics. Each agent's state is measured only at sampling time instants, which is encoded before transmission. Subsequently, the encoded state is transmitted through noiseless digital communication links with Markovian switching rates. For this problem, a sufficient condition is derived to guarantee the convergence of the encoded states, based on which a necessary and sufficient condition is obtained to achieve consensus tracking in the mean-square sense. In addition, two sufficient conditions on coupling gain, one of which is fully distributed, are provided by proposing an optimal linear quadratic regulator-based gain matrix to ensure consensus tracking and then, the analysis of consensus region is presented. Finally, a numerical example is presented for illustrating the effectiveness of the theoretical results.

The semi-global output consensus problem for multiagent systems depicted by discrete-time dynamics subject to external disturbances and input saturation over switching networks is investigated in this paper. Assume that only a small part of subsystems have directly received the output of the exosystem. The distributed consensus algorithms are proposed by adopting the low-gain state feedback and the modified algebraic Riccati equation. Then, the outputs of all subsystems can reach synchronization asymptotically with those of the exosystem by using the proposed consensus protocols on some preconditions. Both the connected switching networks and the jointly connected switching networks are considered for the semi-global output consensus problem, respectively. Some numerical simulation results are shown to validate the theoretical analysis.

An increasing number of cities are implementing bicycle sharing systems to reduce traffic congestion. Determining the locations of bicycle stations is one of the fundamental challenges in planning of such systems. This paper provides a novel solution on it. The min-plus algebra is introduced to model transport systems for accessibility analysis. A unified model in the sense of the min-plus algebra for an integrated system with both buses and bicycles is presented to dynamically describe the state transitions of passengers in the system. A new accessibility is proposed with regards to a general index ω such as the geographical distance and the travel time. A necessary and sufficient condition on the accessibility is then provided. The minimization of bicycle stations under the accessibility is formulated to be a 0-1 integer programming problem. The case studies on two cities, Ningbo and Hangzhou, were performed, which show that compared with the current layouts of urban transportation networks, the proposed public bicycle sharing systems have remarkable advantages in topological characteristics and robustness against failures.

This paper is devoted to solving the output consensus problem of leader-follower higher-order nonlinear multiagent systems subject to mismatched disturbances. The disturbances are allowed to be in higher-order forms. First, by constructing a generalized proportional-integral observer for each follower, estimates of the disturbances and their derivatives are obtained. At the same time, a distributed observer is also developed for the followers to estimate the leader state information. Second, based on the estimates of the disturbances and the leader state, together with the backstepping technique, a feedforward-feedback composite consensus control scheme is proposed. The designed distributed protocols guarantee asymptotic output consensus for the agents. Simulation results validate the effectiveness of the proposed composite control scheme.

In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.

This paper addresses the robust semiglobal coordinated control of multiple-input multiple-output multiagent systems with input saturation together with dead zone and input additive disturbance. Observer-based coordinated control protocol is constructed, by combining the parameterized low-and-high-gain feedback technique and the high-gain observer design approach. It is shown that, under some mild assumptions on agents' intrinsic dynamics, the robust semiglobal consensus or robust semiglobal swarm can be approached for undirected connected multiagent systems. Then, specific guidelines on the selection of the low-gain parameter, the high-gain parameter, and the high-gain observer gain have been provided. At last, numerical simulations are presented to illustrate the theoretical results.

This paper considers the nonfragile $H_\infty $ estimation problem for a class of complex networks with switching topologies and quantization effects. The network architecture is assumed to be dynamic and evolves with time according to a random process subject to a sojourn probability. The coupled signal is to be quantized before transmission due to power and bandwidth constraints, and the quantization errors are transformed into sector-bounded uncertainties. The concept of nonfragility is introduced by inserting randomly occurred uncertainties into the estimator parameters to cope with the unavoidable small gain variations emerging from the implementations of estimators. Both the quantizers and the estimators have several operation modes depending on the switching signal of the underlying network structure. A sufficient condition is provided via a linear matrix inequality approach to ensure the estimation error dynamic to be stochastically stable in the absence of external disturbances, and the $H_\infty $ performance with a prescribed index is also satisfied. Finally, a numerical example is presented to clarify the validity of the proposed method.

This paper investigates the local consensus issue for multiagent systems with nonlinear dynamics and time-varying delays. By defining a weighted average state of the agents and applying local linearization, we show that the local consensus of the agents in a directed communication network can be guaranteed by the asymptotic stability of several decoupled delayed systems. Then, by employing a novel Lyapunov-Krasovskii functional, proposing a new extended reciprocally convex approach and using some matrix analysis, we derive a sufficient condition for the local consensus in terms of linear matrix inequalities associated with the dynamics of the agents, the eigenvalues of Laplacian matrix, and the time-varying delay. Finally, two numerical examples are provided to show the effectiveness of the analytical results.

This paper focuses on addressing the consensus problem of edges for both undirected and directed nodal networks whose edges are described by nominal or uncertain positive linear systems. The definition of line graph is given, and the similar properties and connections between the two types of graphs are established. Based on the rigorous theoretical analysis, distributed positive consensus algorithms are proposed, and the main results are given without utilizing the global interaction information. Subsequently, sufficient conditions for consensus with positivity constraint are given via the vertex number and the edge number of the original nodal network. Furthermore, according to the properties of Metzler matrix, we also solve the consensus problem for multiple edges which are modeled by uncertain positive systems. Some simulation studies are finally presented to verify the feasibility and effectiveness of the proposed results.

Current research interests for humanoid robots include cost, static stability, and human-likeness. With the help of well-developed locomotion controllers, human-like gait has been realized on humanoid robots with higher energy efficiency and increased motion speed. However, such results are based on the walking function of bipedal robots, running function has been less touched or investigated. Different from walking, running could cause more injuries when human cope with the impact from the ground. In this paper, we define a new foot strike pattern that describes the instinctive human running manner and the performance of a group of adults is collected and analysed for comparison of different foot strike patterns. This helps with lower limbs' injury prevention by proving that most of the impact transient is reduced in the new foot strike pattern for both the shod and the barefoot conditions. Therefore, the newly defined foot strike pattern can be considered as an alternative option to reduce the injury of running activities. Furthermore, it would be possible to apply the foot strike pattern mechanism in humanoid robots, not only to extend the service life from the collision and vibration damage of the components, but also to make robots more human-like.

The problem of leader-following consensus of nonlinear agents in hybrid varying directed topology is considering not only the agent but also that the directed edges can have a time-varying nonlinear dynamics with jump discontinuity, which contains the switching topology as its special case. This paper has the following contributions toward this problem. The leader-following consensus problem in hybrid varying directed topology is first addressed, and an online leader switching method is proposed, which reduces the dependence on some global conditions and the connectivity assumptions on the selection of leaders. Second, we generalize the Lipschitz condition and the combined condition of one-sided Lipschitz and quadratically inner-boundedness conditions to a new generalized linear incremental condition, which gives us a more generalized result in the Lyapunov proof and better performance in simulation. Third, an observer-based consensus protocol is constructed with two sufficient observability and controllability conditions and two optimal control design algorithms. Finally, an example of teleoperating multirobotic manipulator joint network is provided to illustrate the performance improvement by comparing with the existing results.

This paper establishes several bounds on the algebraic connectivity and spectral radius of graphs. Before deriving these bounds, a directed graph with a leader node is first investigated, for which some bounds on the spectral radius and the smallest real part of all the eigenvalues of M = L + D are obtained using the properties of M-matrix and non-negative matrix under a mild assumption, where L is the Laplacian matrix of the graph and D = diag{d1, d2, ..., dN} with di > 0 if node i can access the information of the leader node and 0 otherwise. Subsequently, by virtue of the results on directed graphs, the bounds on the algebraic connectivity and spectral radius of an undirected connected graph are provided. Besides establishing these bounds, another important feature is that all these bounds are distributed in the sense of only knowing the information of edge weights' bounds and the number of nodes in a graph, without using any information of inherent structures of the graph. Therefore, these bounds can be in some sense applied to agent networks for reducing the conservatism where control gains in control protocols depend on the eigenvalues of matrices M or L, which are global information. Also some examples are provided for corroborating the feasibility of the theoretical results.

The aperiodic optimal linear estimator design problem is investigated in this paper for networked systems with communication uncertainties, including delays and data losses, where the sampling and estimation are nonuniform and asynchronous. Based on the idea of measurement fusion, two approaches are proposed to design the aperiodic estimators, and it is shown that the estimator is equivalent to that designed by the measurement augmentation method in performance. Moreover, the estimation performance is improved by using a newly proposed measurement retransmission scheme as compared with the commonly used hold-input and zero-input schemes, by which the lost measurements are never used once they are lost.

This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.

This paper proposes an adaptive neural-fuzzy sliding-mode control method for uncertain nonlinear systems with actuator effectiveness faults and input saturation. The parameter dependence of the control scheme is removed from the bound of actuator faults by updating online. A neural-fuzzy model is developed to approximate the uncertain nonlinear terms and a sliding-mode online-updating controller is developed to estimate the bound of the actuator with no prior knowledge of the fault. The asymptotic stability is verified via the Lyapunov method in the presence of actuator faults and saturation. Furthermore, the adaptive neural-fuzzy control method is extended to the uncertain faulty nonlinear systems with integral sliding-mode manifold as well as other popular sliding-mode surfaces. A numerical example is presented to demonstrate the effectiveness of the derived results.

This paper investigates the fuzzy control issue for uncertain active suspension systems via dynamic sliding-mode method. The Takagi-Sugeno fuzzy approach is adopted on the background of the varying masses to describe the prescribed nonlinear system in order to achieve the design targets via the method of sector nonlinearity. This paper employs the dynamic sliding-mode scheme to control nonlinear active suspension systems. In the proposed sliding-mode control scheme, the sliding surface function is formed linearly with the system states and control inputs. Then, a fuzzy dynamic term is utilized to construct the sliding-mode feedback controller. In existing results, the sliding mode is achieved and maintained with no consideration of the system perturbations. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, simulation results are presented to verify the effectiveness of the proposed schemes.

This paper studies the aperiodic sampled-data control for the sliding-mode control (SMC) scheme of fuzzy systems with communication-induced delays via the event-triggered method. In practice, it is impossible to update control in continuous manner; thus, an event-based control technique has become popular with the advantage that the control task is executed only if it is triggered by an event. In this paper, the event-based sliding-mode control (ESMC) is designed for each linear subsystem of the global fuzzy model first. Then, the conditions for “fuzzily” amalgamated ESMC are discussed to stabilize the global fuzzy model. This ensures that the SMC is executed only when necessary. Furthermore, the results are extended to the fuzzy systems with communication-induced delays. Finally, case studies are carried out to demonstrate the effectiveness of the derived results.

This paper is concerned with the finite-time synchronization issue of nonlinear coupled neural networks by designing a new switching pinning controller. For the fixed network topology and control strength, the newly designed controller could optimize the synchronization time by regulating a parameter α (0 ≤ α < 1). The control law presented in this paper covers both continuous controllers and discontinuous ones, which were studied separately in the past. Some criteria are discussed in detail on how to shorten the synchronization time for the strongly connected networks. Finally, the results are generalized to any network topologies containing a directed spanning tree, and one numerical example is given to demonstrate the effectiveness of the theoretical results.

In this brief, we investigate pinning control for cluster synchronization of undirected complex dynamical networks using a decentralized adaptive strategy. Unlike most existing pinning-control algorithms with or without an adaptive strategy, which require global information of the underlying network such as the eigenvalues of the coupling matrix of the whole network or a centralized adaptive control scheme, we propose a novel decentralized adaptive pinning-control scheme for cluster synchronization of undirected networks using a local adaptive strategy on both coupling strengths and feedback gains. By introducing this local adaptive strategy on each node, we show that the network can synchronize using weak coupling strengths and small feedback gains. Finally, we present some simulations to verify and illustrate the theoretical results.