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.

This study aims to investigate containment control of linear multi‐agent systems with input saturation on switching topologies. For such a multi‐agent system, both state feedback and output feedback containment control protocols are proposed via a novel low‐gain feedback approach. Consequently, the authors show that, under the assumption that the switching networks are jointly connected, semi‐global state feedback and output feedback containment control of the multi‐agent system can be attained. The effectiveness of the proposed algorithms is illustrated via numerical examples.

This paper investigates the problem of coordinated tracking of a linear multi‐agent system subject to actuator magnitude saturation and dead zone characteristic with input additive uncertainties and disturbances. Distributed consensus and swarm tracking protocols are developed from a low‐and‐high gain feedback approach. Under the assumption that each agent is asymptotically null controllable with bounded controls, it is shown that robust semi‐global consensus tracking and swarm tracking of the multi‐agent system can always be reached provided that the networks are connected. Numerical examples are provided to illustrate the theoretical results. Copyright © 2014 John Wiley & Sons, Ltd.

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.

Compared with rigid grippers, soft grippers show fantastic adaptability and flexibility in grasping irregularly shaped and fragile objects. However, the low stiffness of the soft actuator limits the scope of applications. Particle jamming has emerged as an important method to adjust the stiffness of soft grippers. This paper proposes a novel particle jamming mechanism based on the differential pressure drive. With the differential drive particle jamming mechanism, a soft actuator is designed, which is characterized by a dual-deformable chamber structure in which one chamber is filled with particles. The simultaneous inflation of the two chambers will result in the bending behavior without significant stiffening. However, if the air chamber is pressurized with a larger pressure, the differential pressure will cause the particles inside the particle chamber to jam each other, which increases the stiffness of the actuator significantly. Thus, the differential drive particle jamming mechanism can achieve the independent control of the stiffness and the bending angle. Both theoretical and experimental studies in this area have shown that the gripper based on the differential drive particle jamming mechanism can stiffen itself effectively, and achieve the independent control of the stiffness and the bending angle, which can be adopted in applications where both high stiffness and dexterity are required.

Soft sensors are required to accommodate the flexible and deformable natures of the human body in wearable device applications. They are also suitable for integration with soft robotic devices to monitor the performance status and provide references for feedback control. However, the choices for bending sensors are still highly limited. In this paper, a soft bending sensor is presented. By careful design with a blend of sensitive and insensitive regions, the sensor could be stretchable while being insensitive to stretching. An analytical study was presented on how to design the sensor with the named bending/stretching feature. This feature enables the sensor to be implemented in measuring human motions where a large amount of skin stretch is involved. Two sensor gloves were designed and fabricated based on the proposed soft bending sensor, aiming for different application scenarios. Both the sensor and the gloves were evaluated using a dedicated evaluation platform with experimental results compared against each other.