Rui-Quan Liao

Distributed controller-estimator for target tracking of networked robotic systems under sampled interaction

This paper investigates the target tracking problem for networked robotic systems (NRSs) under sampled interaction. The target is assumed to be time-varying and described by a second-order oscillator. Two novel distributed controller-estimator algorithms (DCEA), which consist of both continuous and discontinuous signals, are presented. Based on the properties of small-value norms and Lyapunov stability theory, the conditions on the interaction topology, the sampling period, and the other control parameters are given such that the practical stability of the tracking error is achieved and the stability region is regulated quantitatively. The advantages of the presented DCEA are illustrated by comparisons with each other and the existing coordination algorithms. Simulation examples are given to demonstrate the theoretical results.

Multi-consensus of multi-agent networks via a rectangular impulsive approach☆

Abstract A multi-consensus problem is studied in multi-agent networks. The interaction mechanism of competition/abstention/cooperation among agents is introduced. Three rectangular impulsive protocols are proposed to solve multi-consensus of second order multi-agent networks with a directed topology. These algorithms have the performance of Dirac impulsive control and discrete-time control. Necessary and sufficient conditions are obtained for the stationary multi-consensus and the dynamic multi-consensus. Numerical examples are provided to illustrate the effectiveness of the obtained criteria.

Stability and Bifurcation Analysis of Cyclic Genetic Regulatory Networks with Mixed Time Delays

This paper analyzes the stability and bifurcation criteria of cyclic genetic regulatory networks with mixed time delays (discrete and Gamma-type distributed delays). It is of more realistic biological background to use Gamma-type distributed delay kernels to describe the delays in the process between genes. The key aim of our research is to reveal more about the dynamic functions played by biochemical parameters and different mechanisms of discrete and distributed time delays. The existence of positive equilibria in this kind of genetic network is verified. With the mathematical tools of subharmonic function and complex theory, exact conditions of biochemical parameters for stability and bifurcations in cyclic genetic regulatory networks with both positive and negative gains are deduced, respectively. Finally, several simulation examples are adopted to deepen our analysis.

Multi-consensus of multi-agent systems with various intelligences using switched impulsive protocols

In this paper, multi-consensus refers to that the states of multi-agent systems asymptotically converge to several consistent values. The concept of intelligence degree is introduced to characterize the level of agent intelligence. Based on that, some distributed switched impulsive protocols are proposed using sampled position data and sampled velocity data alternately at sampling instants. The continuous-time multi-agent system using the proposed protocols is equivalently transformed into a discrete-time system. Some necessary and sufficient conditions on the communication network topology are obtained. Three types of multi-consensus can be asymptotically achieved if and only if the directed network has a spanning tree and the feedback gains and sampling periods are chosen appropriately. Moreover, the final states of multi-consensus are analytically determined for second-order multi-agent systems, which depend on the initial states of the agents, the communication network topology, and the feedback gains in the protocols. Numerical examples are finally presented to show the effectiveness of the proposed protocols and to verify the theoretical results.

Stability and bifurcation analysis of new coupled repressilators in genetic regulatory networks with delays

The genetic regulatory networks are complex dynamic systems which reflect various kinetic behaviors of living things. In this paper, a new structure of coupled repressilators is introduced to exploit the underlying functions. The new coupled repressilator model consists of two identical repressilators inhibiting each other directly. The coupling delays are taken into account. The existence of a unique equilibrium for this system is verified firstly, then the stability criteria for equilibrium are analyzed without and with coupling delays. The different functions on equilibrium and its stability played by related biochemical parameters in the structure including maximal transcription rate, coupling strength, the decay rate ratio between proteins and mRNAs, and coupling delays are discussed. At last, several numerical simulations are made to demonstrate our results.

Fundamental performance limitations of networked control systems with novel trade-off factors and constraint channels

Abstract This paper focuses on the optimal tracking performance issues for linear time invariant system with bandwidth limited and additive colored white Gaussian noise (ACGN) simultaneously. The nonminimal phase and unstable plant are considered, and multi-repeated zeros and poles is investigated. The objective function of tracking response is minimized jointly with the control effort. In order to more fully reflect the performance of the network control systems (NCSs), the performance index is measured by the tracking error energy, input channel energy and plant input energy using novel trade-off factors. The novel trade-off factors can be measured each frequency band for each signal, which are stable and minimal phase transfer function. To obtain the optimal performance, the two-parameter controller is adopted. The tracking performance is given by explicit expression, which is critically dependent on the intrinsic characteristics of the given plant (unstable poles and nonminimal phase zeros), communication parameters (bandwidth and statistical characteristics of network noise) and statistical characteristics of reference signal. Finally, the simulation results demonstrate the effectiveness of the proposed control scheme.

Robust mode-free sliding mode control of multi-fingered hand with position synchronization in the task space

In this paper, for the purpose of improving operation performance of multi-fingered hand and multiple robotic manipulators, a robust position synchronization mode-free sliding-mode control (SMC) strategy is proposed. By invoking the Lyapunov stability approach, the effectiveness of the proposed approach is testified to be robust while facing various disturbances and dynamic uncertainties. Besides, according to the practical application, the kinematic diversity is taken into consideration. We assume each individual in the multi-agent system to be with kinematic redundancy or without. Finally, we present computer simulation results to verify the effectiveness of the proposed algorithm.

Multisynchronization of Coupled Heterogeneous Genetic Oscillator Networks via Partial Impulsive Control

This paper focuses on the collective dynamics of multisynchronization among heterogeneous genetic oscillators under a partial impulsive control strategy. The coupled nonidentical genetic oscillators are modeled by differential equations with uncertainties. The definition of multisynchronization is proposed to describe some more general synchronization behaviors in the real. Considering that each genetic oscillator consists of a large number of biochemical molecules, we design a more manageable impulsive strategy for dynamic networks to achieve multisynchronization. Not all the molecules but only a small fraction of them in each genetic oscillator are controlled at each impulsive instant. Theoretical analysis of multisynchronization is carried out by the control theory approach, and a sufficient condition of partial impulsive controller for multisynchronization with given error bounds is established. At last, numerical simulations are exploited to demonstrate the effectiveness of our results.

Event-driven multi-consensus of multi-agent networks with repulsive links

Due to diversification in environment, a network of agents may have several emergent behaviors. This paper introduces an event-driven paradigm for realizing multi-consensus, which as a generic version of group/cluster consensus, depends both on the initial underlying topology and initial states.For the network feature, we resort to a distributed event-driven paradigm, since event-driven control has advantages on communication reduction and control energy saving. Moreover, to relax assumption on network topology, repulsive links are exploited at event instants to facilitate multiple coordination.To realize multi-consensus, we design a distributed event-driven controller based on coupled intra-subgroup and extra-subgroup information. In this context, with different control strengths, the finial value of MAN would be varying. This phenomenon matches the principle of multi-consensus in the current study.Based on LaSalles invariance principle, we prove that under the proposed event-driven configuration, the joint cooperation and competition contributes to multi-consensus provided that the sampling period is no larger than a positive threshold. It is shown there is no further requirement on network topologies in pursuit of multiple coordination. This paper studies multiple coordination of multi-agent networks under an event-driven paradigm. For an undirected connected graph, a node clustering scheme is first adopted to ensure a relatively strong degree of connectivity within each potential subgroup, and some repulsive effect is used to deal with the extra-subgroup links. To reduce unnecessary communication, a distributed event-driven controller is designed via coupled intra-subgroup and extra-subgroup information. Based on the LaSalles invariance principle, it is shown that under the proposed event-driven control configuration, multi-agent networks can realize multi-consensus without any balanced requirement on the underlying topologies. Simulation work is presented to validate the theoretical results.

Multiconsensus of second-order multiagent systems with input delays

The multiconsensus problem of double-integrator dynamic multiagent systems has been investigated. Firstly, the dynamic multiconsensus, the static multiconsensus, and the periodic multiconsensus are considered as three cases of multiconsensus, respectively, in which the final multiconsensus convergence states are established by using matrix analysis. Secondly, as for the multiagent system with input delays, the maximal allowable upper bound of the delays is obtained by employing Hopf bifurcation of delayed networks theory. Finally, simulation results are presented to verify the theoretical analysis.