Publications

Sensor Scheduling Design for Complex Networks under a Distributed State Estimation Framework

This paper investigates sensor scheduling for state estimation of complex networks over shared transmission channels. For a complex network of dynamical systems, referred to as nodes, a sensor network is adopted to measure and estimate the system states in a distributed way, where a sensor is used to measure a node. The estimates are transmitted from sensors to the associated nodes, in the presence of one-step time delay and subject to packet loss. Due to limited transmission capability, only a portion of sensors are allowed to send information at each time step. The goal of this paper is to seek an optimal sensor scheduling policy minimizing the overall estimation errors. Under a distributed state estimation framework, this problem is reformulated as a Markov decision process, where the one-stage reward for each node is strongly coupled. The feasibility of the problem reformulation is ensured. In addition, an easy-to-check condition is established to guarantee the existence of an optimal deterministic and stationary policy. Moreover, it is found that the optimal policies have a threshold, which can be used to reduce the computational complexity in obtaining these policies. Finally, the effectiveness of the theoretical results is illustrated by several simulation examples.

BIBO Stability of Nonlinear Fuzzy PI Control Systems

In this paper, we analyze in detail the bounded-input/bounded-output (BIBO) stability of the nonlinear fuzzy proportional-integral (PI) control systems developed in Ying, Siler, and Buckley (1990). In this investigation, the "small gain theorem" is e

Sensor scheduling design for complex networks under a distributed state estimation framework

This paper investigates sensor scheduling for state estimation of complex networks over shared transmission channels. For a complex network of dynamical systems, referred to as nodes, a sensor network is adopted to measure and estimate the system states in a distributed way, where a sensor is used to measure a node. The estimates are transmitted from sensors to the associated nodes, in the presence of one-step time delay and subject to packet loss. Due to limited transmission capability, only a portion of sensors are allowed to send information at each time step. The goal of this paper is to seek an optimal sensor scheduling policy minimizing the overall estimation errors. Under a distributed state estimation framework, this problem is reformulated as a Markov decision process, where the one-stage reward for each node is strongly coupled. The feasibility of the problem reformulation is ensured. In addition, an easy-to-check condition is established to guarantee the existence of an optimal deterministic and stationary policy. Moreover, it is found that the optimal policies have a threshold, which can be used to reduce the computational complexity in obtaining these policies. Finally, the effectiveness of the theoretical results is illustrated by several simulation examples.

Corrections to “LMI-based Approach for Asymptotically Stability Analysis of Delayed Neural Networks”

No abstract is provided for this article.

Analytic closed-form solutions for suboptimal trajectory planning of single-link flexible-joint robot arms

A suboptimal trajectory planning problem for single-link flexible-joint robot arms is studied. A global feedback-linearization technique is first applied to reformulate the nonlinear constrained optimization as a suboptimal interpolation problem. Then the unique analytic suboptimal solution for the problem is obtained in closed form. Simulation results are given to show the effectiveness of the method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Co-Evolution of Cross-border Portfolio Investment Networks and Indicators for Financial Crises

Two financial networks, namely, cross-border long-term debt and equity securities portfolio investment networks are analysed. They serve as proxies for measuring the interdependence of financial markets and the robustness of the global financial system from 2002 to 2012, covering the 2008 global financial crisis. Focusing on the largest strongly-connected core component of the threshold network, while the edge threshold is set according to the percolation properties of the long-term debt securities network, we identify two early-warning indicators for global financial distress. The spread of certain financial derivative products, such as credit default swaps and equity-linked derivatives, scales with the edge density of the long-term debt securities network. In addition, the algebraic connectivity of the equity securities network, taken as a measure for the robustness of financial markets, drops already sharply well ahead of the 2008 financial crisis.

Extending the Symbolic Dynamics of Chua's Bernoulli-Shift Rule 56.

IEEE Systems, Man, and Cybernetics Society Information

No abstract is provided for this article.

A novel Trellis-Coded Differential Chaotic Modulation system

In this paper, a novel coded modulation scheme named Trellis-Coded Differential Chaotic Modulation (TC-DCM) is proposed, which combines trellis codes with M-ary Differential Chaotic Shift Keying (M-DCSK). The new scheme not only reduces the multipath interference efficiently due to its inherent spreading property, but also avoids the use of Channel State Information (CSI), exact synchronization, despreading and the Rake receiver, making the corresponding receiver design simpler and more suitable for band-limited communication systems under severe multipath propagation conditions. Analytical Bit-Error-Rate (BER) bounds are derived and verified over Additive White Gaussian Noise (AWGN) channels. Both analytical performances and simulation results show that the proposed scheme with different states and different coding rates can obtain significant coding gains, compared to the corresponding uncoded schemes with the same bandwidth over AWGN channels. In addition, it is found from simulations that over multipath Rayleigh fading channels without CSI, the proposed TC-DCM system outperforms the Trellis-Coded Modulation Direct-Sequence Spread-Spectrum (TCM DS/SS) system with the same bandwidth efficiency.

Almost Sure Stability of Nonlinear Systems Under Random and Impulsive Sequential Attacks

This article is concerned with the stability problem for a class of Lipschitz-type nonlinear systems in networked environments, which are suffered from random and impulsive deception attacks. The attack is modeled as a randomly destabilizing impulsive sequence, whose impulsive instants and impulsive gains are both random with only the expectations available. Almost sure stability is ensured based on Doob's Martingale Convergence Theorem. Sufficient conditions are derived for the solution of the nonlinear system to be almost surely stable. An example is given to verify the effectiveness of the theoretical results. It is shown that the random attack will be able to destroy the stability, therefore, a large feedback gain may be necessary.

Observer-Based Consensus for Multi-Agent Systems With Semi-Markovian Jumping Via Adaptive Event-Triggered SMC

This paper investigates the observer-based event-triggered adaptive sliding mode control (SMC) problem of the semi-Markovian jumping multi-agent systems (S-MJMASs) with completely unknown and uncertain bounded transfer probabilities (TPs). As impacted by the limited bandwidth of the communication network between individual agents and the unmeasurable state information of the systems, an innovative observer based distributed event-triggered adaptive mechanism (ETAM) is proposed, in which the global information of the network is not used and the triggering threshold is dynamically regulated by the adaptive law to reduce excessive network communication. Additionally, since delays exist between the event trigger and the zero-order holder (ZOH) during data transmission in network communication systems, as well as the semi-Markovian jumping parameters, the uncertainty of systems is increased. In this paper, a novel integral sliding surface is constructed and its reachability and continuity in stochastic senses are guaranteed to withstand interferences. With the help of a stochastic semi-Markovian Lyapunov functional and numerous linear matrix inequalities (LMIs) approaches, certain adequate conditions are achieved to ensure that all agents in S-MJMASs can track the leader. Finally, certain numerical simulations are used to demonstrate the efficiency of the suggested theoretical conclusions.

Multivaluedness in Networks: Exemplars

This brief presents the first observations of multivaluedness in four systems: a random process, a nonlinear nondynamical system, a nonlinear dynamical system with nonlinearly sensed input and output and an adaptive linear estimator. The preliminary findings reported here, suggest the impact of multivaluedness in different types of networks to range from adverse to benign or even essential.

Adaptability between FM-DCSK and Channel Coding over Fading Channels

FM-DCSK is a non-coherent modulation and demodulation technique that uses chaotic signals as the carrier. Due to its inherent broadband nature, its good performance of anti-multipath-fading is promising for wireless communications. In order to improve the global performance of such chaotic communication systems, enhanced FM-DCSK based on the Woven convolutional code (WCC) is presented. Through system simulations, this article demonstrates that the WCC-based FM-DCSK system is superior to that of the traditional code-based FM-DCSK system and the original FM-DCSK system over AWGN, Rayleigh and Ricean flat fading channels, especially with prominent coding gains over fading channels. It is further verified that there exists adaptability between FM-DCSK and channel coding. This finding will be significant for optimizing and analyzing the performance of the FM-DCSK system improved by good channel coding schemes, towards better applications of the chaotic communication technology in the future.

Reliable Event-Triggered Load Frequency Control of Uncertain Multiarea Power Systems With Actuator Failures

Load frequency control (LFC) is crucial for the economic operation and safety of power systems. Therefore this paper addresses the LFC problem for uncertain multi-area power systems with actuator failures. Specifically, actuator failures, uncertainties and communication bandwidth constraints appearing in multi-area power systems are taken into account simultaneously, and novel reliable event-triggered LFC schemes are proposed to cope with these troubles. The proposed schemes can ensure the asymptotical stability of the closed-loop system when only matched uncertainty exists. For the case of coexisting matched and mismatched uncertainties, the state trajectories of the closed-loop system can be controlled within a bounded set, where the size of the bounded set is only related to the mismatched uncertainty. To illustrate the theoretical results, a numerical example of three-area interconnected power system is presented. Note to Practitioners—Load frequency directly affects the quality of electric energy and is one of the main observation states of power systems, hence LFC has been widely investigated in the literature. For multi-area power systems, the system model to be controlled may be subjected to multiple unfavorable factors in practical situations, such as limited bandwidths, model uncertainties and actuator failures. To cope with these unfavorable factors, this paper is devoted to developing a unified control framework to guarantee the stability of the frequency deviation based on the event-triggered mechanism. Considering both matched and unmatched system uncertainties may exist as well as the bound of system uncertainties can be unknown, event-triggered control schemes including static event-triggered LFC and adaptive event-triggered LFC are accordingly designed to deal with aforementioned situations such that the closed-loop system is asymptotically or boundedly stable. The research outcome of this paper provides simple but effective LFC approaches that can be used to maintain the reliable and stable operation of multi-area power systems.

Generating multi-scroll chaotic attractors via switching control

This paper proposes a new switching control method, saturated function series approach, for generating multi-scroll chaotic attractors. The systematic methodology developed here can create multi-scroll chaotic attractors from a given 3-D linear autonomous system with a saturated function series controller. It includes 1-D n-scroll, 2-D n /spl times/ m-grid scroll, and 3-D n /spl times/ m /spl times/ l-grid scroll chaotic attractors. The chaos generation mechanism in multi-scroll systems is briefly discussed by analyzing the system equilibria.

Research on bifurcation behaviour and chaos control in DC-DC buck converter

In this paper,the bifurcation behaviour and chaos control are investigated for a DC-DC buck converter with load capacitor.Some valuable new results are obtained,e.g.,the periodicity adding windows are found in this circuit system and the measure of chaotic motion is found to converge to zero asymptotically increasing load capacitance.Moreover,it is found that the transform ratio of voltage for periodict motion is higher than that for the chaotic motion in the buck converter.These results have some applications for designing practical circuits.At the same time,chaotic behaviours of this circuit system can be effectively controlled by applying suitable periodic impulses to the system.

Linear quadratic optimal consensus of discrete-time multi-agent systems with optimal steady state: A distributed model predictive control approach

This paper develops a distributed model predictive control algorithm for linear quadratic optimal consensus of discrete-time multi-agent systems. The consensus state and control sequence are both optimized at every predictive step on a finite horizon and then implemented in the real system. The stability of the closed-loop system is analyzed, establishing a distributed consensus condition depending only on individual agent’s local parameters. The consensus condition is then relaxed for controllable systems, making it easy to choose the weighted matrices and control period for each agent. The proposed algorithm is applied to the formation control of multi-vehicle systems verified by numerical simulations.

Controlling degenerate Hopf bifurcations

No abstract is provided for this article.