Publications

We study boundary expansions of solutions of complex Monge-Ampere equations and discuss the convergence of such expansions. We prove a global conver- gence result under that assumption that the entire boundary is analytic. If a portion of the boundary is assumed to be analytic, the expansions may not converge locally.

This work is concerned with the controller design of networked control systems (NCSs). A new model of NCSs is provided under consideration of both the network-induced delay and the data packet dropout in the transmission. In terms of the given model, a controller design method is proposed based on a delay dependent approach. The feedback gain of a memoryless controller and the maximum allowable value of the network-induced delay can be derived by solving a set of linear matrix inequalities. Two examples are given to show the effectiveness of our method.

This paper deals with the problem of asynchronous event-triggered control for decentralized networked systems. A group of geographically distributed sensors rather than a centralized sensor are deployed to asynchronously sample and measure the system’s state signal. First, an asynchronous decentralized event-triggered transmission scheme is developed to check which sensor measurements should be transmitted to a remote control station via a network channel. Second, a series of artificial piecewise functions are introduced to incorporate the simultaneous effects of intermittent transmissions and network-induced delays into multiple delays. By considering distribution characteristics of these delays and using a switching Lyapunov–Krasovskii functional, criteria on L 2 stability analysis and control design are derived. Finally, a well-used batch reactor system is employed to illustrate the effectiveness of the proposed control design method.

This paper focuses on the stability problem for a class of linear neutral systems with mixed neutral and discrete delays. A discretized Lyapunov functional approach is developed for such kinds of systems. The resulting stability criteria are formulated in the form of a linear matrix inequality (LMI). These criteria are applicable to linear neutral systems with both small and non-small discrete delays. For nominal systems, the analytical results can be approached with fine discretization. For uncertain systems, the new approach is much less conservative. Numerical examples show significant improvement over approaches in the literature.

This paper is concerned with lag synchronization of two coupled delayed systems with parameter mismatch. Due to parameter mismatch, complete lag synchronization can not be achieved. Therefore, a new lag quasi-synchronization scheme is proposed to ensure that coupled systems are in a state of lag synchronization with an error level. Several simple criteria are derived and the error level is estimated by applying a generalized Halanary inequality and matrix measure. Three examples are given to illustrate the effectiveness of the proposed lag quasi-synchronization scheme. It is shown that as the coupling strength increases, the estimated error level is close to the simulated one, which well supports theoretical results.

The design problem of a delay-dependent robust H∞ controller for uncertain descriptor systems with time-varying discrete and distributed delays is investigated. The designed controller can guarantee the closed-loop system is regular, impulse-free and exponentially stable with an H∞ norm bound constraint. The obtained criteria to derive an efficient robust H∞ control design are expressed as a set of nonconvex matrix inequalities, which can be solved by combining both the linear matrix inequalities technique and the cone complementarity method. Two numerical examples are given to demonstrate effectiveness and less conservativeness of the proposed method.

This paper considers the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control problem for discrete-time Takagi-Sugeno (T-S) model fuzzy systems with event-triggered output feedback. The measurement output is transmitted to a fuzzy controller when the output error exceeds a pre-given threshold. The parallel distribution compensation (PDC) can not be used for controller design since the controller may not receive enough information about premise variables of the plant due to the event-triggered transmission scheme. A fuzzy dynamical output feedback controller is proposed to regularly generate the control input, which makes the controlled system stable with a certain H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> disturbance attenuation level. A numerical example is given to show the effectiveness of the proposed approach.

In this paper, we study the smooth isometric immersion of a complete simply connected surface with a negative Gauss curvature in the three-dimensional Euclidean space. For a surface with a finite total Gauss curvature and appropriate oscillations of the Gauss curvature, we prove the global existence of a smooth solution to the Gauss-Codazzi system and thus establish a global smooth isometric immersion of the surface into the three-dimensional Euclidean space. Based on a crucial observation that some linear combinations of the Riemann invariants decay faster than others, we reformulate the Gauss-Codazzi system as a symmetric hyperbolic system with a partial damping. Such a damping effect and an energy approach permit us to derive global decay estimates and meanwhile control the non-integrable coefficients of nonlinear terms.

In the Cloud Radio Access Network (C-RAN) architecture, a Control Unit (CU) implements the baseband processing functionalities of a cluster of Base Stations (BSs), which are connected to it through a fronthaul network. This architecture enables centralized processing at the CU, and hence the implementation of enhanced interference mitigation strategies, but it also entails an increased decoding latency due to the transport on the fronthaul network. The fronthaul latency may offset the benefits of centralized processing when considering the performance of protocols at layer 2 and above. This letter studies the impact of fronthaul latency on the performance of standard Automatic Retransmission reQuest (ARQ) protocols, namely Stop and Wait, Go-Back-N and Selective Repeat. The performance of the C-RAN architecture in terms of throughput and efficiency is compared to the that of a conventional cellular system with local processing, as well as with that of a proposed hybrid C-RAN system in which BSs can perform decoding. The dynamics of the system are modeled as a multi-dimensional Markov process that includes sub-chains to capture the temporal correlation of interference and channel gains. Numerical results yield insights into the impact of system parameters such as fronthaul latency and signal-to-interference ratio on different ARQ protocols.

Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything (V2X) communication to share perceptual data, enhances detection but is vulnerable to channel impairments, such as noise, fading, and interference. To strengthen the reliability of intelligent transportation systems, this work improves the robustness of V2X cooperative perception under communication conditions that reflect common channel impairments. This paper proposes an Adaptive Feature Fusion Transformer (AFFormer), a Transformer-based framework that mitigates the adverse effects of corrupted features by modeling temporal, inter-agent, and spatial correlations. AFFormer introduces three key modules: Multi-Agent and Temporal Aggregation for context-aware fusion across agents and over time, Dual Spatial Attention for efficient modeling of spatial dependencies, and Uncertainty-Guided Fusion for entropy-driven refinement of fused features. A teacher-student knowledge distillation strategy further enhances robustness by aligning fused features with reliable early-collaboration supervision. AFFormer is validated on the V2XSet and DAIR-V2X datasets, where it consistently outperforms existing methods under both ideal and impaired communication conditions, demonstrating improved robustness to communication-induced feature degradation while maintaining a competitive efficiency-accuracy trade-off.

This paper focuses on network-based master-slave synchronization for delayed neural networks through a remote controller. The insertion of communication networks in a master-slave synchronization scheme inevitably induces network delays, packet dropouts and stochastic fluctuations. The data packets may be received with a different temporal order from that they are sent due to the fact that the network-induced delay is time-varying. A logic data processor and a logic zero order hold are proposed in the master-slave synchronization framework. Then an error system for the master system and the slave system is formulated. By combining a generalized Jensen integral inequality and a convex combination technique, some synchronization criteria are derived to ensure the mean-square global exponential synchronization of state trajectories for the master system and the slave system. The controller gain matrix is obtained by solving a minimization problem in terms of linear matrix inequalities using a cone complementary technique. As a special case in which only network-induced delays and packet dropouts are occurred in the signal transmission channels, some results are also presented. Finally, two illustrative examples are provided to show the effectiveness and applicability of the proposed scheme.

This paper is concerned with event-triggered mixed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> and passive control for linear systems via dynamic output feedback controllers. The system outputs are grouped into multiple nodes, in which different senors sample the corresponding data with a same period. A decentralized event-triggering scheme is introduced to select those necessary data packets to be transmitted so that communication resources can be significantly saved while preserving the prescribed closed-loop performance. First, to organize the decentralized data packets transmitted from the sensor nodes, a data packet packet (DPP) is used to generate new signal once its stores are updated at some time instants. Second, under the mechanism of the DPP, the closed-loop system is modeled as a linear system with an interval time-delay. Employ Lyapunov functional method to formulate a novel sufficient condition such that the closed-loop system is asymptotically stable with the mixed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> and passive performance. Third, an LMI-based approach is proposed to co-design both event-triggering schemes and desired dynamic output feedback controllers. A satellite control system is given to demonstrate the effectiveness of the method proposed in this paper.

This paper is concerned with the networked active suspension control problem for in-wheel motor-driven electric vehicles subject to communication constraints, including intermittent data transmissions, quantized output measurements and network-induced transmission delays. The central goal is to develop a resource-efficient communication and active suspension control co-design approach such that the limited in-vehicle network resources are occupied in an efficient manner, while simultaneously achieving the desired suspension system performance. For this purpose, a networked data transmission framework, incorporating a dynamic event-triggered communication mechanism and a logarithmic quantizer, is developed to accommodate the intermittent and digitalized packet-based transmissions over the in-vehicle controller area network channels. Specifically, the event triggering mechanism sporadically selects the sampled sensor data packets to be transmitted, which are then quantized before sending over the network channels. Then, formal stability and suspension performance analysis is carried out, and a co-design criterion on the existence of the desired triggering mechanism and event-triggered output feedback controller is further derived. Finally, the effectiveness and merits of the derived results are substantiated via several numerical case studies.

This paper is concerned with decentralized event-triggered dissipative control for systems with the entries of the system outputs having different physical properties. Depending on these different physical properties, the entries of the system outputs are grouped into multiple nodes. A number of sensors are used to sample the signals from different nodes. A decentralized event-triggering scheme is introduced to select those necessary sampled-data packets to be transmitted so that communication resources can be saved significantly while preserving the prescribed closed-loop performance. First, in order to organize the decentralized data packets transmitted from the sensor nodes, a data packet processor (DPP) is used to generate a new signal to be held by the zero-order-hold once the signal stored by the DPP is updated at some time instant. Second, under the mechanism of the DPP, the resulting closed-loop system is modeled as a linear system with an interval time-varying delay. A sufficient condition is derived such that the closed-loop system is asymptotically stable and strictly (Q0,S0,R0) -dissipative, where Q0,S0 , and R0 are real matrices of appropriate dimensions with Q0 and R0 symmetric. Third, suitable output-based controllers can be designed based on solutions to a set of a linear matrix inequality. Finally, two examples are given to demonstrate the effectiveness of the proposed method.