Quasi-synchronization of fractional-order complex networks with random coupling via quantized control

We investigate the quasi-synchronization of fractional-order complex networks(FCNs) with random coupling via quantized control. Firstly, based on the logarithmic quantizer theory and the Lyapunov stability theory, a new quantized feedback controller, which can make all nodes of complex networks quasi-synchronization and eliminate the disturbance of random coupling in the system state, is designed under non-delay conditions. Secondly, we extend the theoretical results under non-delay conditions to time-varying delay conditions and design another form of quantization feedback controller to ensure that the network achieves quasi-synchronization. Furthermore, the error bound of quasi-synchronization is obtained.Finally, we verify the accuracy of our results using two numerical simulation examples.

Adaptive Consensus Quantized Control for a Class of High-Order Nonlinear Multi-Agent Systems With Input Hysteresis and Full State Constraints

For a class of high-order nonlinear multi-agent systems with input hysteresis,an adaptive consensus output-feedback quantized control scheme with full state constraints is investigated.The major properties of the proposed control scheme are:1)According to the different hysteresis input characteristics of each agent in the multi-agent system,a hysteresis quantization inverse compensator is designed to eliminate the influence of hysteresis characteristics on the system while ensuring that the quantized signal maintains the desired value.2)A barrier Lyapunov function is introduced for the first time in the hysteretic multi-agent system.By constructing state constraint control strategy for the hysteretic multi-agent system,it ensures that all the states of the system are always maintained within a predetermined range.3)The designed adaptive consensus output-feedback quantization control scheme allows the hysteretic system to have unknown parameters and unknown disturbance,and ensures that the input signal transmitted between agents is the quantization value,and the introduced quantizer is implemented under the condition that only its sector bound property is required.The stability analysis has proved that all signals of the closed-loop are semi-globally uniformly bounded.The Star Sim hardware-in-the-loop simulation certificates the effectiveness of the proposed adaptive quantized control scheme.

Finite-time synchronization of uncertain fractional-order multi-weighted complex networks with external disturbances via adaptive quantized control

The finite-time synchronization of fractional-order multi-weighted complex networks(FMCNs)with uncertain parameters and external disturbances is studied.Firstly,based on fractional calculus characteristics and Lyapunov stability theory,quantized controllers are designed to guarantee that FMCNs can achieve synchronization in a limited time with and without coupling delay,respectively.Then,appropriate parameter update laws are obtained to identify the uncertain parameters in FMCNs.Finally,numerical simulation examples are given to validate the correctness of the theoretical results.

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

Quantized Nonlinear Control-A Survey

Quantized control systems design is motivated by the convergence of controls and communications to address modern engineering applications involving the use of information technology. This paper presents an overview of recent developments on the control of linear and nonlinear systems when the control input is subject to quantization or the quantized states or outputs are used as feedback measurements. The co-existence of high-dimeasionality, quantization, nonlinearity and uncertainty poses great challenges to quantized control of nonlinear systems and thus calls for new ideas and techniques. The field of quantized nonlinear control is still at its infancy. Preliminary results in our recent work based on input-to-state stability and cyclic-small-gain theorems are reviewed. The open problems in quantized nonlinear control are also outlined.

Finite-time stabilization of switched dynamical networks with quantized couplings via quantized controller

This paper concerns the stabilization of switched dynamical networks with logarithmic quantization couplings in a settling time.The switching sequence is constrained by hybrid dwell time. Controller is designed by using limited information. Due to the quantization and switching, traditional finite-time analysis methods cannot be utilized directly. By designing multiple Lyapunov functions and constructing comparison systems, a general criterion formulated by matrix inequalities is first given. Then specific conditions in terms of linear matrix inequalities are established by partitioning the dwell time and using convex combination technique. An optimal algorithm is proposed for the estimation of settling time. Numerical simulations are given to verify the effectiveness of the theoretical results.

Data-Driven Control of Linear Systems via Quantized Feedback

Quantized feedback control is fundamental to system synthesis with limited communication capacity.In sharp contrast to the existing literature on quantized control which requires an explicit dynamical model,the authors study the quadratic stabilization and performance control problems with logarithmically quantized feedback in a direct data-driven framework,where the system state matrix is not exactly known and instead,belongs to an ambiguity set that is directly constructed from a finite number of noisy system data.To this end,the authors firstly establish sufficient and necessary conditions via linear matrix inequalities for the existence of a common quantized controller that achieves our control objectives over the ambiguity set.Then,the authors provide necessary conditions on the data for the solvability of the LMIs,and determine the coarsest quantization density via semi-definite programming.The theoretical results are validated through numerical examples.

Iterative Learning Control With Incomplete Information： A Survey

Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.

Networked Control Systems:A Survey of Trends and Techniques

Networked control systems are spatially distributed systems in which the communication between sensors, actuators,and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices,increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems,process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘control over networks’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘control over networks’, providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.

Quantized Formation Control of Heterogeneous Nonlinear Multi-Agent Systems with Switching Topology

This paper studies the formation control problem for the second-order heterogeneous nonlinear multi-agent systems(MASs)with switching topology and quantized control inputs.Compared with formation control under the fixed topology,under the switching topology inherent nonlinear dynamics of the agent and the connectivity change of the communication topology are considered.Moreover,to avoid the chattering phenomenon caused by unknown input disturbances,the hysteretic quantizers are incorporated to quantize the input signals.By using the Lyapunov stability theory and leader-follower formation approach,the proposed formation control scheme ensures that all signals of the MASs are semi-globally uniformly ultimately bounded(SGUUB).Finally,the efficiency of the theoretical results is proved by a simulation example.

Quantized H_∞ Fault-tolerant Control for Networked Control Systems

Quantized H_∞ fault-tolerant control for networked control systems (NCSs) with partial actuator fault with respect to actuators is concerned in this paper. Considering transmission delay, packet dropout and quantization, a synthesis model with partial actuator fault is established. The piecewise constant controller is adopted to model NCS with the transmission delay and packet dropout. Due to data transmitted in practical NCSs should be quantized before they are sent to the next network node, the logarithmic static and time-invariant quantizers at the sensor and controller sides are proposed in the paper. For the established model, an appropriate type of Lyapunov functions is provided to investigate the delay-dependent H_∞ control problem. According to an optimal problem, the controller that makes the system achieve the best performance is designed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.

Fault-tolerant control with mixed aerodynamic surfaces and RCS jets for hypersonic reentry vehicles

This paper proposes a fault-tolerant strategy for hypersonic reentry vehicles with mixed aerodynamic surfaces and reaction control systems（RCS） under external disturbances and subject to actuator faults.Aerodynamic surfaces are treated as the primary actuator in normal situations,and they are driven by a continuous quadratic programming（QP） allocator to generate torque commanded by a nonlinear adaptive feedback control law.When aerodynamic surfaces encounter faults,they may not be able to provide sufficient torque as commanded,and RCS jets are activated to augment the aerodynamic surfaces to compensate for insufficient torque.Partial loss of effectiveness and stuck faults are considered in this paper,and observers are designed to detect and identify the faults.Based on the fault identification results,an RCS control allocator using integer linear programming（ILP） techniques is designed to determine the optimal combination of activated RCS jets.By treating the RCS control allocator as a quantization element,closed-loop stability with both continuous and quantized inputs is analyzed.Simulation results verify the effectiveness of the proposed method.

量化反馈控制与估计的综述(英文)

This paper serves as a tutorial paper for a new area of research in control systems,namely,quantized feedback control and estimation. This area is motivated by the increasing need of incorporating communication networks in a control system. In such a framework,feedback information needs to be transmitted over a digital network,which results in a number of new challenges for estimation and control design. The focus of this paper is to introduce a number of recent results on the design of quantizers for the purposes of control design and state estimation. uantized feedback control,networked control,quantized estimation,robust control.