Quantized Output Feedback Control Research Articles

Dynamic Quantized Output-Feedback Control of Impulsive Systems With Round-Robin Protocols and Transmission Delays

Dynamic Quantized Output-Feedback Control of Impulsive Systems With Round-Robin Protocols and Transmission Delays

Adaptive Quantized Output Feedback Control of Nonlinear Systems With Mismatched Uncertainties and Sensor Failures

Adaptive Quantized Output Feedback Control of Nonlinear Systems With Mismatched Uncertainties and Sensor Failures

State Quantized Output Feedback Control for Nonlinear Systems via Event-Triggered Sampling

The current article proposes a novel output feedback event-triggered control scheme for nonlinear systems considering state quantization. First, we construct a state observer to track the unavailable system states. Second, a dynamic event-triggered and quantized mechanism is constructed to handle the state sampling and quantization. By designing the event-triggered mechanism to sample the system state, and using the quantizer to filtrate the sampled signals, the wasted resources in the data channels can be effectively reduced, and the communication efficiency can be improved. Then, based on the input-to-state stability method, the asymptotic stability is ensured for the closed-loop systems. Moreover, we propose an event-triggered and quantized control scheme for the nonlinear systems with input delay, and the asymptotic stability is ensured using the Lyapunov–Krasovskii functional method. The proposed output feedback event-triggered and quantized mechanisms can guarantee a positive lower bound of the transmission interval times of communication channels, which means that the Zeno behavior is avoided. Finally, a simulation example is presented to verify the feasibility of the proposed control schemes.

Quantized output feedback control for switched systems with DoS attacks and event-triggered sampling

This paper studies the event-triggered control for discrete-time switched systems under the influence of denial-of-service (DoS) attacks and output quantization. Firstly, the switching is assumed to be slow enough in the sense of average dwell time, and DoS attacks are assumed to be energy-limited by constraining DoS frequency and DoS duration. Secondly, by designing an event-triggered mechanism which integrates switching, DoS attacks and transmission error, the initial state bound is obtained at a finite time. Then, a novel quantization coding method is designed by introducing a monotonically increasing sequence, which guarantees the unsaturation of the quantizer. On the basis of this, the exponential convergence and Lyapounov stability of the closed-loop system are established. Finally, two-tanks system is illustrated to demonstrate the effectiveness of the theoretical analysis.

Quantized Output Feedback Control of AFS for Electric Vehicles With Transmission Delay and Data Dropouts

This article proposes a robust <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_\infty $ </tex-math></inline-formula> output feedback control strategy to improve vehicle lateral stability through active front wheel steering with quantization error, transmission delay and data dropouts. Since vehicle lateral dynamics presents inherently uncertain challenges, the polytopic technique is used and the variation of tire cornering stiffness is compensated via norm-bounded uncertainty. Meanwhile, considering that the measurement outputs are inevitably suffer from network-induced constrains, i.e. the quantization error, transmission delay and data dropouts, which degrade the stability and handling performance of vehicle, a robust gain-scheduling <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_\infty $ </tex-math></inline-formula> output feedback controller design strategy is proposed and the stability conditions are presented in the form of linear matrix inequalities that are derived from Lyapunov asymptotic stability and quadratic <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_\infty $ </tex-math></inline-formula> performance. Finally, two simulation cases are carried out with MATLAB/Simulink-Carsim to validate the effectiveness of the proposed method.

Observer-based fuzzy feedback control for nonlinear systems subject to transmission signal quantization

This paper investigates the observer-based quantized output feedback control for a kind of nonlinear discrete-time systems. The system studied in this paper is denoted by a Takagi–Sugeno (T–S) fuzzy model. Under digital communication channels, all transmitted signals between the system and the actuator (including the controller and the observer) will be quantized by the dynamic quantizers in the closed-loop system. Taking into consideration the design of the controller, observer, and dynamic parameters of quantizers, an effective matrix inequality decoupling method is presented to handle the problem. One is shown that the proposed design conditions of the controller, observer, dynamic parameters of quantizers are summarized in a matrix inequality, which can be synthesized synchronously. The resulting design ensures that the quantized closed-loop system can meet the prescribed H∞ performance. Finally, the availability and the feasibility of the presented design method are demonstrated by a mechanical motion system.

Finite-time fuzzy adaptive quantized output feedback control of triangular structural systems

This paper proposes a finite-time fuzzy adaptive quantized control scheme for a class of triangular structural nonlinear systems. Specifically, a smooth function with intermediate control law is introduced in the modified backstepping recursive process to eliminate the effect of quantization. The output constraints issue is solved by employing a barrier Lyapunov function. Then, a command filter is applied to avoid repeatedly differentiating virtual control signals and reduce the computational complexity. Moreover, the proposed method can guarantee that the tracking error converges to a small neighborhood of the origin in the finite time. Finally, the performance and the effectiveness of the proposed method are demonstrated via simulation results.

Synchronization of chaotic Lur’e systems with time-delays via quantized output feedback control

In this paper, the asymptotic stability for chaotic Lur’e systems (CLSs) is studied. A new control method, which involves both state quantizer and control quantizer, is presented. In addition, dynamic parameters of quantizers and controller are designed synchronously to ensure the asymptotic synchronization of the master–slave systems. Moreover, by solving linear matrix inequalities, the corresponding dynamic parameters and control gain can be given. Finally, one numerical simulation and two practical simulations are raised to prove the effectiveness of the control strategy.

Quantized output regulation of minimum‐phase linear uncertain systems

SummaryThis article investigates the robust output regulation problem of a class of minimum‐phase linear uncertain systems subject to limited measurement information. A novel dynamic quantized output feedback control law together with a hybrid quantized feedback control policy is developed. By means of Lyapunov analysis, it is shown that the tracking error tends to zero asymptotically in spite of system uncertainties, disturbances, and limited measurement information. In addition, a special case of the main result leads to the solution of the robust stabilization problem of minimum‐phase linear systems subject to system uncertainties, disturbances, and the quantized output.

Neural observer-based quantized output feedback control for MEMS gyroscopes with guaranteed transient performance

In this paper, a neural observer-based quantized output feedback control with guaranteed transient performance is developed for MEMS gyroscopes. Firstly, to generate piece-wise quantized control signals that can be performed in the digital control system, a hysteresis quantizer (HQ) is employed, meanwhile the undesirable chattering phenomena occurring universally in the traditional non-hysteresis quantizers can be also discarded. Subsequently, to provide prescribed specifications on the transient and steady-state behaviors of output tracking errors, asymmetric preselected boundaries and error transformation functions are constructed to convert the original constrained dynamics into an unconstrained one, such that the predetermined transient and steady-state performance can be achieved. Furthermore, with the aid of presented minimal learning parameter-based neural observer (MLP-NO), not only the unknown disturbances can be online identified, but also the notorious difficulties, known as the excessive occupation of the limited computational resource as well as the restriction of immeasurable velocity states, can be simultaneously circumvented. Also, the stability of resulting control law is analyzed via Lyapunov function and non-smooth analysis technique. The simulation results and comparisons validate the effectiveness of the proposed scheme.

Secure Communication Based on Quantized Synchronization of Chaotic Neural Networks Under an Event-Triggered Strategy.

This article presents a secure communication scheme based on the quantized synchronization of master-slave neural networks under an event-triggered strategy. First, a dynamic event-triggered strategy is proposed based on a quantized output feedback, for which a quantized output feedback controller is formed. Second, theoretical criteria are derived to ensure the bounded synchronization of master-slave neural networks. With these criteria, an explicit upper bound is given for the synchronization error. Sufficient conditions are also provided on the existence of quantized output feedback controllers. A Chua's circuit is chosen to illustrate the effectiveness of our theoretical results. Third, a secure communication scheme is presented based on the synchronization of master-slave neural networks by combining the basic principle of cryptology. Then, a secure image communication is studied to verify the feasibility and security performance of the proposed secure communication scheme. The impact of the quantization level and the event-triggered control (ETC) on image decryption is investigated through experiments.

Robust output regulation of discrete-time linear systems by quantized output feedback control

This technical communique studies the robust output regulation problem of uncertain discrete-time linear systems by quantized output feedback control. We show that, under the same assumptions as those that guarantee the solvability of the robust output regulation problem by a dynamic output feedback control law, our problem is also solvable by a dynamic quantized output feedback control law as long as the quantization density is greater than certain explicitly specified lower bound.

Quantized output feedback control for nonlinear Markovian jump distributed parameter systems with unreliable communication links

This paper investigates robust quantized output feedback control of nonlinear Markovian jump distributed parameter systems (MJDPSs) with incomplete transition rates. Considering the digital communication channel in practical applications, the data of measured output and control input is quantized before transmission, by mode-dependent quantizer. Furthermore, a randomly occurring communication fault phenomenon is noticed in stability analysis, and is described by Bernoulli distributed white sequences. Based on Takagi–Sugeno (T-S) fuzzy model and dynamic parallel distributed compensate principle, a novel output feedback controller is developed. The conditions, to ensure that the MJDPSs are stochastically stable with mixed L2−L∞/H∞ performance, are given in terms of linear matrix inequalities (LMIs), and controller gains can be obtained by LMI toolbox. Finally, an example is provided to illustrate the effectiveness of the proposed method.

Observer-based fuzzy adaptive stabilization of uncertain switched stochastic nonlinear systems with input quantization

This paper proposes an observer-based fuzzy adaptive output feedback control scheme for a class of uncertain single-input and single-output (SISO) nonlinear stochastic systems with quantized input signals and arbitrary switchings. The SISO system under consideration contains completely unknown nonlinear functions, unmeasured system states and quantized input signals quantized by a hysteretic quantizer. By adopting a new nonlinear disposal of the quantized input, the relationship between the control input and the quantized input is established. The hysteretic quantizer that we take can effectively avoid the chattering phenomena. Furthermore, the introduction of a linear observer makes the estimation of the states possible. Based on the universal approximation ability of the fuzzy logic systems (FLSs) and backstepping recursive design with the common stochastic Lyapunov function approach, a quantized output feedback control scheme is constructed, where the dynamic surface control (DSC) is explored to alleviate the computation burden. The proposed control scheme cannot only guarantee the boundedness of signals but also make the output of the system converge to a small neighborhood of the origin. The simulation results are exhibited to demonstrate the validity of the control scheme.

Quantized Output Feedback Control for Stochastic Semi-Markov Jump Systems With Unreliable Links

This brief is concerned with the problem of quantized output feedback (OF) control for semi-Markov jump systems subject to unreliable links. The jump among the operation modes is subject to the semi-Markov process, where the transition probabilities depend not only on the next system mode but the sojourn time at current mode as well. The communication link is considered to be unreliable, in which the packet dropouts described by a stochastic Bernoulli parameter and signal quantization are taken into account simultaneously. The purpose is to synthesize an OF controller, which ensures that the closed-loop system is mean-square $\sigma $ -error stable. Some sojourn time-dependent criteria are established for the realizability of admissible OF controller. With the help of those criteria, the controller gains could be obtained by finding a solution to a convex optimization problem. Finally, both a numerical example and a PWM-driven boost converter are presented to confirm the availability and feasibility of the proposed approach.

Quantized Output Feedback Control of Networked Control Systems with Packet Dropout

This paper considers the quantized dynamic output feedback control of networked control system(NCS) with random packet dropout in both sensor-to-controller and controller-to-actuator channels. The packet losses in the two links are modeled as two independent Markov chains and the NCS is modeled as a Markov jump system. The stochastic switching signal for the quantized output feedback controller is designed to be a function of the number of successive packet loss in both of the two channels. Quantization density varies with the networked load condition. Then a sufficient condition of the stochastic stability with a prescribed H∞ performance level is established based on the Lyapunov-Krasovskii function approach. Furthermore, a quantized output feedback controller is obtained via the cone complement linearization method. Finally, simulation results are provided to verify the effectiveness of the proposed method.

Hybrid Scheduling and Quantized Output Feedback Control for Networked Control Systems

A novel co-design scheme of hybrid scheduling strategy, adaptive logarithmic quantizer and dynamic robust H-infinity output feedback controller for a class of networked control system (NCS)with communication constraints and time delay is proposed. The hybrid scheduling scheme integrates dead zone scheduling and Try Once Discard (TOD) scheduling so as to get the stronger adaptability and flexibility than the single scheduling. In this scheme, dead zone scheduling which updates the threshold according to mode-dependent control strategy is used for single node of NCS to reduce the network bandwidth utilization while TOD scheduling is used for the whole node of NCS in order to meet the requirements of communication constraints and guarantee the overall system performance.We develop the integrated design for the hybrid scheduling strategy, adaptive quantizer and dynamic robust output feedback controller to maintain asymptotic stability of the closed-loop NCS by using the multiple-Lyapunov function and switched system theory. The proposed method can improve the the quality of service (QoS) meanwhile ensure the quality of control (QoC) of overall systems, which make a better trade-off between network utilization and control performance. An simulation example demonstrates the efficiency of the proposed method.

Fuzzy adaptive quantized output feedback tracking control for switched nonlinear systems with input quantization

In this paper, the problem of adaptive fuzzy quantized output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict feedback form. The considered switched systems contain unknown nonlinearities, hysteretic quantized input and without requiring the system states being available for measurement. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a switched fuzzy state observer is designed to estimate the unmeasured states. The hysteretic quantized input is implemented to avoid the oscillation caused by logarithmic quantizer and decomposed into two bounded nonlinear functions. Based on the estimated states and using the backstepping design principle, an adaptive fuzzy quantized output feedback control scheme is developed. It is proved that whole adaptive fuzzy quantized control scheme can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

Robust quantized output feedback control for uncertain discrete time‐delay systems with saturation nonlinearity

SummaryThis paper is concerned with robust quantized output feedback control problems for uncertain discrete‐time systems with time‐varying delay and saturation nonlinearity. It is assumed that the quantizer is of the saturating type. A new framework for the local boundedness stabilization of quantized feedback systems is developed. Attention is focused on finding a quantized static output feedback controller such that all trajectories of the resulting closed‐loop system starting from an admissible initial basin converge to a bounded region strictly within the initial basin. A quantized feedback controller is proposed, which comprises output feedback and the exogenous signal parts. Simulation examples are given to illustrate the effectiveness and advantage of the proposed methods. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Quantized Output Feedback Control of Uncertain Discrete-Time Systems with Input Saturation

This paper deals with the problem of quantized output feedback control for uncertain discrete-time systems with input saturation. Input quantization case and output quantization case are studied, respectively. The purpose of the study was to design of dynamic output feedback controllers such that all the trajectories of the closed-loop system converge to a small ellipsoid for every initial condition starting from large admissible domain. By solving the optimization problem, the corresponding domains can be obtained. Finally, two simulation examples are provided to demonstrate the applicability of the proposed approach.