Event-triggered consensus control of disturbed multi-agent systems using output feedback

In this article, the event-triggered consensus control is investigated for general linear multi-agent systems with external disturbances, by using the accessible measurement outputs. In particular, a novel protocol is proposed using the local observed state variables at event-triggered instants, which are respectively derived by adopting an observer to each agent based on output signal. Then it is proved that under the designed event-triggered control protocol consensus can be achieved with the desired disturbance attenuation ability and no Zeno behavior occurs. A numerical simulation is given to demonstrate the effectiveness of the developed control strategy     

H∞ observer-based event-triggered sliding mode control for a class of discrete-time nonlinear networked systems with quantizations

This paper investigates the problem of H_∞ observer-based event-triggered sliding mode control (SMC) for a class of uncertain discrete-time Lipschitz nonlinear networked systems with quantizations occurring in both input and output channels. The event-triggered strategy is used to save the limited network bandwidth. Then, based on the zero-order-hold (ZOH) measurement, a state observer is designed to reconstruct the system state, which facilitates the design of the discrete-time sliding surface. Considering the effects of quantizations, networked-induced constraints and event-triggered scheme, the nonlinear state error dynamics and sliding mode dynamics are converted into a unified linear parameter varying (LPV) time-delay system with the aid of a reformulated Lipschitz property. By using the Lyapunov-Krasovskii functional and free weighting matrix, a new sufficient condition is derived to guarantee the robust asymptotic stability of the resulting closed-loop system with prescribed H_∞ performance. And then the observer gain, event-triggering parameter and sliding mode parameter are co-designed. Furthermore, a novel SMC law is synthesized to force the trajectories of the observer system onto a pre-specified sliding mode region in a finite time. Finally, a single-link flexible joint robot example is utilized to demonstrate the effectiveness of the proposed method.     

H∞ output-feedback fuzzy proportional-integral control of fully delayed input/output systems

This paper presents the output-feedback fuzzy proportional-integral (PI) controller design for uncertain nonlinear systems with both fully delayed input and output. Based on the Takagi–Sugeno (T–S) fuzzy model representation, the output-feedback PI control is realized via parallel distributed PI compensation and novel LMI gain design. Although the T–S fuzzy PI controller is simple, asymptotic output regulation is assured to overcome the effect of uncertainty, state delay, and full input/output delays. When considering disturbance and measurement noise, the control performance is achieved by robust gain design. Furthermore, state observers and bilinear matrix inequality conditions are removed in this paper. Finally, time-delay Chua׳s circuit system and a continuous-time stirred tank reactor are taken as applications to show the expected performance.     

Sampled-data control for linear time-delay distributed parameter systems

Some real systems have spatiotemporal dynamics and are time-delay distributed parameter systems (DPSs). The existence of time-delay may lead to system instability. The analysis and design of DPSs with time-delay is essentially more complicated. To take into account the factor of time-delay and fully enjoy the benefits of the digital technology in control engineering, it is a theoretical and practical value to consider the sampled-data control (SDC) problem of DPSs with time-delay. However, there are few attempts to solve the SDC problem of time-delay DPSs. In this paper, we introduce a SDC for linear time-delay DPSs described by parabolic partial differential equations (PDEs). A SDC design is developed in the formulation of spatial linear matrix inequalities (LMIs) by constructing an appropriate Lyapunov functional, which can stabilize exponentially the time-delay DPSs. This stabilization condition can be applied to either slowing-varying time delay or fast-varying one. Finally, simulation results of a numerical example are provided to illustrate the effectiveness of the proposed method.     

Static output feedback stabilization of networked control systems with a parallel-triggered scheme

This paper investigates the parallel-triggered static output feedback stabilization problem for linear networked control systems. A new parallel-triggered scheme is proposed by using both the relative error and the absolute error information. The scheme can reduce transmission rate while maintaining the global asymptotical stability. The linear parallel-triggered networked control system is modeled as a time-delay system. By employing Lyapunov stability theory, sufficient conditions are established for the closed-loop system to be globally asymptotically stable in terms of linear matrix inequalities. Moreover, a co-design algorithm is developed to obtain both the optimal trigger parameters and the output feedback controller gain in the sense that the transmission rate is minimized. Finally, two examples are given to illustrate the advantages of the proposed scheme.     

Event-triggered adaptive control of a class of nonlinear systems

In this paper, the event-triggered adaptive control for a class of nonlinear systems in Brunovsky form is considered. The sensors are event-triggered thus the states are transmitted only at the discrete triggering points, which are more efficient in using communication bandwidth. To solve this problem, we design a set of event-triggered conditions and based on which the controller and parameter estimator are designed without the ISS assumption. It is shown that the proposed control schemes guarantee that all the closed-loop signals are semi-globally bounded and the stabilization error converges to the origin asymptotically. The Zeno behavior is also excluded. Simulation results illustrate the effectiveness of our scheme.     

Finite-time decentralized adaptive neural constrained control for interconnected nonlinear time-delay systems with dynamics couplings among subsystems

The problem of finite-time decentralized neural adaptive constrained control is studied for large-scale nonlinear time-delay systems in the non-affine form. The main features of the considered system are that 1) unknown unmatched time-delay interactions are considered, 2) the couplings among the nested subsystems are involved in uncertain nonlinear systems, 3) based on finite-time stability approach, asymmetric saturation actuators and output constraints are studied in large-scale systems. First, the smooth asymmetric saturation nonlinearity and barrier Lyapunov functions are used to achieve the input and output constraints. Second, the appropriately designed Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. Note that, due to unknown time-delay interactions and the couplings among subsystems, the controller design is more meaningful and challenging. At last, based on finite-time stability theory and Lyapunov stability theory, a decentralized adaptive controller is proposed, which decreases the number of learning parameters. It is shown that the designed controller can ensure that all closed-loop signals are bounded and the tracking error converges to a small neighborhood of the origin. The simulation studies are presented to show the effectiveness of the proposed method.     

Event-triggered control design of linear networked systems with quantizations

This paper is concerned with the control design problem of event-triggered networked systems with both state and control input quantizations. Firstly, an innovative delay system model is proposed that describes the network conditions, state and control input quantizations, and event-triggering mechanism in a unified framework. Secondly, based on this model, the criteria for the asymptotical stability analysis and control synthesis of event-triggered networked control systems are established in terms of linear matrix inequalities (LMIs). Simulation results are given to illustrate the effectiveness of the proposed method.     

Delay-dependent guaranteed-cost control based on combination of Smith predictor and equivalent-input-disturbance approach

This paper presents a new system configuration and a design method to improve control performance for a system with an input time delay and disturbances. The equivalent-input-disturbance approach is extended to handle a time-delay system. It is combined with the Smith predictor to reject disturbances. A delay-dependent stability condition is devised in terms of a matrix inequality by using the free-weighting matrix approach. The gain of the observer is designed by applying the cone complementary linearization method to the matrix inequality. A numerical example demonstrates the validity of the method.     

一种克服模型参数失配的广义预测控制算法

针对模型参数失配对广义预测控制输出的影响,提出了一种输出增量反馈的广义预测控制简化算法.该算法通过引入一个输出增量速度函数,设计了输出增量参考序列,以控制输出增量的方式间接控制系统输出;同时利用阶梯控制方式,对输入增量引入柔化系数矩阵进行约束,既避免了传统预测控制律中逆矩阵的求解,减少了计算量,又防止了控制量的剧烈变化;最后引入控制增量增益,利用这个自由度提高了系统的鲁棒稳定性.仿真结果表明:该预测控制简化算法能有效克服模型参数失配带来的影响,抑制系统输出调整过程中的输出波动,缩短调整时间,提高系统的动态特性,并抑制系统控制输入的剧烈变化.     

Global adaptive output feedback control for a class of nonlinear time-delay systems

This paper addresses the problem of global output feedback control for a class of nonlinear time-delay systems. The nonlinearities are dominated by a triangular form satisfying linear growth condition in the unmeasurable states with an unknown growth rate. With a change of coordinates, a linear-like controller is constructed, which avoids the repeated derivatives of the nonlinearities depending on the observer states and the dynamic gain in backstepping approach and therefore, simplifies the design procedure. Using the idea of universal control, we explicitly construct a universal-type adaptive output feedback controller which globally regulates all the states of the nonlinear time-delay systems.     

基于灰色预测的无模型控制在球磨机负荷控制中的仿真研究

火电厂钢球磨煤机的负荷对象具有大滞后、慢时变、强非线性等复杂特性,采用常规控制方法难以获得满意的控制效果,本文提出了基于灰色预测的无模型自适应负荷控制方法.该方法融合了无模型控制的自适应、抗干扰特性与灰色预测模型的预测时延、抑制超调和快速稳定特性,它将灰色模型的预测结果代替负荷对象输出测量值,再进行无模型自适应闭环控制.仿真结果表明这种控制方法系统响应快、超调小、鲁棒性好、抗干扰能力强,可以有效解决大滞后、非线性及适应性等问题.     

大滞后系统的Smith在线辨识预估控制的研究

工业过程中普遍存在大时滞对象,为解决大滞后复杂系统因无法建立精确数学模型而难于控制的问题,将史密斯(Smith)预估控制原理和在线辨识方法结合起来,在Smith预估控制系统中,用系统辨识的模型代替传统预估补偿模型,根据最小二乘辨识算法辨识模型的各个参数,提出了Smith在线辨识预估控制算法;针对二阶加纯滞后对象在滞后时间有/无建模误差进行了仿真研究。研究结果表明,Smith在线辨识预估控制的性能指标和鲁棒性有很大的改善。     

Event-triggered reliable control for fuzzy Markovian jump systems with mismatched membership functions

The problem of event-triggered reliable control for fuzzy Markovian jump system (FMJS) with mismatched membership functions (MMFs) is addressed. Based on the mode-dependent reliable control and event-triggered communication scheme, the stability conditions and control design procedure are formulated. More precisely, a general actuator-failure is designed such that the FMJS is reliable in the sense of stochastically stable and reduce the utilization of network resources. Furthermore, the improved MMFs are introduced to reduce the conservativeness of obtained results. Finally, simulation results indicate the effectiveness of the proposed methodology.     

阳极焙烧排烟架的模糊PID复合控制

阳极焙烧系统是一个具有耦合、大时滞、非线性的控制系统,其中排烟架是阳极焙烧系统的重要组成部分。针对系统存在的滞后及时变问题,该文采用稳态、动态性能较好的复合模糊控制器对其进行控制。通过仿真及运行的结果可以表明,复合模糊控制效果明显优于传统的PID控制,提高了控制系统的稳定性和鲁棒性。     

Adaptive predictive functional control of a class of nonlinear systems

This paper describes the use of pseudo-partial derivative (PPD) to dynamically linearize a nonlinear system, and aggregation is applied to the predicted PPD, resulting in a model-free adaptive predictive control algorithm for a nonlinear system. The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection.     

Multivariable control of grinding plants: a comparative simulation study

In this paper five multivariable adaptive and classical control strategies have been studied and implemented in a simulator of the copper grinding plant of CODELCO-Andina. The strategies presented were compared and, according to theory, exhibit good behavior. The extended horizon, pole-placement and model reference multivariable adaptive control strategies were formulated in discrete-time and use a model of the plant whose parameters are updated on line using the recursive least squares method along with UD factorization of the covariance matrix and variable forgetting factor. The direct Nyquist array and sequential loop closing techniques were also studied and simulated. The two-by-two multivariable system chosen to represent the grinding plant has the percentage of solids (density) of the pulp fed to the hydrocyclones (which is highly correlated with the percentage of +65 mesh in the overflow of hydrocyclones) and the sump level as output (controlled) variables. The water flow added to the sump and the speed of the pump are its input (manipulated) variables. All the algorithms tested by simulation exhibited good performance and were able to control the grinding plant in a stable fashion. Adaptive algorithms showed better performance than classical techniques, with the extended horizon and pole-placement algorithms proving to be the best. The fact that adaptive algorithms continuously adjust their parameters renders such controllers superior to those based on fixed parameters.     

H∞ non-fragile observer-based dynamic event-triggered sliding mode control for nonlinear networked systems with sensor saturation and dead-zone input

This paper considers the problem of robust non-fragile observer-based dynamic event-triggered sliding mode control (SMC) for a class of discrete-time Lipschitz nonlinear networked control systems subject to sensor saturation and dead-zone input nonlinearity. First, an improved dynamic event-triggered scheme (DETS) in consideration of sensor saturation is proposed to reduce the number of data transmission. Next, a non-fragile observer is designed to estimate the system state, which facilitates the construction of the discrete sliding surface. By using a reformulated Lipschitz property, the error dynamics and sliding mode dynamics are modeled as a unified linear parameter varying (LPV) networked system with time-varying delays. Then, based on this model, sufficient conditions are established to guarantee the resulting closed-loop system to be asymptotically stable with a given disturbance attenuation level. Furthermore, an observer-based event-triggered SMC law is designed to drive the trajectories of the observer system onto a region near equilibrium point in a finite time in the presence of dead-zone input nonlinearity. Finally, two practical examples are employed to demonstrate the effectiveness of the proposed method.