AQM controller design for networks supporting TCP vegas: a control theoretical approach

In this paper, a mathematical model and control theoretical framework for designing AQM controllers in networks supporting TCP Vegas is introduced. We have emphasized on a modified TCP Vegas algorithm that can respond to congestion signals through explicit congestion notification (ECN). The overall nonlinear delayed differential equations of the dynamics model of closed loop system have been derived based on TCP Vegas model. The model is then linearized to derive a transfer function representation between the packet marking probability and the bottleneck router queue length as the input and output of the modified TCP Vegas/AQM system. The model properties have been then examined especially for the case of single bottleneck homogeneous network which is closely investigated. Finally an AQM controller based on Coefficient Diagram Method (CDM) has been designed for the system and its performance has been compared with some other AQM controllers. CDM is a new indirect pole placement method that considers the speed, stability and robustness of the closed loop system in terms of time domain specifications. In order for synthesizing the simulation scenarios, our campus router traffic has been studied experimentally for a sample period of one hour and the corresponding parameters has been extracted. The simulation results are representative of good performance of developed TCP Vegas/AQM structure for different simulated scenarios.     

Design and analysis of a model predictive controller for active queue management

Model predictive (MP) control as a novel active queue management (AQM) algorithm in dynamic computer networks is proposed. According to the predicted future queue length in the data buffer, early packets at the router are dropped reasonably by the MPAQM controller so that the queue length reaches the desired value with minimal tracking error. The drop probability is obtained by optimizing the network performance. Further, randomized algorithms are applied to analyze the robustness of MPAQM successfully, and also to provide the stability domain of systems with uncertain network parameters. The performances of MPAQM are evaluated through a series of simulations in NS2. The simulation results show that the MPAQM algorithm outperforms RED, PI, and REM algorithms in terms of stability, disturbance rejection, and robustness.     

Adaptive fuzzy funnel congestion control for TCP/AQM network

In this paper, a performance constraint control problem is considered for Transmission Control Protocol/Active Queue Management (TCP/AQM) network with external disturbance and input saturation. On the basis of backstepping-like design procedure and fuzzy approximation technique, an adaptive fuzzy controller with prescribed constraint is achieved to ensure that the transient and steady state performances of the tracking errors can be satisfied. The stability analysis proves that all the signals in the closed-loop system are semi-globally, uniformly and ultimately bounded. The simulation results clarify the feasibility and effectiveness of the proposed approach.     

Design of a new PID controller using predictive functional control optimization for chamber pressure in a coke furnace

An improved proportional-integral-derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers.     

Design of adaptive backstepping congestion controller for TCP networks with UDP flows based on minimax

The congestion control problem of TCP network systems with user datagram protocol (UDP) flows is investigated in this paper. A nonlinear TCP network model with strict-feedback structure is first established. The unknown UDP flow is regarded as the external disturbance, and the maximum UDP flow is calculated by using the minimax approach. And then, a congestion control algorithm is proposed by using the adaptive backstepping approach. Meanwhile, the adaptive law is employed to estimate the unknown link capacity. The design of the adaptive law is to introduce a parameter mapping mechanism to limit the parameter identification range to a specified interval, thereby improving the estimation efficiency of the parameters. Furthermore, a state-feedback congestion controller is presented to make sure that the output of the system tracks the desired queue. The simulation results show the superiority and feasibility of the proposed method.     

A novel dual closed-loop control scheme based on repetitive control for grid-connected inverters with an LCL filter

Grid-connected inverters with LCL filters need high steady-state control accuracy, fast dynamic response performance, and strong robustness to guarantee the power quality. However, there are many problems in traditional control strategies that restrict improvements to control system performance, such as poor dynamic performance of traditional single-repetitive control, large ripples, low steady-state accuracy of inverter current feedback based repetitive dual-loop control or grid-current feedback based single-loop proportional-integral control. In this paper, a novel dual closed-loop repetitive control strategy based on grid current feedback is proposed for single-phase grid-connected inverters with LCL filters. The proportional-integral inner loop is stabilized by using an inherent one-beat delay achieved by digital controller. Based on the inner loop system, a detailed design scheme of a repetitive controller is presented, through which direct control of the grid current is realized, the reference is tracked perfectly to a zero phase shift, and high-attenuation gain is achieved in the high frequency range. In particular, the gird-voltage feed forward control and current reference feedforward control are adopted to suppress grid-voltage disturbance and increase dynamic tracking performance. Finally, the simulation and experimental results show that the proposed method has the advantages of high steady-state accuracy, fast dynamic response, and anti-disturbance ability.     

时变大时滞神经元自适应预测PID控制器

本文提出一种克服时变大时滞,扰主被控制过程参数时变的神经自适应预测ＰＩＤ控制算法。该算法利用预测控制克服时滞,利用智能方法优化ＰＩＤ控制器的参数。     

高性能运动控制器的滑模变结构控制

采用经典PID控制算法的传统运动控制器在受到外部扰动或伺服系统结构参数发生变化时会使系统性能受到影响,运动控制器与数控系统之间低速的ISA总线通信也已无法满足控制器进行复杂的位置控制运算需要大量实时数据传输的要求,降低了运动控制器的控制性能。文章提出在运动控制系统中采用滑模控制算法,减少了外部干扰和系统内部参数变化对系统的影响,提高了系统的鲁棒性 此外,设计中采用PCI总线通信,使数据通信能力显著提高。采用该算法可以有效地克服系统结构参数变化和外部干扰对系统动态响应的影响,明显提高系统的响应速度,同时保持原来系统无超调的要求,使系统具有更好的动态性和较高的鲁棒性,提高了运动控制器的控制性能。     

预测函数控制及其在工业电加热炉中的应用

首先介绍并分析了预测函数控制方法的主要思想和特点,讨论了相应的控制器参数设计方法。进而针对典型的一阶时滞系统,给出了具体的预测函数控制器设计方法,并应用于一工业电加热炉对象的温度控制系统,取得了很好的控制效果。结果表明预测函数控制是一种具有较好控制精度,较快跟踪速度,良好动态特性的控制方法     

Asymptotic stabilization of a class of nonlinear systems with long input delay in the presence of disturbance

Asymptotic stabilization of a class of nonlinear systems with known constant long input delay is addressed in the presence of external disturbance by applying sliding mode control method. Modified prediction variable scheme is employed to compensate long delays in the input, where conventional prediction variable approaches cannot be employed. This is mainly due to the fact that the external disturbance appears in the prediction variable, which renders the controller dependent on the external disturbance. In order to tackle this problem, the nonlinear disturbance observer based predictor is used. A suitable disturbance observer is designed to estimate the external disturbance that appears in the prediction variable. Respected to some existing results, the prediction-based control for more general class of the nonlinear systems in the presence of external disturbance is the main contribution of this paper. Actuator and sensor delays exist in the most common dynamic systems. So, the proposed control scheme can be employed in many conventional systems. The simulation results indicate the robustness and efficiency of the proposed controller.     

大射电望远镜系统输出滞后补偿方法

针对大口径射电望远镜摩擦、间隙和大惯量引起的输出滞后问题,提出了一种输出滞后鲁棒控制器设计方法。首先,根据阶跃响应辨识的思想获得扰动的边界,在此基础上基于稳定性理论,确定出系统的不稳定边界;其次,设计鲁棒控制器使系统的频率响应曲线与禁区无交叉,从而使系统具有鲁棒性和稳定性,该方法的优点在于它是基于稳定性理论设计的无需稳定性证明,且设计简单容易实现,能保证系统在一定范围内发生波动时仍具有较好的控制性能;最后,通过实验验证了文中方法的有效性。     

Robust current control-based generalized predictive control with sliding mode disturbance compensation for PMSM drives

This paper addresses the current control of permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and disturbances. A generalized predictive current control method combined with sliding mode disturbance compensation is proposed to satisfy the requirement of fast response and strong robustness. Firstly, according to the generalized predictive control (GPC) theory based on the continuous time model, a predictive current control method is presented without considering the disturbance, which is convenient to be realized in the digital controller. In fact, it's difficult to derive the exact motor model and parameters in the practical system. Thus, a sliding mode disturbance compensation controller is studied to improve the adaptiveness and robustness of the control system. The designed controller attempts to combine the merits of both predictive control and sliding mode control, meanwhile, the controller parameters are easy to be adjusted. Lastly, the proposed controller is tested on an interior PMSM by simulation and experiment, and the results indicate that it has good performance in both current tracking and disturbance rejection.     

pH过程的FNNC-PI控制研究

在化工、生物及废水处理工程中 ,大量存在着的 p H过程需要得到精确的控制。由于 p H过程是一个具有严重非线性及滞后性的被控对象 ,传统的 PID控制或非线性 PID控制难以达到理想的控制效果。这里给出了一种模糊神经网络控制器与传统 PI相结合的控制方法 ,即 p H过程的 FNNC- PI控制方案 ,该方案能很好地处理 p H过程的严重非线性和滞后性 ,而且具有较强的鲁棒性和抗干扰能力。     

Disturbance-rejection-based tuning of proportional–integral–derivative controllers by exploiting closed-loop plant data

A systematic data-based design method for tuning proportional–integral–derivative (PID) controllers for disturbance attenuation is proposed. In this method, a set of closed-loop plant data are directly exploited without using a process model. PID controller parameters for a control system that behaves as closely as possible to the reference model for disturbance rejection are derived. Two algorithms are developed to calculate the PID parameters. One algorithm determines the optimal time delay in the reference model by solving an optimization problem, whereas the other algorithm avoids the nonlinear optimization by using a simple approximation for the time delay term, enabling derivation of analytical PID tuning formulas. Because plant data integrals are used in the regression equations for calculating PID parameters, the two proposed algorithms are robust against measurement noises. Moreover, the controller tuning involves an adjustable design parameter that enables the user to achieve a trade-off between performance and robustness. Because of its closed-loop tuning capability, the proposed method can be applied online to improve (retune) existing underperforming controllers for stable, integrating, and unstable plants. Simulation examples covering a wide variety of process dynamics, including two examples related to reactor systems, are presented to demonstrate the effectiveness of the proposed tuning method.     

一种新型自动化仪表用高斯基函数网络算法研究

本文提出一种新型基于高斯基函数网络的内模控制自动化仪表用算法,深入分析了高斯基函数网络内部模型和内模控制器的建立,主要结果考虑了形状参数和可变中心向量的自适应选取,仿真及温度实时控制结果表明该算法有效,具有很好的自适应性和鲁棒性,且易于实现并嵌入自动化仪表中,可应用于具有纯滞后,非线性和时变特性的被控过程。     

Modified Smith predictor based cascade control of unstable time delay processes

An improved cascade control structure with a modified Smith predictor is proposed for controlling open-loop unstable time delay processes. The proposed structure has three controllers of which one is meant for servo response and the other two are for regulatory responses. An analytical design method is derived for the two disturbance rejection controllers by proposing the desired closed-loop complementary sensitivity functions. These two closed-loop controllers are considered in the form of proportional-integral-derivative (PID) controller cascaded with a second order lead/lag filter. The direct synthesis method is used to design the setpoint tracking controller. By virtue of the enhanced structure, the proposed control scheme decouples the servo response from the regulatory response in case of nominal systems i.e., the setpoint tracking controller and the disturbance rejection controller can be tuned independently. Internal stability of the proposed cascade structure is analyzed. Kharitonov's theorem is used for the robustness analysis. The disturbance rejection capability of the proposed scheme is superior as compared to existing methods. Examples are also included to illustrate the simplicity and usefulness of the proposed method.     

挖掘机器人伺服系统神经网络滑模控制

挖掘机器人伺服系统存在高度非线性、参数不确定和未建模动态等诸多不利因素,提出了一种结合径向基函数(RBF)神经网络的非线性滑模控制器,以提高控制精度和鲁棒性。首先,建立了单联伺服系统的数学模型;其次,采用RBF神经网络对系统的不利因素进行逼近,提出积分滑模面进一步减小稳态误差,同时减少对伺服系统参数的依赖,在此基础上,设计了基于RBF神经网络的滑模控制器(SMC-RBF),利用Lyapunov理论证明了系统的渐近稳定性;最后,通过不同的参考信号和整平实验验证了控制器的优越性。仿真结果表明,SMC-RBF控制器响应快,跟踪精度高且鲁棒性强,与PID控制器相比正弦轨迹跟踪精度提高了46%。整平实验结果表明,铲斗末端轨迹跟踪精度提高了52%。     

A simple nonlinear PD controller for integrating processes

Many industrial processes are found to be integrating in nature, for which widely used Ziegler–Nichols tuned PID controllers usually fail to provide satisfactory performance due to excessive overshoot with large settling time. Although, IMC (Internal Model Control) based PID controllers are capable to reduce the overshoot, but little improvement is found in the load disturbance response. Here, we propose an auto-tuning proportional-derivative controller (APD) where a nonlinear gain updating factor α continuously adjusts the proportional and derivative gains to achieve an overall improved performance during set point change as well as load disturbance. The value of α is obtained by a simple relation based on the instantaneous values of normalized error (e_N) and change of error (Δe_N) of the controlled variable. Performance of the proposed nonlinear PD controller (APD) is tested and compared with other PD and PID tuning rules for pure integrating plus delay (IPD) and first-order integrating plus delay (FOIPD) processes. Effectiveness of the proposed scheme is verified on a laboratory scale servo position control system.     

一种二自由度内模控制方法

针对典型的工业过程控制对象，提出了一种二自由度内模控制方法，此方法可以使系统同时具有良好的目标值跟踪特性，干扰抑制特性和鲁棒性，改进了常规内模控制的不足，而且控制算法简单，参数调整方便，理论分析和仿真实验结果表明了它的有效性。