深孔钻削刀具系统磁流变制振器设计及其动态性能研究

依据实际深孔钻削刀具系统的结构布局及其振动特征,设计了一种新型刀具系统制振器的结构布局形式。以制振器理想输出阻尼力和内磁感应强度达到饱和为设计目标,给出了磁流变制振器结构的优化设计方法及其具体结构参数;运用有限元法,分析了新型制振器的磁场分布特征及其输出阻尼特征。以此为基础,通过深孔钻削实验研究,获得了不同励磁电流和切削参数条件下刀具振动的抑制效果,验证了所提出的新型磁流变制振构型的可行性和有效性。

基于事件驱动型传感器网络的跑道入侵防御

为避免在机场发生航空器/车辆入侵跑道,将事件驱动型传感器网络引入跑道入侵防御系统中,通过对传感器网络获取的目标探测信息实施融合重建跑道运行态势。根据跑道运行过程建立基于Petri网的场面活动模型,定义跑道入侵控制规范将跑道入侵探测与避免问题转化为状态禁止问题。针对模型存在的不可控事件,通过计算满足强控制规范条件的控制率实现逻辑控制器的设计,并证明该逻辑控制器是极大允许。案例研究表明,控制器通过跑道入口停止排灯和滑行管制指令实现跑道入侵防御,该监控算法的复杂度仅与传感器网络节点的布局而非与航空器/车辆的数量有关。

PID Controller Design Based on the Time Domain Information of Robust IMC Controller Using Maximum Sensitivity

The IMC(Internal Model Control) controller based on robust tuning can improve the robustness and dynamic performance of the system.In this paper,the robustness degree of the control system is investigated based on Maximum Sensitivity(Ms) in depth.And the analytical relationship is obtained between the robustness specification and controller parameters,which gives a clear design criterion to robust IMC controller.Moreover,a novel and simple IMC-PID(Proportional-Integral-Derivative) tuning method is proposed by converting the IMC controller to PID form in terms of the time domain rather than the frequency domain adopted in some conventional IMC-based methods.Hence,the presented IMC-PID gives a good performance with a specific robustness degree.The new IMC-PID method is compared with other classical IMC-PID rules,showing the flexibility and feasibility for a wide range of plants.

Cascade control based on minimum sensitivity in outer loop for processes with time delay

A new cascade control program was proposed based on modified internal model control to handle stable,unstable and integrating processes with time delay.The program had totally four controllers of which the secondary loop had two controllers and the primary loop had two controllers.The two secondary loop controllers were designed using IMC technique.They were decoupled completely and could be adjusted independently,which avoided the undesirable influence on performance of the primary controllers.The main controller in the primary loop was devised as a PID using the method of minimum sensitivity,which could guarantee not only the nominal performance but also the robust stability of the system.A setpoint filter was added in the primary loop to improve the tracking performance.All the controllers of the two closed-loops were designed analytically,and could be adjusted and optimized by single parameter respectively.Simulations were carried out on three various processes with time delay,and the results show that the proposed method can provide a better performance of both set-point tracking and disturbance rejection and robustness against parameters perturbation.

Improved H_∞ control for networked control systems with network-induced delay and packet dropout

The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that the sensor is time-driven and the logic Zero-order-holder(ZOH) and controller are event-driven.Based on this model,the delay interval is divided into two equal subintervals for H_∞ performance analysis.An improved H_∞ stabilization condition is obtained in linear matrix inequalities(LMIs) framework by adequately considering the information about the bounds of the input delay to construct novel Lyapunov–Krasovskii functionals(LKFs).For the purpose of reducing the conservatism of the proposed results,the bounds of the LKFs differential cross terms are properly estimated without introducing any slack matrix variables.Moreover,the H_∞ controller is reasonably designed to guarantee the robust asymptotic stability for the linear NCSs with an H_∞ performance level γ.Numerical simulation examples are included to validate the reduced conservatism and effectiveness of our proposed method.

A new robust fuzzy method for unmanned flying vehicle control

A new general robust fuzzy approach was presented to control the position and the attitude of unmanned flying vehicles(UFVs). Control of these vehicles was challenging due to their nonlinear underactuated behaviors. The proposed control system combined great advantages of generalized indirect adaptive sliding mode control(IASMC) and fuzzy control for the UFVs. An on-line adaptive tuning algorithm based on Lyapunov function and Barbalat lemma was designed, thus the stability of the system can be guaranteed. The chattering phenomenon in the sliding mode control was reduced and the steady error was also alleviated. The numerical results, for an underactuated quadcopter and a high speed underwater vehicle as case studies, indicate that the presented adaptive design of fuzzy sliding mode controller performs robustly in the presence of sensor noise and external disturbances. In addition, online unknown parameter estimation of the UFVs, such as ground effect and planing force especially in the cases with the Gaussian sensor noise with zero mean and standard deviation of 0.5 m and 0.1 rad and external disturbances with amplitude of 0.1 m/s2 and frequency of 0.2 Hz, is one of the advantages of this method. These estimated parameters are then used in the controller to improve the trajectory tracking performance.

Design considerations for the improved current-doubler-rectifier ZVS PWM full-bridge converter

The improved current-doubler-rectifier zero-voltage-switching PWM full-bridge converter (CDR ZVS PWM FB converter) achieves ZVS for the switches in a wide load range with the use of the energy stored in the output filter inductances, and the rectifier diodes commute naturally, therefore no oscillation and voltage spike occurs. The transformer needs no special manufacture method to limit the leakage inductance. The ZVS achievement and the design considerations for the output filter inductances and the blocking capacitor are discussed for the improved CDR ZVS PWM FB converter. A 540 W prototype converter is built in the lab to verify the operational principle and design considerations for the improved converter, the experimental results are also included.

Nonlinear decoupling controller design based on least squares support vector regression

Support Vector Machines (SVMs) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on a method of least squares SVM (LS-SVM) for multivariate function estimation, a generalized inverse system is developed for the linearization and decoupling control of a general nonlinear continuous system. The approach of inverse modelling via LS-SVM and parameters optimization using the Bayesian evidence framework is discussed in detail. In this paper, complex high-order nonlinear system is decoupled into a number of pseudo-linear Single Input Single Output (SISO) subsystems with linear dynamic components. The poles of pseudo-linear subsystems can be configured to desired positions. The proposed method provides an effective alternative to the controller design of plants whose accurate mathematical model is un- known or state variables are difficult or impossible to measure. Simulation results showed the efficacy of the method.

Robust Non-fragile PID Controller Design for the Stroke Regulation of Metering Pumps

This job focuses on the stroke regulation of a class of high-precision metering pumps.A parametertuning method of robust non-fragile PID（proportional-integral-derivative）controllers is proposed with the assumption that a PID controller has additive gain perturbations.An H-infinite robust PID controller can be obtained by solving a linear matrix inequality.This approach can guarantee that the closed-loop control systems is asymptotically stable and the H-infinite norm of the transfer function from the disturbance to the output of a controlled system is less than a given constant to attenuate disturbances.The simulation case shows that the control performance of the proposed strategy is significantly better than the traditional PID approach in the situation with perturbations of controller parameters.

Linearization of T-S fuzzy systems and robust H_∞ control

Takagi-Sugeno(T-S) fuzzy model is difficult to be linearized because of membership functions included.So,novel T-S fuzzy state transformation and T-S fuzzy feedback are proposed for the linearization of T-S fuzzy system.The novel T-S fuzzy state transformation is the fuzzy combination of local linear transformation which transforms local linear models in the T-S fuzzy model into the local linear controllable canonical models.The fuzzy combination of local linear controllable canonical model gives controllable canonical T-S fuzzy model and then nonlinear feedback is obtained easily.After the linearization of T-S fuzzy model,a robust H∞ controller with the robustness of sliding model control(SMC) is designed.As a result,controlled T-S fuzzy system shows the performance of H∞ control and the robustness of SMC.

Model Predictive Controller Design for the Dynamic Positioning System of a Semi-submersible Platform

This paper researches how to apply the advanced control technology of model predictive control （MPC） to the design of the dynamic positioning system （DPS） of a semi-submersible platform. First, a linear low-frequency motion model with three degrees of freedom was established in the context of a semi-submersible platform. Second, a model predictive controller was designed based on a model which took the constraints of the system into account. Third, simulation was carried out to demonstrate the feasibility of the controller. The results show that the model predictive controller has good performance and good at dealing with the constraints or the system.

H_∞ Robust Fault-Tolerant Controller Design for an Autonomous Underwater Vehicle’s Navigation Control System

In order to improve the security and reliability for autonomous underwater vehicle （AUV） navigation, an H∞ robust fault-tolerant controller was designed after analyzing variations in state-feedback gain Operating conditions and the design method were then analyzed so that the control problem could be expressed as a mathematical optimization problem. This permitted the use of linear matrix inequalities （LMI） to solve for the Hv controller for the system. When considering different actuator failures, these conditions were then also mathematically expressed, allowing the H∞ robust controller to solve for these events and thus be fault-tolerant. Finally, simulation results showed that the H∞ robust fault-tolerant controller could provide precise AUV navigation control with strong robustness.

Adaptive controller design based on input-output signal selection for voltage source converter high voltage direct current systems to improve power system stability

An input-output signal selection based on Phillips-Heffron model of a parallel high voltage alternative current/high voltage direct current(HVAC/HVDC) power system is presented to study power system stability. It is well known that appropriate coupling of inputs-outputs signals in the multivariable HVDC-HVAC system can improve the performance of designed supplemetary controller. In this work, different analysis techniques are used to measure controllability and observability of electromechanical oscillation mode. Also inputs–outputs interactions are considered and suggestions are drawn to select the best signal pair through the system inputs-outputs. In addition, a supplementary online adaptive controller for nonlinear HVDC to damp low frequency oscillations in a weakly connected system is proposed. The results obtained using MATLAB software show that the best output-input for damping controller design is rotor speed deviation as out put and phase angle of rectifier as in put. Also response of system equipped with adaptive damping controller based on HVDC system has appropriate performance when it is faced with faults and disturbance.

Pressure-tracking control of a novel electro-hydraulic braking system considering friction compensation

This work presents an integrated pressure-tracking controller for a novel electro-hydraulic brake(EHB) system considering friction and hydraulic disturbances. To this end, a mathematical model of an EHB system, consisting of actuator and hydraulic sub-systems, is derived for describing the fundamental dynamics of the system and designing the controller. Due to sensor inaccuracy and measurement noise, a Kalman filter is constructed to estimate push rod stroke for generating desired master cylinder pressure. To improve pressure-tracking accuracy, a linear friction model is generated by linearizing the nonlinear Tustin friction model, and the unmodeled friction disturbances are assumed unknown but bounded. A sliding mode controller is designed for compensating friction disturbances, and the stability of the controller is investigated using the Lyapunov method. The performance of the proposed integrated controller is evaluated with a hardware-in-the-loop(HIL) test platform equipped with the EHB prototype. The test results demonstrate that the EHB system with the proposed integrated controller not only achieves good pressure-tracking performance, but also maintains robustness to friction disturbances.

Terminal Sliding Mode Fuzzy Control Based on Multiple Sliding Surfaces for Nonlinear Ship Autopilot Systems

A terminal sliding mode fuzzy control based on multiple sliding surfaces was proposed for ship course tracking steering, which takes account of rudder characteristics and parameter uncertainty. In order to solve the problem, the controller was designed by employing the universal approximation property of fuzzy logic system, the advantage of Nussbaum function, and using multiple sliding mode control algorithm based on the recursive technique. In the last step of designing, a nonsingular terminal sliding mode was utilized to drive the last state of the system to converge in a finite period of time, and high-order sliding mode control law was designed to eliminate the chattering and make the system robust. The simulation results showed that the controller designed here could track a desired course fast and accurately. It also exhibited strong robustness peculiarly to system, and had better adaptive ability than traditional PID control algorithms.

Multi-loop Constrained Iterative Model Predictive Control Using ARX -PLS Decoupling Structure

A multi-loop constrained model predictive control scheme based on autoregressive exogenous-partial least squares(ARX-PLS) framework is proposed to tackle the high dimension, coupled and constraints problems in industry processes due to safety limitation, environmental regulations, consumer specifications and physical restriction. ARX-PLS decoupling character enables to turn the multivariable model predictive control(MPC) controller design in original space into the multi-loop single input single output(SISO) MPC controllers design in latent space.An idea of iterative method is applied to decouple the constraints latent variables in PLS framework and recursive least square is introduced to identify ARX-PLS model. This algorithm is applied to a non-square simulation system and a stirred reactor for ethylene polymerizations comparing with adaptive internal model control(IMC) method based on ARX-PLS framework. Its application has shown that this method outperforms adaptive IMC method based on ARX-PLS framework to some extent.

A new wide area damping controller design method considering signal transmission delay to damp interarea oscillations in power system

Wide area damping controller(WADC) is usually utilized to damp interarea low frequency oscillation in power system. However, conventional WADC design method neglects the influence of signal transmission delay and damping performance of WADC designed by the conventional method may deteriorate or even has no effect when signal transmission delay is beyond delay margin, an index that denotes delay endurance degree of power system. Therefore, a new design method for WADC under the condition of expected damping factor and required signal transmission delay is presented in this work. An improved delay margin with less conservatism is derived by adopting a new Lyapunov-Krasovskii function and more compact bounding technique on the derivative of Lyapunov-Krasovskii functional. The improved delay margin, which constructs the correlation of damping factor and signal transmission delay, can be used to design WADC. WADC designed by the proposed method can ensure that power system satisfies expected damping factor when WADC input signal is delayed within delay margin. Satisfactory test results demonstrate the effectiveness of the proposed method.

Development of Linearizing Feedback Control with a Variable Structure Observer for Continuous Stirred Tank Reactors

This paper deals with the design of an observer-based nonlinear control for continuous stirred tank reactors(CSTR).A variable structure observer is constructed to estimate the whole process state variables.This observer is basically the conventional Luenberger observer with an additional switching term used to guarantee the robustness against modeling errors.The observer is coupled with a nonlinear controller,designed based on input-output linearization for controlling the reactor temperature.The asymptotical stability of the closed-loop system is shown by the Lyapunov stability theorem.Finally,computer simulations are developed for showing the performance of the proposed approach.

Using Lyapunov function to design optimal controller for AQM routers

It was shown that active queue management schemes implemented in the routers of communication networks sup-porting transmission control protocol (TCP) flows can be modelled as a feedback control system. In this paper based on Lyapunov function we developed an optimal controller to improve active queue management (AQM) router’s stability and response time, which are often in conflict with each other in system performance. Ns-2 simulations showed that optimal controller outperforms PI controller significantly.

Partially Decentralized Controller Design via Model Predictive Control

An expansion procedure to design partially decentralized controllers via model predictive control is proposed in this paper. Partially decentralized control is a control structure that lies between a fully decentralized structure and a fully centralized one, and has the advantage of achieving comparable performance as a fully centralized controller but with simpler structure. The proposed method follows the expansion method proposed in a previous paper where internal model control (IMC) was used to design controllers for non-square subsystems. The method requires computing the pseudo-inverse of a non-square matrix via pseudo-inverse factors. Instead, the proposed method uses dynamic matrix control (DMC) to design PID controllers for non-square subsystems without using additional factors. The effectiveness of the proposed method is demonstrated on several chemical examples. Simulation results show that the proposed method is simple and can achieve better performance.