分布式群体在动态系统控制决策中的内隐学习

采用计算机网络模拟技术 ,考察分布式群体在动态系统控制决策过程中对系统规则的内隐学习效应及其迁移。结果表明 ,在决策者的显性规则知识量极少且没有增加的情况下 ,决策绩效随决策进程适应性提高。决策者所能报告的规则知识量与决策绩效的相关也不显著。同时 ,当决策任务目标转换时 ,决策的高绩效得以维持。这表明群体决策者能对动态系统规则进行内隐学习 ,且能正迁移到类似的决策情景中。研究进一步指出 。

一类连续模糊动态系统控制方法在Furuta摆中的应用

为了研究 Furuta 摆在倒立点附近的稳定控制问题,采用基于 T-S 模糊模型的一类连续模糊动态系统控制方法,首次进行 Furuta 摆的模糊状态空间建模,并采用模糊切换的思想,设计了 Furuta 摆在倒立点附近的稳定控制器,进而分析了系统稳定性。与已有的方法相比,该方法的优点是稳定区域大、调节时间短。数字仿真结果验证了方法的有效性。

具有控制约束的动态投入产出与经济系统最优控制

研究基于动态投入产出理论的确定性线性经济系统控制模型.对于具有控制积分不等式约束的二次型性能指标的经济系统给出了最优调节规律和最小的经济损耗.

Robust adaptive dynamic surface control for nonlinear uncertain systems

We propose a new method for robust adaptive backstepping control of nonlinear systems with parametric uncertainties and disturbances in the strict feedback form. The method is called dynamic surface control. Traditional backstepping algorithms require repeated differentiations of the modelled nonlinearities. The addition of n first order low pass filters allows the algorithm to be implemented without differentiating any model nonlinearities, thus ending the complexity arising due to the 'explosion of terms' that makes other methods difficult to implement in practice. The combined robust adaptive backstepping/first order filter system is proved to be semiglobally asymptotically stable for sufficiently fast filters by a singular perturbation approach. The simulation results demonstrate the feasibility and effectiveness of the controller designed by the method.

面对入世 以动应变

加入WTO后,我国公安机关将面临新的执法环境,需要建立动态管理系统控制模式,运用科学的管理方法和手段使管理系统处于最优化状态,从而保障公安管理系统能够适应不断变化的执法环境。

Control uncertain continuous－time chaotic dynamical system

The new chaos control method presented in this paper is useful for taking advantage of chaos.Based on sliding mode control theory, this paper provides a switching manifold controlling strategy of chaoticsystem, and also gives a kind of adaptive parameters estimated method to estimate the unknown systems' pa-rameters by which chaotic dynamical system can be synchronized. Taking the Lorenz system as example, and with the help of this controlling strategy, we can synchronize chaotic systems with unknown parameters and different initial conditions.

Constraints Adjustment and Objectives Coordination of Satisfying Optimal Control Applied to Heavy Oil Fractionators

In this paper, the feasibility and objectives coordination of real-time optimization (RTO) are systemically investigated under soft constraints. The reason for requiring soft constraints adjustment and objective relaxation simultaneously is that the result is not satisfactory when the feasible region is apart from the desired working point or the optimization problem is infeasible. The mixed logic method is introduced to describe the priority of the constraints and objectives, thereby the soft constraints adjustment and objectives coordination are solved together in RTO. A case study on the Shell heavy oil fractionators benchmark problem illustrating the method is finally presented.

Consensus tracking protocol and formation control of multi-agent systems with switching topology

Consensus tracking control problems for single-integrator dynamics of multi-agent systems with switching topology are investigated. In order to design effective consensus tracking protocols for a more general class of networks, which are aimed at ensuring that the concerned states of agents converge to a constant or time-varying reference state, new consensus tracking protocols with a constant and time-varying reference state are proposed, respectively. Particularly, by contrast with spanning tree, an improved condition of switching interaction topology is presented. And then, convergence analysis of two consensus tracking protocols is provided by Lyapunov stability theory. Moreover, consensus tracking protocol with a time-varying reference state is extended to achieve the fbrmation control. By introducing formation structure set, each agent can gain its individual desired trajectory. Finally, several simulations are worked out to illustrate the effectiveness of theoretical results. The test results show that the states of agents can converge to a desired constant or time-varying reference state. In addition, by selecting appropriate structure set, agents can maintain the expected formation under random switching interaction topologies.

Sliding mode identifier for parameter uncertain nonlinear dynamic systems with nonlinear input

This paper presents a sliding mode (SM) based identifier to deal with the parameter identification problem for a class of parameter uncertain nonlinear dynamic systems with input nonlinearity. A sliding mode controller (SMC) is used to ensure the global reaching condition of the sliding mode for the nonlinear system; an identifier is designed to identify the uncertain parameter of the nonlinear system. A numerical example is studied to show the feasibility of the SM controller and the asymptotical convergence of the identifier.

Linear and nonlinear control of a robotic excavator

Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.

Passive control of Permanent Magnet Synchronous Motor chaotic system based on state observer

Passive system theory was applied to propose a new passive control method with nonlinear observer of the Permanent Magnet Synchronous Motor chaotic system. Through constructing a Lyapunov function, the subsystem of the Permanent Magnet Synchronous Motor chaotic system could be proved to be globally stable at the equilibrium point. Then a controller with smooth state feedback is designed so that the Permanent Magnet Synchronous Motor chaotic system can be equivalent to a passive system. To get the state variables of the controller, the nonlinear observer is also studied. It is found that the outputs of the nonlinear observer can approximate the state variables of the Permanent Magnet Synchronous Motor chaotic system if the system’s nonlinear function is a globally Lipschitz function. Simulation results showed that the equivalent passive system of Permanent Magnet Synchronous Motor chaotic system could be globally asymptotically stabilized by smooth state feedback in the observed parameter convergence condition area.

Semi-active predictive control strategy for seismically excited structures using MRF-04K dampers

The theoretical study of a semi-active predictive control(SAPC) system with magnetorheological(MR) dampers to reduce the responses of seismically excited structures was presented.The SAPC scheme is based on a prediction model of the system response to obtain the control actions by minimizing an object function,which has a function of self-compensation for time delay occurring in real application.A double-ended shear mode combined with a valve mode MR damper,named MRF-04K damper,with the maximum force of 20 kN was designed and manufactured,and parameters of the Bouc-Wen hysteresis model were determined to portray the behavior of this damper.As an example,a 5-story building frame equipped with 2 MRF-04K dampers was presented to demonstrate the performance of the proposed SAPC scheme for addressing time delay and reducing the structural responses under different earthquakes.Comparison with the uncontrolled structure,the passive-off and passive-on cases indicates that both the peak and the norm values of structural responses are all clearly reduced,and the SAPC scheme has a better performance than the two passive cases.

The Dynamic Model of Allocation Control in Venture Capital

The allocation of control and stock in venture capital is the key point of the venture capital project.This paper develops a dynamic model of control and stock and profoundly analyses how to allocate the control between the entrepreneur and the venture capitalist.The model reveals the relationship of control and stock's structure,the time and the degree of imparting the control to the entrepreneur or the venture capitalist,the condition of retracting the control and compensation accordingly.

A measurement system of magnetism parameters for motion control

Magnetism parameters vary with the position and the speed of electromagnetic actuator's motion parts.The measurement unit presented in the paper can be applied to get the position and the speed feedback information from the measurement of electromagnetism parameters,and can constitute the untouched feedback sensing unit in the closed-loop motion control,and it adapts to the diversified feedback control of electromagnetic actuator.The digital miniaturization meter,based on MSP430 single chip processor,which can do the multi-purpose measurement of Φ & B through the menu selection,can be used for the electromagnetic actuator's performance evaluation and improvement,and also the online quality control in production process.Both real-time data graph and data table can be displayed in the meter.The paper presents the system's structure,describes the principle,discusses the working modes,and shows the software flowchart and the measuring results.

Study on Three-layered Grid Conceptual Prototype Using Ecological Network Computing Environment

Next generation grid systems where the emphasis shifts to distributed global collaboration, a service-oriented approach and information layer issues exhibit a strong sense of automation. Requirements for these systems resemble the self-organizing and the healing properties of natural ecosystems. Some key ecological concepts and mechanisms are introduced into the design for the third generation grid computing architectures by inspiration of this resemblance. Also, an Ecological Network-based Computing Environment (ENCE) platform is designed in this paper. Based on the ENCE platform, a grid-computing model of three-layered grid conceptual prototype that embeds the ENCE layers is presented from the viewpoint of implementation. The implementation model should be useful to the design of the third generation grid systems.

Using chaos to improve measurement precision

If the measuring signals were input to the chaotic dynamic system as initial parameters, the system outputs might be in steady state, periodic state or chaos state. If the chaotic dynamic system outputs controlled in the periodic states, the periodic numbers would be changed most with the signals. Our novel method is to add chaotic dynamic vibration to the measurement or sensor system.The sensor sensitivity and precision of a measurement system would be improved with this method. Chaotic dynamics measurement algorithms are given and their sensitivity to parameters are analyzed in this paper. The effects of noises on the system are discussed.

WPT-Based Modal Control on Distributed Structures with MRF-04K Damper

The magnetorheological （MR） fluid damper-based semiactive control systems have received considerable attention for protecting structures against natural hazards such as strong earthquakes and high winds. In this paper, a novel modal controller using wavelet packet transform （WPT） is proposed for the vibration control of distributed structures. In the proposed control system, the WPT method is utilized to decompose the acceleration measurement and select the modes containing most of the WPT energy component as the dominant modes. Then, a modal controller is designed to control the dominant modes and the optimal active control force is solved. Finally, Clipped-optimal con- trol law is adopted to determine the voltage applied to each MR damper. A Kalman-filter observer, which estimates the full controlled modal states from local accelerometer feedbacks, is designed for rendering the controller to be more applicable to distributed structures with a large number of degrees of freedom. A numerical example of a stadium root structure installed with MRF-04K damper is presented. The effectiveness of the controller is evaluated under both Tianjin and E1 Centro earthquake excitations. The superior performance and adaptability of the controller for versatile loading conditions are demonstrated through the comparison with traditional truncated modal controller.

Vehicle height control of electronic air suspension system based on mixed logical dynamical modelling

Due to the coexistence and coupling of continuous variables and discrete events, the vehicle height adjustment process of electronic air suspension system can be regarded as a typical hybrid system. Therefore, the hybrid system theory was applied to design a novel vehicle height control strategy in this paper. A nonlinear mechanism model of the vehicle height adjustment system was established based on vehicle system dynamics and thermodynamic theory for variable-mass gas charge/discharge system. In order to model both the continuous/discrete dynamics of vehicle height adjustment process and the on-off statuses switching of solenoid valves, the framework of mixed logical dynamical(MLD) modelling was used. On the basis of the vehicle height adjustment control strategy, the MLD model of the adjustment process was built by introducing auxiliary logical variables and auxiliary continuous variables. Then, the co-simulation of the nonlinear mechanism model and the MLD model was conducted based on the compiling of HYSDEL. The simulation and experimental results show that the proposed control strategy can not only adjust the vehicle height effectively, but also achieve the on-off statuses direct control of solenoid valves.

Nonlinear hierarchy-structured predictive control design for a generic hypersonic vehicle

A hierarchy-structured predictive controller is designed and analyzed for rotation motion dynamics of a generic hypersonic vehicle(GHV).This vehicle model has fast variability,is highly nonlinear,and includes uncertain parameters.The controller contains two subsystems,the inner-fast-loop nonlinear generable predictive controller(NGPC)and the outer-slow-loop NGPC,both of which are designed by the closed-form optimal generable predictive control method.Thus,the heavy on-line computational burden in the classical predictive control method is avoided.The hierarchy structure of the control system decreases the relative degree of each subsystem and helps increase the dynamic response speed of the attitude controller.In order to improve the robustness of the control system,a feedback correction algorithm is proposed that corrects the calculation error between the predictive model and the real dynamic model.Simulation studies are conducted for the trimmed cruise conditions of an altitude of 33.5 km and Mach 15 to investigate the responses of the vehicle to the step commands of angle of attack,sideslip angle,and bank angle.The simulation studies demonstrate that the proposed controller is robust with respect to the parametric uncertainties and atmospheric disturbance,and meets the performance requirements of GHV with acceptable control inputs.

ADAPTIVE SYSTEMS THEORY: SOME BASIC CONCEPTS, METHODS AND RESULTS

The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some 'critical values' and establishing some 'Impossibility Theorems' for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.