基于包含原理一般动态互联系统的分解与分散控制

针对一般结构互联系统的动态变化, 通过系统结构的描述, 以包含原理的多重叠分解为基础, 构建出适用于一般结构互联系统对对分解与重叠分散控制的扩展收缩变换矩阵、置换矩阵及相关的补偿矩阵; 然后根据所提出的子系统对的删除与添加方式, 构建出相应的删除矩阵与添加矩阵, 并将两者结合得到用于完成结构变化后的互联系统对对分解与重叠分散控制的结构变化矩阵, 从而实现具有一般动态结构互联系统的分解与分散控制; 最后以四区域互联电力系统AGC为例对其进行详细说明.

     

Stochastic optimal control via Bellman''s principle

This paper presents a strategy for finding optimal controls of non-linear systems subject to random excitations. The method is capable to generate global control solutions when state and control constraints are present. The solution is global in the sense that controls for all initial conditions in a region of the state space are obtained. The approach is based on Bellman's principle of optimality, the cumulant neglect closure method and the short-time Gaussian approximation. Problems with state-dependent diffusion terms, non-closeable hierarchies of moment equations for the states and singular state boundary condition are considered in the examples. The uncontrolled and controlled system responses are evaluated by creating a Markov chain with a control dependent transition probability matrix via the generalized cell mapping method. In all numerical examples, excellent controlled performances were obtained.     

Overlapping decentralized approach to automation generation control of multi-area power systems

An overlapping decentralized control scheme is presented and applied to automatic generation control (AGC) for multi-area power systems. Based on the inclusion principle, the system is first decomposed in the expanded space as a group of pair-wise subsystems (areas). Then, the decentralized controllers designed, by standard linear quadratic (LQ) control laws are implemented in each pair-wise subsystem. Finally, the overlapping decentralized controller is obtained by coordinating and contracting the pair-wise decentralized controllers from the expanded space to the original space, preserving the inclusion conditions. When applied to AGC of a four-area power system, the proposed methodology not only guarantees AGC qualities, but also increases the system reliability with respect to a wide variety of structured perturbations. Simulation results illustrate the effectiveness of the presented approach both in the general case of information structure constraints and in the cases when some pairs of subsystems are disconnected by unpredicted faults.     

Stochastic robustness synthesis applied to a benchmark control problem

Stochastic robustness synthesis is used to find compensators that solve a benchmark problem. The synthesis minimizes a robustness cost function that is the weighted quadratic sum of stochastic robustness metrics. These metrics — probability of instability, probability of actuator saturation, and probability of settling time violation — are estimated using Monte Carlo analysis. A simple search method minimizes the robustness cost by selecting values for the design parameters of a linear quadratic Gaussian regulator. The resulting compensators are robust, require low actuator authority, and compare well with previous designs.     

基于DCS原理的供热自动控制系统

介绍了一种基于分布式控制系统（DCS）的技术原理，结合宾馆锅炉供热系统的运行特点，使用参数自调节的PID控制技术，实现了对燃煤供热锅炉精确的温度控制和燃烧环境的优化，开发了一个分布式宾馆供热自动测控系统。     

一种虚拟式的自动控制原理实验平台设计

目前多用MATLAB进行自动控制原理的各类仿真,而它所需编写代码繁琐且界面不够灵活。鉴于此,提供了利用基于G语言的LABVIEW设计的自动控制原理虚拟实验平台。从模块组成上介绍了虚拟平台所完成的设计及分析功能,并以频域响应分析、频率法校正为例详细阐述了平台设计、分析系统的原理,最后经过与MATLAB仿真结果的对比验证,表明该平台系统分析的准确性与可靠性。     

Stochastic maximum principle for optimal control problems involving delayed systems

Dear editor, The main objective of this study is to investigate one type of stochastic optimal control problem for a delayed system using the maximum principle ...     

小型污水处理系统的自控装置研制

本文介绍为住宅小区的典型污水处理系统配置的一种自控装置。它由触摸屏和PLC等元件组成．取代传统的继电接触器控制装置。具有简单，方便，可靠等特点。文章在简述小型污水处理系统的基础上，论述了该自控装置的结构及工作原理。着重介绍F940WGOT触摸屏的画面制作功能，应用及设计时注意事项。     

Stochastic programming methods applied to network optimization

As communication technologies evolve, it becomes necessary to incorporate the stochastic effect of traffic flows into network models. This paper introduces the stochastic programming (SP) methodology for characterizing traffic. Two SP approaches, here-and-now (HN) and scenario tracking (ST), are described through case studies for a prototype network. A numerical optimization procedure is used to perform the simulation. It is clearly demonstrated that when the probability distributions can be estimated analytically, the HN approach can be attractive. Otherwise, the ST approach may be more appropriate.     

Control strategies for automatic generation control over MTDC grids

Increasingly in power systems, there is a trend towards the sharing of reserves and integration of markets over wide areas in order to enable increased penetration of renewable sources in interconnected power systems. In this paper, a number of simple PI and gain based Model Predictive Control algorithms are proposed for Automatic Generation Control in AC areas connected to Multi-Terminal Direct Current grids. The paper discusses how this approach improves the sharing of secondary reserves and could assist in achieving EU energy targets for 2030 and beyond.     

Asynchronous decentralized event-triggered control

In this paper we propose an approach to the implementation of controllers with decentralized strategies triggering controller updates. We consider set-ups with a central node in charge of the computation of the control commands, and a set of not co-located sensors providing measurements to the controller node. The solution we propose does not require measurements from the sensors to be synchronized in time. The sensors in our proposal provide measurements in an aperiodic way triggered by local conditions. Furthermore, in the proposed implementation (most of) the communication between nodes requires only the exchange of one bit of information (per controller update), which could aid in reducing transmission delays and as a secondary effect result in fewer transmissions being triggered.     

Stochastic maximum principle for SPDEs with noise and control on the boundary

In this paper we prove necessary conditions for optimality of a stochastic control problem for a class of stochastic partial differential equations that is controlled through the boundary. This kind of problem can be interpreted as a stochastic control problem for an evolution system in a Hilbert space. The regularity of the solution of the adjoint equation, that is a backward stochastic equation in infinite dimension, plays a crucial role in the formulation of the maximum principle.     

Stochastic maximum principle for delayed doubly stochastic control systems and their applications

ABSTRACT

In this paper, we investigate the optimal control problems for delayed doubly stochastic control systems. We first discuss the existence and uniqueness of the delayed doubly stochastic differential equation by martingale representation theorem and contraction mapping principle. As a necessary condition of the optimal control, we deduce a stochastic maximum principle under some assumption. At the same time, a sufficient condition of optimality is obtained by using the duality method. At the end of the paper, we apply our stochastic maximum principle to a class of linear quadratic optimal control problem and obtain the explicit expression of the optimal control.     

A decentralized approach to integrated flight control synthesis

A new approach to decoupled control of large-scale non-linear systems is applied to a dynamic flight control. Control synthesis is performed in two steps. First the nominal, programmed control is synthesized using the complete model of flight dynamics. This nominal control should realize the nominal trajectory under ideal conditions with no perturbations. In the second step the tracking of the nominal trajectory is realized. The system is viewed as a set of decoupled subsystems and for each subsystem local control is synthesized. Then, the stability of the overall system is analyzed and the global control is introduced to compensate coupling among some of the subsystems. A particular choice of subsystems in a case of flight control and of local and global control synthesis is proposed. A simulation of flight control with the proposed control law is also presented.     

An inclusion principle for dynamic systems

The purpose of this paper is to present a detailed study of the inclusion concept in dynamic systems, which is a suitable mathematical framework for comparing systems with different dimensions. The framework offers immediate results in reduced-order modeling and the overlapping decentralized control of complex systems. The presentation, which is limited to linear constant systems, relies on both the matrix algebra (computations) and the geometric elements (structure) to provide a balanced view of the issues involved in the concept of inclusion. The framework is quite broad, and has been used to consider nonlinear and time-varying systems, as well as systems with hereditary and stochastic effects.     

基于AGC的光伏电站一次调频控制

逆变器调节速度快,且利用光伏电站的调频能力可降低常规调频备用容量,光伏电站深入参与电网一次调频将是一种很好的选择。基于此,本文在光伏电站自动发电控制（AGC）系统基础上增加光伏电站有功-频率下垂控制特性,使光伏电站在无需额外硬件增加或改造基础上实现AGC和一次调频功能一体化集成;其次,增加一次调频和AGC配合策略,实现二者无缝配合;最后,针对有功功率跟踪能力的不足对有功分配策略进行改进,提高了有功功率控制精度,提升了调频贡献能力。经过西北电网组织的新能源电站快速调频试验的验证,基于光伏电站自动发电控制系统的光伏电站一次调频控制具备较好的响应速度和调频贡献能力,能够为电网频率稳定提供支撑作用。     

Stochastic minimax optimal control strategy for uncertain quasi-Hamiltonian systems using stochastic maximum principle

A stochastic minimax optimal control strategy for uncertain quasi-Hamiltonian systems is proposed based on the stochastic averaging method, stochastic maximum principle and stochastic differential game theory. First, the partially completed averaged Itô stochastic differential equations are derived from a given system by using the stochastic averaging method for quasi-Hamiltonian systems with uncertain parameters. Then, the stochastic Hamiltonian system for minimax optimal control with a given performance index is established based on the stochastic maximum principle. The worst disturbances are determined by minimizing the Hamiltonian function, and the worst-case optimal controls are obtained by maximizing the minimal Hamiltonian function. The differential equation for adjoint process as a function of system energy is derived from the adjoint equation by using the Itô differential rule. Finally, two examples of controlled uncertain quasi-Hamiltonian systems are worked out to illustrate the application and effectiveness of the proposed control strategy.     

Stochastic control of discrete systems: a separation principle forWiener and polynomial systems

A new separation principle is established for systems represented in discrete frequency-domain Wiener or polynomial forms. The LQG or H ₂ optimal controller can be realized using an observer based structure estimating noise free output variables that are fed back through a dynamic gain control block. Surprisingly, there are also two separation principle theorems, depending upon the order in which the ideal output optimal control and the optimal observer problems are solved     

Wave CPG model for autonomous decentralized multi-legged robot: Gait generation and walking speed control

In this paper, we propose a method to control gait generation and walking speed control for an autonomous decentralized multi-legged robot by using a wave Central Pattern Generator (CPG) model. The wave CPG model is a mathematical model of nonlinear oscillators and generates rhythmic movements of the legs. The gait generation and the walking speed control are achieved by controlling the virtual energy of the oscillators (Hamiltonian). A real robot experiment showed the relationship to the Hamiltonian, the actual energy consumption and the walking speed, and the effectiveness of the proposed method was verified.