ON DECENTRALIZED OBSERVATION AND DECENTRALIZED CONTROL OF LARGE SCALE SYSTEMS

In this paper, the problem of decentralized observation and decentralized control of linear, time-invariant large scale systems is studied. Based on conventional observer theory, the necessary and sufficient conditions for existence of completely decentralized observer are obtained. Moreover, the necessary and sufficient condition is given for stabilization of large scale systems by local output with state of the subsystem estimated through the completely decentralized observer.

Optimal decentralized control of large scale systems

This paper presents a new optimized decentralized controller design method for solving the tracking and disturbance rejection problems for large-scale linear time-invariant systems, using only low-order decentralized controllers. To illustrate the type of results which can be obtained using the new optimized decentralized control design method, the control of a large flexible space structure is studied and compared with the standard centralized LQR-observer controller. The order of the resultant decentralized controller is much smaller than that of the standard centralized LQR-observer controller. The proposed controller also has certain fail-safe properties and, in addition, it can be five orders of magnitude more robust than the standard LQR-observer controller based on their real stability radii. The new decentralized controller design method is applied to a large flexible space structure system with 5 inputs and 5 outputs and of order 24.

Observer-based Adaptive Optimal Control for Unknown Singularly Perturbed Nonlinear Systems With Input Constraints

This paper introduces an observer-based adaptive optimal control method for unknown singularly perturbed nonlinear systems with input constraints. First, a multi-Time scales dynamic neural network MTSDNN observer with a novel updating law derived from a properly designed Lyapunov function is proposed to estimate the system states. Then, an adaptive learning rule driven by the critic NN weight error is presented for the critic NN, which is used to approximate the optimal cost function. Finally, the optimal control action is calculated by online solving the Hamilton-Jacobi-Bellman HJB equation associated with the MTSDNN observer and critic NN. The stability of the overall closed-loop system consisting of the MTSDNN observer, the critic NN and the optimal control action is proved. The proposed observer-based optimal control approach has an essential advantage that the system dynamics are not needed for implementation, and only the measured input U+002F output data is needed. Moreover, the proposed optimal control design takes the input constraints into consideration and thus can overcome the restriction of actuator saturation. Simulation results are presented to confirm the validity of the investigated approach. © 2014 Chinese Association of Automation.

Decentralized Control for Residential Energy Management of a Smart Users' Microgrid with Renewable Energy Exchange

This paper presents a decentralized control strategy for the scheduling of electrical energy activities of a microgrid composed of smart homes connected to a distributor and exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is stated and solved with the aim of reducing the overall energy supply from the grid, by allowing users to exchange the surplus renewable energy and by optimally planning users' controllable loads. We assume that each smart home can both buy/sell energy from/to the grid taking into account time-varying non-linear pricing signals. Simultaneously, smart homes cooperate and may buy/sell locally harvested renewable energy from/to other smart homes. The resulting optimization problem is formulated as a non-convex non-linear programming problem with a coupling of decision variables in the constraints. The proposed solution is based on a novel heuristic iterative decentralized scheme algorithm that suitably extends the Alternating Direction Method of Multipliers to a non-convex and decentralized setting. We discuss the conditions that guarantee the convergence of the presented algorithm. Finally, the application of the proposed technique to a case study under several scenarios shows its effectiveness.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Decentralized robust guaranteed cost control for a class of interconnected singular large-scale systems with time-delay and parameter uncertainty

The decentralized robust guaranteed cost control problem is studied for a class of interconnected singular large-scale systems with time-delay and norm-bounded time-invariant parameter uncertainty under a given quadratic cost performance function. The problem that is addressed in this study is to design a decentralized robust guaranteed cost state feedback controller such that the closed-loop system is not only regular, impulse-free and stable, but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of the decentralized robust guaranteed cost state feedback controllers is proposed in terms of a linear matrix inequality （LMI） via LMI approach. When this condition is feasible, the desired state feedback decentralized robust guaranteed cost controller gain matrices can be obtained. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed approach.

Decentralized H-infinity state feedback control for discrete-time singular large-scale systems

The decentralized H-infinity control problem for discrete-time singular large-scale systems is considered. Based on the bounded real lemma of discrete-time singular systems, a sufficient condition for the existence of decentralized H-infinity controller for discrete-time singular large-scale systems is presented in terms of the solvability to a certain system of linear matrix inequalities by linear matrix inequality (LMI) approach, and the feasible solutions to the system of LMIs provide a parameterized representation of a set of decentralized H-infinity controller. The given example shows the application of the method.

Decentralized Iterative Learning Controllers for Nonlinear Large-scale Systems to Track Trajectories with Different Magnitudes

在为大规模工业进程的层次不变的优化编程，一种可行技术是使用真实系统的信息以便修改基于模型的最佳。在这种情形，有不同大小的步功能类型控制决定的一个序列被计算，由哪个真实系统连续地被刺激。在这份报纸，一套反复的学习控制器为大规模非线性的工业过程的一个班在分散的模式被嵌进层次不变的优化的过程。为每个分系统的控制器被用来产生升级的控制信号的一个序列以便与不同规模承担顺序的步骤控制决定的责任。学习控制设计的目的是连续地精制系统的短暂性能。借助于卷绕旋转积分的 Hausdorff 年轻的不平等，更新的规则的集中在 Lebesgue-p 标准的意义被分析。集中上的非线性和相互作用的发明被讨论。建议控制计划的有效性和有效性被一些模拟表明。

Sample-data Decentralized Reliable H∞ Hyperbolic Control for Uncertain Fuzzy Large-scale Systems with Time-varying Delay

这份报纸学习样品数据的问题为有变化时间的延期的不明确的连续时间的模糊大规模系统的可靠 H 夸张控制。第一，模糊夸张模型( FHM )被用来为某些复杂大规模系统建立模型，然后根据 Lyapunov 指导方法和大规模系统的分散的控制理论，线性 matrixine 质量( LMI )基于条件 arederived toguarantee H 性能不仅当所有控制部件正在操作很好时，而且面对一些可能的致动器失败。而且，致动器的精确失败参数没被要求，并且要求仅仅是失败参数的更低、上面的界限。条件依赖于时间延期的上面的界限，并且不依赖于变化时间的延期的衍生物。因此，获得的结果是不太保守的。最后，二个例子被提供说明设计过程和它的有效性。

Optimal tracking control for nonlinear large-scale systems with persistent disturbances

This paper studies the optimal control with zero steady-state error problem for nonlinear large-scale systems affected by external persistent disturbances.The nonlinear large-scale system is transformed into N nonlinear subsystems with interconnect terms.Based on the internal model principle,a disturbance compensator is constructed such that the ith subsystem with external persistent disturbances is transformed into an augmented subsystem without disturbances.According to the sensitivity approach,the optimal tracking control law for the ith nonlinear subsystem can be obtained.The optimal tracking control law for the nonlinear large-scale systems can be obtained.A numerical simulation shows that the method is effective.

Optimal tracking control for linear time-delay large-scale systems with persistent disturbances

An optimal tracking control （OTC） problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is constructed. The system with persistent disturbances is transformed into an augmented system without persistent disturbances. The original OTC problem of linear time-delay system is transformed into a sequence of linear two- point boundary value （TPBV） problems by introducing a sensitivity parameter and expanding Maclaurin series around it. By solving an OTC law of the augmented system, the OTC law of the original system is obtained. A numerical simulation is provided to illustrate the effectiveness of the proposed method.

Remote Control and Telemetry System for Large-scale Model Test at Sea

Physical testing of large-scale ship models at sea is a new experimental method.It is a cheap and reliable way to research the environment adaptability of a ship in complex and extreme wave conditions.It is necessary to have a stable experimental system for the test.Since the experimental area is large, a remote control system and a telemetry system are essential, and were designed by the authors.An experiment was conducted on the Songhuajiang River to test the systems.The relationship between the model's speed and its electromotor's revolutions was also measured during the model test.The results showed that the two systems make it possible to carry out large-scale model tests at sea.

ASUBOPTIMAL DESIGN OF H∞DECENTRALIZED STATE FEEDBACK CONTROL FOR INTERCONNEC TED SYSTEMS

In the paper, the problem of H∞ decentralized state feedback control for largescale systems is described. An algorithm is proposed which uses the method of a feasible direction matrix. The algorithm only requires the solution of an algebraic Riccati equation (ARE) and makes the H∞norm of the closedloop transfer function matrix from disturbance inputs to controlled outputs less than a given constant which ensure the stability of the overall controlled system at each iteration. The given example shows that the convergence of the algorithm is satisfactory.

Non-fragile guaranteed cost control for uncertain neutral large-scale interconnected systems

This paper focuses on the problem of non-fragile decentralized guaranteed cost control for uncertain neutral large-scale interconnected systems with time-varying delays in state,control input and interconnections.A novel scheme,viewing the interconnections with time-varying delays as effective information but not disturbances,is developed.Based on Lyapunov stability theory,using various techniques of decomposing and magnifying matrices,a design method of the non-fragile decentralized guaranteed cost controller for unperturbed neutral large-scale interconnected systems is proposed and the guaranteed cost is presented.The further results are derived for the uncertain case from the criterion of unperturbed neutral large-scale interconnected systems.Finally,an illustrative example shows that the results are significantly better than the existing results in the literatures.

On the decomposition problem of neutral type linear large scale control system in the theory of stabilization(1)

In this paper we choose the symmetric positive definite solutionof Riccati matrix algebraic equation and,construct a positive defini-tequadratic form V-function and,use Lyapunov deco mpositionequivalence method founded by Liu Yong-qing to obtain the condi-tions of the asymptotic stability of the solution of neutral typelinear large scale control system,the estimate formula of thedecom posing coefficients and time delay are also given.

Optimal Tracking Controller Design for a Small Scale Helicopter

A model helicopter is more difficult to control than its full scale counterpart. This is due to its greater sensitivity to control inputs and disturbances as well as higher bandwidth of dynamics. This work is focused on designing practical tracking controller for a small scale helicopter following predefined trajectories. A tracking controller based on optimal control theory is synthesized as a part of the development of an autonomous helicopter. Some issues with regards to control constraints are addressed. The weighting between state tracking performance and control power expenditure is analyzed. Overall performance of the control design is evaluated based on its time domain histories of trajectories as well as control inputs.

MULTITASK SCHEDULING IN NETWORKED CONTROL SYSTEMS WITH APPLICATION TO LARGE SCALE VEHICLE CONTROL

Aiming at scheduling problems of networked control system （NCS） used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task scheduling are compared, and the mathematic description of task scheduling is presented. A performance index function of task scheduling of NCS according to task balance and traffic load matching principles is defined. According to this index, a static scheduling method is designed and implemented to controlling task set simulation of the DCY100 transportation vehicle. The simulation results are applied successfully to practical engineering in this case so as to validate the effectiveness of the proposed performance index and scheduling algorithm.

On the conjunction practical stability and controllability of large-scale impulsive control systems

We studied the conjunction practical stability and controllability of large-scale impulsive control systems by using the comparison systems and vector Lyapunov fimctions. Then the less conservative sufficient conditions for conjunction practical stability and controllability of large-scale impulsive control system were obtained.

An Adaptive Sliding Mode Tracking Controller Using BP Neural Networks for a Class of Large-scale Nonlinear Systems

A new type controller, BP neural-networks-based sliding mode controller is developed for a class of large-scale nonlinear systems with unknown bounds of high-order interconnections in this paper. It is shown that decentralized BP neural networks are used to adaptively learn the uncertainty bounds of interconnected subsystems in the Lyapunov sense, and the outputs of the decentralized BP neural networks are then used as the parameters of the sliding mode controller to compensate for the effects of subsystems uncertainties. Using this scheme, not only strong robustness with respect to uncertainty dynamics and nonlinearities can be obtained, but also the output tracking error between the actual output of each subsystem and the corresponding desired reference output can asymptotically converge to zero. A simulation example is presented to support the validity of the proposed BP neural-networks-based sliding mode controller.

Research on Control Method of Inverters for Large-scale Grid Connected Photovoltaic Power System

A grid-connected inverter controlling method to analyze dynamic process of large-scale and grid-connected photovoltaic power station is proposed. The reference values of control variables are composed of maximum power which is the output of the photovoltaic array of the photovoltaic power plant, and power factor specified by dispatching, the control strategy of dynamic feedback linearization is adopted. Nonlinear decoupling controller is designed for realizing decoupling control of active and reactive power. The cascade PI regulation is proposed to avoid inaccurate parameter estimation which generates the system static error. Simulation is carried out based on the simplified power system with large-scale photovoltaic plant modelling, and the power factor, solar radiation strength, and bus fault are considered for the further research. It’s demonstrated that the parameter adjustment of PI controller is simple and convenient, dynamic response of system is transient, and the stability of the inverter control is verified.