考虑阻尼器被动特性的半主动控制算法研究

研究了半主动阻尼器的被动特性 ,并给出了该被动特性的数学表达式。将该被动特性作为约束引入状态反馈H2最优控制 ,得到双线性不等式约束下的最优化问题 ,并采用路径追踪法求解该问题。最后给出一个 5自由度算例 ,在理想半主动阻尼器的假设下 ,检验了算法 ,结果表明本文方法非常有效 ,并可推广到其他附加线性不等式约束的控制问题。此外 ,数值结果表明 ,对于单个半主动阻尼器 ,最优增益矩阵具有对位反馈的特点 ,可以用普通被动线性粘滞阻尼器代替。     

Dissipativity reinforcement in feedback systems and its application to expanding power systems

This paper focuses on the performance analysis and improvement of interconnected passive systems. We assume that each subsystem has a special passivity property that is characterized by 2 parameters. The parameters are also utilized for evaluating the dissipation performance as the L₂‐gain. Then, the feedback system composed of passive subsystems inherits the parameter‐dependent passivity, and the parameter transition is given. In addition, it is shown that the dissipation performance of the feedback system is strictly improved as compared with that of the subsystems, which is called dissipativity reinforcement in this paper. Furthermore, we expand the feedback system to a larger‐scale system via the iterative feedback connection of the passive subsystems. Then, the performance of the entire system is gradually reinforced with the increase in the number of subsystems. Subsequently, we extend the class of parameter‐dependent passivity to a frequency‐dependent one. Finally, dissipativity reinforcement via an iterative feedback connection is applied to a power system that involves a large number of renewable energy generators. In particular, we propose a strategy for designing the power system, such that the dissipation performance of the entire system is gradually reinforced via scale expansion, ie, with the increase in the amount of energy generators installed.     

A general dissipativity constraint for feedback system design,with emphasis on MPC

A “general dissipativity constraint” (GDC) is introduced to facilitate the design of stable feedback systems. A primary application is to MPC controllers when it is preferred to avoid the use of “stabilising ingredients” such as terminal constraint sets or long prediction horizons. Some very general convergence results are proved under mild conditions. The use of quadratic functions, replacing GDC by “quadratic dissipativity constraint” (QDC), is introduced to allow implementation using linear matrix inequalities. The use of QDC is illustrated for several scenarios: state feedback for a linear time‐invariant system, MPC of a linear system, MPC of an input‐affine system, and MPC with persistent disturbances. The stability that is guaranteed by GDC is weaker than Lyapunov stability, being “Lagrange stability plus convergence.” Input‐to‐state stability is obtained if the control law is continuous in the state. An example involving an open‐loop unstable helicopter illustrates the efficacy of the approach in practice.     

Robust H∞ controller design for a class of linear quantum systems with time delay

Time delay is frequently encountered in practical quantum feedback control systems with long transmission lines and measurement process. This paper is concerned with measurement‐based feedback H^∞ control for quantum systems with time delays appearing in the feedback loops. A physical model is presented for the quantum time‐delay system described by complex quantum stochastic differential equations. Quantum versions of some fundamental properties, such as dissipativity and stability, are discussed for this model. A numerical procedure is proposed for H^∞ controller synthesis, which can deal with a non‐convex optimization problem arising in the design processes. Copyright © 2016 John Wiley & Sons, Ltd.     

Output synchronization of discrete-time dynamical networks based on geometrically incremental dissipativity

In this work, we investigate the output synchronization problem for discrete-time dynamical networks with identical nodes. Firstly, if each node of a network is geometrically incrementally dissipative, the entire network can be viewed as a geometrically dissipative nonlinear system by choosing a particular input–output pair. Then, based on the geometrical dissipativity property, we consider two cases: output synchronization under arbitrary topology and switching topology, respectively. For the first case, we establish several criteria of output synchronization under arbitrary switching between a set of connection topologies by employing a common Lyapunov function. For the other case, we give the design method of a switching signal to achieve output synchronization even if all subnetworks are not synchronous. Finally, an example is provided to illustrate the effectiveness of the main results.     

Dissipativity‐based distributed model predictive control with low rate communication

Distributed or networked model predictive control (MPC) can provide a computationally efficient approach that achieves high levels of performance for plantwide control, where the interactions between processes can be determined from the information exchanged among controllers. Distributed controllers may exchange information at a lower rate to reduce the communication burden. A dissipativity‐based analysis is developed to study the effects of low communication rates on plantwide control performance and stability. A distributed dissipativity‐based MPC design approach is also developed to guarantee the plantwide stability and minimum plantwide performance with low communication rates. These results are illustrated by a case study of a reactor‐distillation column network. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3288–3303, 2015     

不确定线性脉冲系统的鲁棒耗散性

利用Lyapunov函数和线性矩阵不等式方法 ,得出了不确定脉冲线性系统相对于二次供给率的鲁棒耗散性的条件。     

Distributed model predictive control based on dissipativity

A noncooperative approach to plant‐wide distributed model predictive control based on dissipativity conditions is developed. The plant‐wide process and distributed control system are represented as two interacting process and controller networks, with interaction effects captured by the dissipativity properties of subsystems and network topologies. The plant‐wide stability and performance conditions are developed based on global dissipativity conditions, which in turn are translated into the dissipative trajectory conditions that each local model predictive control MPC must satisfy. This approach is enabled by the use of dynamic supply rates in quadratic difference forms, which capture detailed dynamic system information. A case study is presented to illustrate the results. © 2012 American Institute of Chemical Engineers AIChE J, 59: 787–804, 2013     

Dissipativity and passivity analysis for discrete‐time complex‐valued neural networks with leakage delay and probabilistic time‐varying delays

In this paper, the problem of dissipativity and passivity analysis is investigated for discrete‐time complex‐valued neural networks with time‐varying delays. Both leakage and discrete time‐varying delays have been considered. By constructing a suitable Lyapunov–Krasovskii functional and by using discretized Jensen's inequality approach, sufficient conditions have been established to guarantee the (Q ,S ,R ) ? γ dissipativity and passivity of the addressed discrete‐time complex‐valued neural networks. These conditions are derived in terms of complex‐valued linear matrix inequalities (LMIs), which can be checked numerically using Yet Another LMI Parser toolbox in Matrix Laboratory. Finally, three numerical examples are established to illustrate the effectiveness of the obtained theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.