This paper addresses the cooperative control problem of a dual-antenna system under wind disturbances, conducting systematic research on system modeling and control design. By constructing an extended model of the dual-antenna system and leveraging the signal processing mechanism of antenna arrays connected via correlators, a key servo performance metric for the cooperative control of dual-antenna systems is innovatively proposed. This method, by sharing state information between the two antennas, achieves superior system performance at the control level compared to independent control schemes. Simulation results demonstrate that the proposed method significantly enhances the tracking performance and correlator output accuracy of the dual-antenna system, providing a theoretical foundation and practical guidance for the optimal cooperative control of arrays under correlated wind disturbances.

This paper studies a parameter identification method for two-inertia system. The method improved the accuracy and stability of the two-inertia system identification model by using Least Squares Method(LSM) to identify each parameter from its spectrum. Compared to traditional LSM methods, it has better accuracy and stability. Then, based on the two-inertia system model, this paper uses lead network based on Linear Quadratic Regulator (LQR) to control the real system. Comparison between simulation and actual measurement demonstrates the proposed identification method?s rationality and accuracy.

This paper proposes a non-parametric frequencydomain identification framework for lightly damped servo systems subject to restricted excitation. The method integrates multiexperiment data fusion with adaptive regularized smoothing to achieve an optimal balance between noise suppression and resonance fidelity. First, a signal-to-noise ratio (SNR) weighted fusion scheme is developed to combine multiple empirical transfer function estimates (ETFEs) in a minimum-variance sense. Second, an adaptive smoothing strategy is introduced within a convex optimization framework. A structural indicator derived from the residuals between the baseline fused spectrum and a uniformly smoothed reference is used to determine frequency-dependent regularization weights. This ensures that sharp resonances are preserved by locally reducing smoothing, while noise is effectively suppressed in flatter regions. Simulation results demonstrate that the proposed method significantly outperforms uniform smoothing benchmarks, offering superior estimation accuracy for high-performance control applications.

This work delves into the mean-square stability and stabilization via output feedback of networked control systems over communication channels with random data transmission delays and packet dropouts. The transmission delays and packet losses are characterized by independent and identically distributed (i.i.d.) processes with given probability mass functions (PMFs). A necessary and sufficient condition of mean-square (input–output) stability is established for the networked control systems. Utilizing this mean-square input–output stability criterion, we develop a new design approach for the mean-square stabilization via output feedback. Additionally, in scenario where the external input of the networked system is an i.i.d. process, we study the asymptotic stationarity of the control signal. To illustrate and verify the results presented in this work, a numerical example is provided.

This paper investigates the optimal tracking performance of a discrete-time linear time-invariant (LTI) multi-input and single-output (MISO) plant responding to a step reference signal, in the presence of temporally correlated multiplicative uncertainty. By temporally correlated, we mean the uncertainty has a practical structure of finite impulse response (FIR) and certain dynamical first and second moments, which includes multiplicative white noises and significant network-induced uncertainties. A two-degree-of-freedom (2DOF) controller is adopted and the tracking performance is measured by the expected energy of the tracking error. By a projection lemma, the criterion of achievability of asymptotic tracking is proposed in an innovative form, which explicitly characterizes how the plant properties (i.e., the potentially repeated unstable output poles, nonminimum phase output zeros, and relative degree) and the uncertainty property (captured by a rational function) may affect the performance limitation. It turns out that, when the achievability condition holds, the minimal achievable tracking performance of the closed-loop system with the uncertainty is proportional to the tracking performance limit of the system without uncertainty, made worse by a quantity related to the inverse of the largest stability margin of the closed-loop system against the uncertainty. In addition, some well-known criteria are reproduced by applying the result to the systems with random packet dropout or multiplicative white uncertainty. Several simulations are also conducted to validate the results. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and

This work mainly investigates the mean-square stability for a single-input single-output networked linear feedback system. The control signal in the networked system is transmitted over an unreliable channel with data transmission delays and packet dropouts. The transmission delays and packet dropouts are modeled by an independent and identically distributed random process with a known probability mass function. At the channel terminal, a linear receiving strategy is adopted. Based on the unit impulse response of the unreliable channel, we propose a new model of the channel uncertainty induced by the data transmission delays. It is found that the relation between the second-order statistics of the input and output of the channel uncertainty is time-invariant. To explore the effect of the channel uncertainty on the mean-square stability of this system, we introduce a concept called as frequency response of variation of the unreliable channel. With this new concept, a necessary and sufficient condition of the mean-square stability is established for the networked feedback system. It reveals that the mean-square stability is determined by the interaction between the frequency response of variation and the feedback system with a nominal channel. The channel uncertainty induced by data transmission delays is a colored multiplicative uncertainty. When the plant in the networked feedback system is minimum phase, an analytic necessary and sufficient condition is presented for its mean-square stabilizability via output feedback. It turns out that the stabilizability is only determined by the interaction between the frequency response of variation of the channel and unstable poles of the plant. Finally, numerical examples are given to illustrate our results.

In this paper, the feedback stabilization of a linear time-invariant (LTI) multiple-input multiple-output (MIMO) system cascaded by a linear stochastic system is studied in the mean-square sense. Here, the linear stochastic system can model a class of correlated stochastic uncertainties such as channel uncertainties induced by packet loss and random transmission delays in networked systems. By proposing a key parameter called coefficient of frequency variation to characterize the correlation of the stochastic uncertainties, we present a necessary and sufficient condition of the mean-square stability for this MIMO stochastic feedback system. After then a necessary and sufficient condition for the mean-square stabilizability is provided, which reveals a fundamental limit imposed by the system's unstable poles, nonminimum-phase (NMP) zeros, relative degrees (input delays), and the coefficient of frequency variation of the stochastic uncertainties. A numerical example is presented to illustrate the fundamental constraints in the mean-square stabilizability of MIMO networked systems with parallel communication channels.

In this work, the mean-square stabilizability via output feedback of a networked feedback system over an unreliable communication channel is studied. The unreliability of the channel is modeled by multiplicative noises. The admissible signal-to-noise ratio (SNR) of the unreliable channel with which the mean-square stabilizability of the networked feedback system is preserved is studied in terms of characteristics of the plant in the system. It is found that the infimum of the admissible SNR is determined by the inner of the plant’s non-minimum phase zeros, the balanced realization of the inner of plant’s unstable poles and the relative degree of the plant. Moreover, it is shown that this infimum of the admissible SNR is an exponential function of the relative degree with the square product of the unstable poles as the base. Our result analytically describes the inherent constraint between the channel SNR and the unstable poles, non-minimum zeros, relative degree of the plant in the mean-square stabilization problem of the network feedback system.

This work studies the mean-square stability of a discrete-time networked linear feedback system over a communication channel with random data transmission delays or packet dropouts. To describe data transmission process in the channel, a new stochastic state-space model is established for the unreliable channel. By applying this model, a set of necessary and sufficient conditions is presented for the mean-square stability of the networked feedback system. These conditions explain the interaction between the state-space model of the networked system and the statistics of the random parameters in the channel model in the mean-square stability problem. Moreover, we study the connection between the mean-square stability and input-output meansquare stability of this system. It is found that the mean-square stability criteria presented in this work is equivalent to the input-output mean-square stability criterion presented in our previous works.

伺服控制系统在工业机器人、数控机床等高速高精度运动控制系统中有着广泛应用,伺服系统控制器是决定其性能优劣的关键,为此提出一种基于频域特性的伺服系统控制器设计方法.通过设计控制器改变系统开环频率特性,然后分析开环频率特性来评估系统的闭环性能,进一步依据开环频率特性和设计指标调整控制器参数使系统达到理想性能,最后在闭环响应中检验控制器设计效果.为了验证所提方法的有效性,以PID控制器和基于内模原理的LQR控制器频域设计为例在自主研发的伺服云台控制系统中进行实验.实验结果表明,基于频域的控制器设计方法提升了控制器设计的效率和伺服系统的性能.

The flexible resonance characteristic in the electromechanical servo system is the key element that limits performances of the system. An accurate description of this characteristic is of great significance for suppressing resonance and improving the performance of the servo system. In this paper, adopting pseudo-random sequence as the identification input and combining impulse response correlation identification and eigen-system realization algorithm, an identification scheme which integrates experimental design, model calculation and model verification is proposed. This scheme can effectively identify the flexible modes, and hence is suitable for the identification of electromechanical servo systems.Using a large-aperture radio telescope antenna as the application example, the implementation of the identification scheme is detailed, and the models of the antenna servo system are obtained. The frequency-domain and time-domain fitting indexes indicate that, compared with the least square method and the subspace method, the model obtained by the method in this paper shows advantages in fitting flexible resonances.

This work addresses the mean-square stability and stabilizability problem for minimum-phase multi-input and multi-output (MIMO) plant with a novel colored multiplicative feedback uncertainty. The proposed uncertainty is generalization of the i.i.d. multiplicative noise and assumed to be a stochastic system with random finite impulse response (FIR), which has advantage on modeling a class of network phenomena such as random transmission delays. A concept of coefficient of frequency variation is developed to characterize the proposed uncertainty. Then, the mean-square stability for the system is derived, which is a generalization of the well-known mean-square small gain theorem. Based on this, the mean-square stabilizability condition is established, which reveals the inherent connection between the stabilizability and the plant's unstable poles and the coefficient of frequency variation of the uncertainty. The result is verified by a numerical example on the stabilizability of a networked system with random transmission delay as well as analog erasure channel.

This paper studies a high-performance control design for the servo system of a vehicle-mounted mobile satellite communication antenna. Considering the different requirements for tracking and disturbance attenuation in the servo system, a novel controller structure consisting of a central controller and a disturbance filter is proposed. Based on this controller structure, a bi-objective control design scheme is proposed: One is an optimal tracking design for the central controller, and the other is a disturbance attenuation design for the disturbance filter. It turns out that the resulting control system achieves an optimal tracking performance when the external disturbance is at a low level; meanwhile, the system achieves a robust disturbance attenuation performance when the disturbance is significant. Moreover, considering the trade-offs between performance and the robust stability of the closed-loop system, the weighting parameter selection in control design criteria is studied for a practical application. Furthermore, validation experiments and field tests are carried out to evaluate the effectiveness of this design, and their results show that the well-designed bi-objective controller significantly improves the dynamic pointing accuracy of the antenna in tracking a geostationary satellite when its carrier is driving off-road.

This work studies the mean-square stability and stabilization problem for networked feedback systems. Data transmission delays in the network channels of the systems are considered. It is assumed that these delays are i.i.d. processes with given probability mass functions (PMFs). A necessary and sufficient condition of mean-square (input-output) stability is studied for the networked feedback systems in terms of the input-output model and state-space model. Furthermore, according to this condition, mean-square stabilization via output feedback is studied for the networked feedback systems.

This paper addresses the mean-square optimal control problem for a class of discrete-time linear systems with a quasi-colored controldependent multiplicative noise via output feedback. The noise under study is novel and shown to have advantage on modeling a class of network phenomena such as random transmission delays. The optimal output feedback controller is designed using an optimal mean-square state feedback gain and two observer gains, which are determined by the mean-square stabilizing solution to a modified algebraic Riccati equation (MARE), provided that the plant is minimum-phase and left-invertible. A necessary and sufficient condition for the existence of the stabilizing solution to the MARE is explicitly presented. It shows that the separation principle holds in a certain sense for the optimal control design of the work. The result is also applied to the optimal control problems in networked systems with random transmission delays and analog erasure channels, respectively.

H∞ 控制器虽拥有优异的理论性能,但却鲜有在天线伺服系统上的应用,过高的阶次是限制H∞ 控制器应用的重要因素.为解决H∞控制器的高阶次问题,探索了一种基于LMI和互质因式分解的固定阶次H∞控制器设计方法.基于互质因式分解的控制器Youla参数化方法,引出一个保H∞性能控制器降阶的充分条件;利用KYP引理,把此充分条件转化为固定阶次H∞控制器设计问题,并以LMI的形式给出此固定阶次控制器的解.通过天线伺服系统上的仿真和实验,验证了所提算法的有效性和实用性,所得固定阶次H∞控制器性能优于传统方法H∞控制器和常用PI控制器.

This work mainly investigates the mean-square stability and stabilizability for a single-input single-output networked linear feedback system. The control signal in the networked system is transmitted over an unreliable channel. In this unreliable channel, the data transmission times, referred to as channel induced delays, are random values and the transmitted data could also be dropout with certain probability. The channel induced delays and packet dropout are modeled by an independent and identically distributed stochastic process with a fixed probability mass function. At the channel terminal, a linear combination of data received at one sampling time is applied to the plant of the networked feedback system as a new control signal. To describe the uncertainty in the channel, a concept so called frequency response of variation is introduced for the unreliable channel. With the given linear receiving strategy, a mean-square stability criterion is established in terms of the frequency response of variation of the unreliable channel for the networked feedback system. It is shown by this criterion that the mean-square stability is determined by the interaction between the frequency response of variation and the nominal feedback system. The role played by the random channel induced delays is the same as that played by a colored additive noise in an additive noise channel with a signal-to-noise ratio constraint. Moreover, the mean-square input-output stabilizability via output feedback is studied for the networked system. When the plant in the networked feedback system is minimum phase, an analytic necessary and sufficient condition is presented for its mean-square input-output stabilizability. It turns out that the stabilizability is only determined by the interaction between the frequency response of variation of the channel and unstable poles of the plant.

对于通讯信道具有丢包的网络化反馈控制系统,运用乘性噪声模型来描述丢包这一信道不确定性,并根据网络化系统的结构特点提出了一种渐近跟踪控制器结构,研究了该结构下系统的均方可镇定性以及均方最优渐近跟踪与均方可镇定性的等价关系.在此基础上,运用随机均方最优控制理论给出了该系统均方最优渐近跟踪设计方法,该方法取决于广义代数黎卡提方程(MARE)的均方镇定解.进一步,本文提出了求解上述均方镇定解的新算法.最后的仿真验证了对于信道具有丢包的网络化反馈系统最优渐近跟踪问题,本文所提方法的有效性和可行性.

为了应对工程界对控制工程专业人才在高端控制系统设计能力方面不断提升的要求,通过对反馈系统工程设计实验教学的探索,将实际科研项目及企业合作的工程项目中提炼的典型反馈系统设计问题转化为实验内容,让学生从实验课程中掌握实际工程应用的技术方法,并学会用理论知识去分析实验结果.同时通过科研实验室资源对学生开放共享,真正实现科研、教学的紧密结合,为国家发展培养具备优秀工程素养和创新能力的人才.