研究了线性变参数时滞系统的故障诊断问题。
This paper proposes a fault diagnosis method for linear parameter varying time-delay system (LPVTD).
本文对应用线性变参数(LPV)系统算法的船舶运动与柴油主机推进联合控制进行了系统的研究。
The integrated control of ship motion and main engine propulsion based on linear parameter-varying (LPV) is systemically studied in this dissertation.
当模型复杂且非线性时（换句话说，在线性方式下参数不共变），或者当模型涉及多于两三个不确定参数时，使用该方法。
The method is used when the model is complex and nonlinear (that is, parameters do not co-vary in a linear manner), or when the model involves more than just two or three uncertain parameters.
针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性，提出了一种基于最优预测的神经元模糊自整定PID控制算法。
To the widely existed characteristics of time-delay, non-linear and timevarying of parameters in the industry process, an adaptive neuron-fuzzy PID controller based on optimal prediction is presented.
催化裂化装置是一个高度非线性、时变、长时延、强耦合、分布参数和不确定性的复杂系统。
FCCU (fluid catalysis and cracking unit) is a highly non-linear, time variable, long time delay, intensive coupling, parameter distributed, indefinite and complex system.
这种方法首先对非语言声音信号进行谐波分析，然后对所得到的时变振幅与频率等声音信号参数进行分段线性化。
This technique performs harmonic analysis of the nonspeech audio signals and then the resulted attributes including time-varying amplitude and frequency functions are piecewisely linearized.
针对其存在非线性、参数时变和大延迟等难以控制的特性，提出基于T - S模糊模型的预测函数控制新方法。
As the nonlinearity, time-varying parameters and large lag make the control difficult, a predictive functional control method based on T-S (Takagi-Sugeno) fuzzy model is presented.
此无模型控制方法非常适用于实际的模型参数难以辨识，且是时变的非线性系统。
The model-free control is especially useful for real nonlinear systems whose model parameter are very difficult to be identified and time varying.
滑模变结构控制是一种非线性控制方法，对系统的参数变化和扰动具有安全的自适应性。
Sliding mode variable structure (SMVS) is a nonlinear control method, which is adaptive to disturbance and parameter variations.
然后，对于含有时变系统参数，非线性力不含时间项的情况进行了研究，给出了与其同步的系统的设计方法。
Then for the vibration system with time-varied parameters and without time-varied elements in restoring force, a principal to design a derived synchronization system is given and proved.
利用慢变参数、时程分析和能量分析方法，探讨了铅芯橡胶减震支座（LRB） 的非线性动力性态。
Slowly parameter, nonlinear time response analysis and energy approach can be used to obtain the dynamic behavior of lead rubber bearing (LRB).
对具有慢变参数的非线性振动系统进行了分析研究，这类系统在振动工程中有着广泛的实际背景。
The nonlinear vibration system with slow-changing parameters has been studied. This system has wide background in engineering.
提出了应用变采样率技术估计线性调频项参数来减小距离跟踪的误差，提高雷达的跟踪目标性能。
The parameter of LFM term estimated by the changing sample ratio processing technology to improve the performance of tracing distance is presented.
对于线性非时变的无源二端口网络，在零初始条件下，若存在互易性及对称性，则其电路参数具有一定的特殊性。
If reciprocity and symmetry exist for passive two port networks of linear time invariant under zero intial condition, the circuit parameters will have some important characters.
本文针对工业控制中一类常见的非线性时变系统，提出了一种利用参数反馈在线修正规则的模糊控制器；
This article puts forward a kind of self organization fuzzy controller with parameter feedback for a kind of common nonlinear time varying system in industry.
利用正交多项式序列的正交性及微分算子矩阵，论述了时变非线性分布参数系统参数估计的正交多项式法。
New method of parameter estimation for time varying non linear distributed systems is proposed in term of orthogonality of orthogonal polynomial and differential operation matrix.
针对在平衡点展开的线性模型进行了标准PID和变参数PID控制器的设计。
A standard PID controller and a variable parameter PID controller are designed for the linearization model.
研究了具有参数不确定的线性马尔可夫跳变系统的鲁棒适应控制问题。
Robust stabilization of linear Markov jump systems with parameter uncertainties via adaptive control is considered in the paper.
多模型控制是解决系统时变、非线性、参数不确定性等复杂问题得一种有效方法。
Multiple model control is an effective way for solving complicated problems such as time varying, nonlinear and parameters uncertainty.
本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
This paper presents an adaptive fault prediction method based on strong tracking filter, which can predict faults in a class of nonlinear time varying systems.
针对汽车方向动力学控制存在的非线性和参数时变不确定性问题，提出了一种新的基于单神经元的汽车方向自适应pid控制算法。
In view of the nonlinearity and parameter time-varying uncertainty of vehicle dynamics, a novel algorithm, i. e. single neural adaptive PID control strategy, is propsed for vehicle direction control.
本文针对船舶操纵这种非线性、时变参数控制对象，提出了一种采用神经网络自适应PID控制方案。
In this paper, according to nonlinear and time-varying parameter of ship maneuvering, the scheme of neural network adaptive PID control is proposed.
通过分析被控对象的特性，采用分段线性化的方法设计变参数PID控制器，进而给出基于T-S模型的模糊PID控制策略；
Variable parameter PID control for the controlled object is designed by the method of segment linearization. Furthermore, T-S model based fuzzy PID control strategy is put forward.
而异步电机是一个多变量、强耦合、非线性的时变参数系统，很难直接通过外加信号准确控制电磁转矩。
But asynchronous machine is a multivariate close coupling non - linear time - variable parameter system. And it is difficult to control by rule and line through adding exterior signal directly.
汽车转向系统是一个缓慢变化的非线性系统，在一个较短的时间间隔内，可以用一个参数时变的二阶线性系统对其动力学特性进行描述。
The vehicle steering system is a slowly varying non-linear system, in a short time interval, its dynamic characteristics can be described by a parameter-varying second-order linear system.
供热系统水压过程是一个耦合的、变参数的、非线性的多变量过程。
Hydraulic pressure process in heating system is coupling, parameter varying, nonlinear, multi-variables process.
给出了一个新的用于线性时变参数结构系统模态参数识别的基于固定长度平移窗投影估计的递推子空间方法。
A novel recursive subspace method is developed based on fixed length moving window (FLMW) projection approximation used for estimating the modal parameter of linear time-varying structural system.
循环流化床锅炉是一个分布参数、非线性、时变、多变量紧密耦合的对象。
Circulating fluidized bed (CFB) boiler is a distributed parameter, nonlinear, time varying and multivariate coupling system.
仿真结果表明了该线性时变模型和参数估计算法的可行性，表明该自适应预测控制方法具有优良的控制品质。
Simulation results demonstrate the feasibility of the model and the parameter estimation algorithm, and show that the adaptive predictive control method has excellent control quality.
仿真结果表明了该线性时变模型和参数估计算法的可行性，表明该自适应预测控制方法具有优良的控制品质。
Simulation results demonstrate the feasibility of the model and the parameter estimation algorithm, and show that the adaptive predictive control method has excellent control quality.
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