翼伞系统最优归航轨迹设计的敏感度分析方法

本文对三自由度翼伞系统归航轨迹优化问题进行了研究,采用控制变量参数化与时间尺度变换相结合的优化算法对翼伞系统的最优控制问题进行数值求解.该方法是基于灵敏度分析的优化算法,将控制量以及控制量转换时间转化为一系列参数优化问题同时进行求解.仿真结果表明,相对于基于两端边值优化算法而言,灵敏度分析法只需要正向积分进行求解,因而具有计算简单、耗时短等优点,其控制效果良好,距离偏差和方向偏差均满足实际需求,有效地提高了翼伞系统的着陆精度,验证了该优化算法的可行性.     

Pole assignment for multi-input multi-output systems using output feedback

In this paper the problem of pole assignment using constant gain output feedback is studied for MIMO system with system order n > m + l − 1, where m and l are the number of inputs and outputs, respectively. A new procedure is presented to design a constant gain output feedback matrix which assigns (m + l − 2) poles exactly to the desired locations and shifts all the unassigned poles to suitable locations using root locus techniques.     

Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Problems characterized by qualitative uncertainty described by expert judgments can be addressed by the fuzzy logic modeling paradigm, structured within a so-called fuzzy expert system (FES) to handle and propagate the qualitative, linguistic assessments by the experts. Once constructed, the FES model should be verified to make sure that it represents correctly the experts’ knowledge. For FES verification, typically there is not enough data to support and compare directly the expert- and FES-inferred solutions. Thus, there is the necessity to develop indirect methods for determining whether the expert system model provides a proper representation of the expert knowledge. A possible way to proceed is to examine the importance of the different input factors in determining the output of the FES model and to verify whether it is in agreement with the expert conceptualization of the model. In this view, two sensitivity and uncertainty analysis techniques applicable to generic FES models are proposed in this paper with the objective of providing appropriate tools of verification in support of the experts in the FES design phase. To analyze the insights gained by using the proposed techniques, a case study concerning a FES developed in the field of human reliability analysis has been considered.     

Semi-global observer for multi-output nonlinear systems

We present an explicit form of nonlinear observers for a class of multi-input multi-output systems. Observer construction for multi-output nonlinear systems is not a trivial extension of single output case, especially when the global error convergence is of interest. In this paper, we consider a class of systems in which the subsystem for each output has a triangular dependence on the states of that subsystem itself, and the overall system has a block triangular form for each subsystem. Hence, the contribution is to extend the results existing in the literature in that interconnections between the subsystems are allowed. The construction is based on the saturation of some estimates, which is originated by Khalil and Esfandiari for the use of semi-global output feedback control.     

Systematic testing of an integrated systems model for coastal zone management using sensitivity and uncertainty analyses

Systematic testing of integrated systems models is extremely important but its difficulty is widely underestimated. The inherent complexity of the integrated systems models, the philosophical debate about the model validity and validation, the uncertainty in model inputs, parameters and future context and the scarcity of field data complicate model validation. This calls for a validation framework and procedures which can identify the strengths and weaknesses of the model with the available data from observations, the literature and experts’ opinions. This paper presents such a framework and the respective procedure. Three tests, namely, Parameter-Verification, Behaviour-Anomaly and Policy-Sensitivity are selected to test a Rapid assessment Model for Coastal-zone Management (RaMCo). The Morris sensitivity analysis, a simple expert elicitation technique and Monte Carlo uncertainty analysis are used to facilitate these three tests. The usefulness of the procedure is demonstrated for two examples.     

Robustness analysis for systems with ellipsoidal uncertainty

This note derives an explicit expression for computing the robustness margin for affine systems whose real and complex coefficients are related by an ellipsoidal constraint. The expression, which is an application of a result by Chen, Fan, and Nett for rank-one generalized structured singular-value problems, extends and unifies previous results on robustness margin computation for systems with ellipsoidal uncertainty. © 1998 John Wiley & Sons, Ltd.     

Optimal control of linear systems with parameter uncertainty

A class of infinite-horizon regulator problems is formulated for families of time-invariant linear systems with parameter uncertainty. Under a regularity assumption, the optimal linear, state-feedback control is shown to exist and is defined via a positive-definite solution of a family of Riccati-type, algebraic equations. The solvability of these equations is equivalent to the stabilizability of the family of linear systems by a constant, linear feedback.     

Multi-innovation stochastic gradient algorithms for multi-input multi-output systems

This paper develops a multi-innovation stochastic gradient (MISG) algorithm for multi-input multi-output systems by expanding the innovation vector to an innovation matrix. The convergence analysis shows that the parameter estimates by the MISG algorithm consistently converge to the true parameters under the persistent excitation condition. The MISG algorithm uses not only the current innovation but also the past innovation at each iteration and repeatedly utilizes the available input–output data, thus the parameter estimation accuracy can be improved. The simulation example confirms the theoretical results.     

Optimal phase searching of PTS using modified genetic algorithm for PAPR reduction in OFDM systems

In this paper,a novel genetic algorithm assisted partial transmit sequence(NGA-PTS)is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM).However,the search complexity of the optimum PTS(OPTS)scheme is too large for the typical number of sub-blocks.Therefore,some artificial intelligence methods,such as genetic algorithm technique,and particle swarm optimization,are introduced to reduce the complexity.As traditional GA-PTS(TGA-PTS)technique risks finding a suboptimal solution,how to avoid this disadvantage of TGA-PTS is an interest topic.In order to obtain a better suboptimal solution,a phase factor optimal pair technique and an abandon/introduction new chromosome technique are proposed in GA here.Simulation results show that the proposed scheme achieves a significant improvement over the TGA-PTS scheme in PAPR.Furthermore,by use of the inherent diversity of constellation for each OFDM candidate,in the receiver part,the proposed scheme enables data recovery without any side information.Simulation results show the efficiency of the proposed scheme.     

基于极值搜索算法的一类多输入多输出非仿射型非线性系统输出跟踪控制

针对一类状态不可测的多输入多输出非仿射型非线性系统, 提出了基于极值搜索算法的输出跟踪控制方法. 此方法无需设计系统状态观测器, 仅利用系统的输出量和极值搜索向量形成控制律. 应用平均化理论分析平均化系统的稳定性, 然后利用奇异值扰动方法, 证明了所提出的控制方法可以保证闭环系统的稳定性和输出跟踪误差的收敛性. 仿真结果验证了本文方法的有效性.     

Availability assessment of railway signalling systems with uncertainty analysis using Statecharts

In this paper, we propose an original simulation approach to evaluate the availability of systems in the presence of state uncertainty which arises from incompleteness or imprecision of knowledge and data. This approach is based on a simulation method combining the belief functions theory and the Statecharts. Then we propose a Statechart model of a railway signalling system, European Rail Traffic Management System (ERTMS) Level 2 considering state uncertainty, and evaluate its availability according to the RAMS requirements defined in the railway standards. Finally we propose a sensitivity analysis to estimate the state uncertainty of which constituent system has the most significant influence on the state uncertainty of the entire ERTMS Level 2.     

Robust performance analysis for systems with structured uncertainty

This paper analyses robust performance measures for linear time-invariant systems with norm-bounded time-varying structured uncertainty. We consider two robust performance measures. One is the worst-case peak value of the error signal in response to the disturbance with a known energy. The other is the worst-case energy of the error signal in response to impulsive disturbance. In both cases, the ‘worst case’ is taken over all admissible uncertainties and disturbances. The notion of robust stability is Q-stability, or the scaled H_∞ norm bound. Our main results provide an upper bound for each of the robust performance measures in terms of a positive definite matrix which satisfies a linear matrix inequality (LMI) together with a scaling matrix. Hence, the best bound in this LMI formulation can be computed by convex programming.     

Observer with linear error dynamics for nonlinear multi-output systems

Based upon nonlinear state coordinate transformations and a condensed dual Brunovský form for multi-output systems, a method for designing nonlinear state observers with linear error dynamics is presented. Necessary and sufficient conditions are provided for identifying the class of nonlinear systems for which state observers with linear error dynamics can be obtained.     

Set-point-related indirect iterative learning control for multi-input multi-output systems

A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a supervision module for the local controller, ILC can improve the tracking performance of the closed-loop system along the batch direction. In this study, an ILC-based P-type controller is proposed for multi-input multi-output (MIMO) linear batch processes, where a P-type controller is used to design the control signal directly and an ILC module is used to update the set-point for the P-type controller. Under the proposed ILC-based P-type controller, the closed-loop system can be transformed to a 2-dimensional (2D) Roesser s system. Based on the 2D system framework, a sufficient condition for asymptotic stability of the closed-loop system is derived in this paper. In terms of the average tracking error (ATE), the closed-loop control performance under the proposed algorithm can be improved from batch to batch, even though there are repetitive disturbances. A numerical example is used to validate the proposed results.     

Minimal unknown-input functional observers for multi-input multi-output LTI systems

Designing minimum possible order (minimal) disturbance-decoupled proper functional observers for multi-input multi-output (MIMO) linear time-invariant (LTI) systems is studied. It is not necessary that a minimum-order unknown-input functional observer (UIFO) exists in our proposed design procedure. If the minimum-order observer cannot be attained, the observer's order is increased sequentially through a recursive algorithm, so that the minimal order UIFO can be obtained. To the best of our knowledge, this is the first time that this specific problem is addressed. It is assumed that the system is unknown-input functional detectable, which is the least requirement for the existence of a stable UIFO. This condition also is a certificate for the convergence of our observer's order-increase algorithm. Two methodologies are demonstrated to solve the observer design equations. The second presented scheme, is a new design method that based on our observations has a better numerical performance than the first conventional one. Numerical examples and simulation results in the MATLAB/Simulink environment describe the overall observer design procedure, and highlight the efficacy of our new methodology to solve the observer equations in comparison to the conventional one.     

多输入/多输出系统动态矩阵控制鲁棒稳定性

研究了基于脉冲响应模型的动态矩阵预测控制(DMC)算法,针对多输入、多输出(MIMO)系统脉冲响应模型的特点,利用脉冲响应系数误差矩阵范数平方和定义预测模型的模型误差,以线性矩阵不等式(LMI)的形式提出了DMC闭环鲁棒稳定充要条件,将DMC算法闭环稳定问题转换为一类线性矩阵不等式的可解问题.并且研究了模型误差与闭环系统稳定性之间的关系,给出了保证系统稳定条件下模型误差界的求取方法,通过求解一个线性矩阵不等式约束的凸优化问题得到保证闭环系统稳定的误差界.最后,利用算例对本文方法的有效性进行了验证.     

Optimal design of control systems with large plant uncertainty

This paper presents a practical optimal-design procedure in the fact of a significant and defined plant parameter uncertainty range, using Wiener's least-square optimization with a quadratic constraint in the frequency domain. With a linear time invariant minimum-phase stable plant imbedded, the optimal system to be designed is a two-degree-of-freedom feedback system such that the system response to a deterministic input lies within specified bounds.     

Optimal disturbance reduction in linear multivariable systems

This paper presents a computational solution to an important optimization problem arising in optimal sensitivity theory. The approach is to treat the multivariable problem exactly as the scalar problem in that stability constraints are handled via interpolation. The resulting computations are easily implemented using existing methods.