Mixed H/sub 2//H/sub /spl infin// filtering for uncertain systems with regional pole assignment

The mixed H/sub 2//H/sub /spl infin// filtering problem for uncertain linear continuous-time systems with regional pole assignment is considered. The purpose of the problem is to design an uncertainty-independent filter such that, for all admissible parameter uncertainties, the following filtering requirements are simultaneously satisfied: 1) the filtering process is asymptotically stable; 2) the poles of the filtering matrix are located inside a prescribed region that compasses the vertical strips, horizontal strips, disks, or conic sectors; 3) both the H/sub 2/ norm and the H/sub /spl infin// norm on the respective transfer functions are not more than the specified upper bound constraints. We establish a general framework to solve the addressed multiobjective filtering problem completely. In particular, we derive necessary and sufficient conditions for the solvability of the problem in terms of a set of feasible linear matrix inequalities (LMIs). An illustrative example is given to illustrate the design procedures and performances of the proposed method.     

Robust H/sub /spl infin// filtering of fuzzy dynamic systems

Robust H/sub /spl infin// filtering of complex nonlinear systems which can be represented by a fuzzy dynamic model is presented. Based on a nominal model, a common positive definite matrix P, and a piecewise continuous Lyapunov function respectively, three kinds of new filtering design methods are proposed using quadratic stability theory and linear matrix inequalities (LMIs). It is shown that the filtering system is quadratically stable with disturbance attenuation if there exists a positive definite matrix solution to a LMI or a set of LMIs. An example is also given to demonstrate the performance of the proposed filtering design methods.     

Robust neuro-H/sub /spl infin// controller design for aircraft auto-landing

A robust neuro-control scheme is presented for aircraft auto-landing under severe wind conditions and partial loss of control surfaces. In the scheme, a dynamic radial basis function network (RBFN) called minimal resource allocating network (MRAN), that incorporates a growing and pruning strategy, is utilize to aid an H/sub /spl infin// controller using a feedback-error-learning mechanism. The neural network uses only online learning and is not trained "a priori". Specifically, the performance of this neuro-controller for aircraft auto-landing in a microburst along with a partial loss of control effectiveness is analyzed and compared with other control schemes. Simulation studies show that the performance obtained by the neuro-H/sub /spl infin// control scheme is better than the other control schemes under failure and extreme wind conditions.     

Explicit formulas for two state Kalman, H/sub 2/ and H/sub /spl infin// target tracking filters

The continuous time, two state, target tracking problem is considered from the Kalman, H/sub 2/, and H/sub /spl infin// filter viewpoint. While previous treatments were numerical in nature, analytic transient responses and infinite horizon solutions with analytic performance expressions are presented here. Tracking indices, involving the maneuver and measurement uncertainties, are shown to have a role for both the steady state and transient responses. In addition, the H/sub /spl infin// tracker has a sensor index involving the performance bound and measurement uncertainty, which, along with the tracking index, plays a significant role in the H/sub /spl infin// tracker expressions. Analytical expressions for the probability of target escape, the probability that the target position will be outside the radar beamwidth (BW), are developed not only to compare the performance of various trackers, but also as a design tool to meet tracking specifications. Examples illustrate the performance of the target trackers as a function of the error gain upper bound.     

Problem of precision missile guidance: LQR and H/sup /spl infin// control frameworks

Addressed here is the precision missile guidance problem where the successful intercept criterion has been defined in terms of both minimizing the miss distance and controlling the missile body attitude with respect to the target at the terminal point. We show that the H/sup /spl infin// control theory, when suitably modified, provides an effective framework for the precision missile guidance problem. The existence of feedback controllers (guidance laws) is investigated for the case of finite horizon and non-zero initial conditions. Both state feedback and output feedback implementations are explored.     

Discrete-time min-max tracking

The problem of optimal state estimation of linear discrete-time systems with measured outputs that are corrupted by additive white noise is addressed. Such estimation is often encountered in problems of target tracking where the target dynamics is driven by finite energy signals, whereas the measurement noise is approximated by white noise. The relevant cost function for such tracking problems is the expected value of the standard H/sub /spl infin// performance index, with respect to the measurement noise statistics. The estimator, serving as a tracking filter, tries to minimize the mean-square estimation error, and the exogenous disturbance, which may represent the target maneuvers, tries to maximize this error while being penalized for its energy. The solution, which is obtained by completing the cost function to squares, is shown to satisfy also the matrix version of the maximum principle. The solution is derived in terms of two coupled Riccati difference equations from which the filter gains are derived. In the case where an infinite penalty is imposed on the energy of the exogenous disturbance, the celebrated discrete-time Kalman filter is recovered. A local iterations scheme which is based on linear matrix inequalities is proposed to solve these equations. An illustrative example is given where the velocity of a maneuvering target has to be estimated utilizing noisy measurements of the target position.     

Nonlinear robust observer design for strapdown INS in-flight alignment

A nonlinear observer is proposed for a strapdown inertial navigation system (SDINS) in-flight alignment problem using an H/sub /spl infin// filter Riccati equation and a freedom parameter. The proposed observer improves the filtering stability, convergence, and performance. The characteristics of the observer are analyzed using a Lyapunov function. Simulation results demonstrate a significant reduction in alignment errors by employing the proposed nonlinear observer. The observer is developed in general such that it can be applied to estimating nonlinear systems other than the SDINS in-flight alignment.     

Interval Kalman filtering

The classical Kalman filtering technique is extended to interval linear systems with the same statistical assumptions on noise, for which the classical technique is no longer applicable. Necessary interval analysis, particularly the notion of interval expectation, is reviewed and introduced. The interval Kalman filter (IKF) is then derived, which has the same structure as the classical algorithm, using no additional analysis or computation from such as H/sup /spl infin//-mathematics. A suboptimal IKF is suggested next, for the purpose of real-time implementation. Finally, computer simulations are shown to compare the new interval Kalman filtering algorithm with the classical Kalman filtering scheme and some other existing robust Kalman filtering methods.     

PCM/FM aeronautical telemetry in frequency selective multipath interference

The performance of PCM/FM using a delay-line detector in multipath interference is analyzed. In aeronautical telemetry applications, the multipath interference causes a in the signal spectrum which is web modeled by a channel composed of a line-of-sight signal and a strong specular reflection with magnitude /spl Gamma/ and excess delay less than a bit time. Analysis shows that the bit error probability is strongly dependent on the location of the within the spectrum. The bit error probability averaged over the location is also analyzed. For the case of no predetection filtering, the average bit error probability is dependent on the depth of the but not on the width. The loss in performance (relative to the AWGN environment) is bounded by (1-/spl Gamma/)/sup -2/ which is the depth of the . For the case of predetection filtering, the average bit error probability is dependent on both the width and depth of the . The performance loss is bounded by (1-/spl Gamma/)/sup -2/spl Gamma// which is less than that for the case of no predetection filtering.     

Modified Costas signal

A modification to the Costas signal is suggested. It involves an increase of the frequency separation /spl Delta/f beyond the inverse of the subpulse duration t/sub b/ combined with adding linear FM (LFM) with bandwidth B, in each subpulse. Specific relationships between /spl Delta/f and B will prevent autocorrelation grating lobes, that would normally appear when t/sub b//spl Delta/f>1.     

Sigma-mean monitoring for the local area augmentation of GPS

The local area augmentation system (LAAS) is a ground-based differential GPS system being developed to support aircraft precision approach and landing navigation with guaranteed integrity. To quantitatively appraise navigation integrity, an aircraft computes vertical and lateral protection levels using the standard deviation of pseudo-range correction errors, /spl sigma//sub pr/spl I.bar/gnd/, broadcast by the LAAS ground facility (LGF). Thus, one significant integrity risk is that the true standard deviation (sigma) of the pseudo-range correction error distribution may grow to exceed the broadcast correction error sigma or that the true mean of the correction error distribution becomes excessive during LAAS operation. This event may occur due to unexpected anomalies of GPS measurements. To insure that the true error distribution is bounded by a zero-mean Gaussian distribution with the broadcast sigma value, real-time sigma and mean monitoring is necessary. Both direct estimation and cumulative sum (CUSUM) methods are useful to detect violations with acceptable residual integrity risk. For sigma monitoring, the estimation method more rapidly detects small violations of /spl sigma//sub pr/spl I.bar/gnd/ but the fast initial response (FIR) CUSUM variant more promptly detects significant violations that would pose a larger threat to user integrity. For the purposes of mean monitoring, the FIR CUSUM variant is superior to the estimation method in detecting any mean violations. The results demonstrate that real-time protection is achievable against all sizes of sigma/mean failures that can threaten navigation integrity.     

基于LMI的鲁棒滤波在无人机飞控系统中的应用

针对无人机在实际飞行过程中存在外界干扰以及传感器量测噪声的问题,应用线性矩阵不等式理论对无人机飞控系统进行了降阶鲁棒滤波器设计.讨论了适用于连续系统的降阶鲁棒滤波算法以及滤波器存在的条件.最后,进行了无人机纵向高度保持阶段的数字仿真,给出迎角与俯仰角速度的仿真曲线,仿真结果验证了该算法的合理性和有效性.     

Application of velocity filtering to optical-flow passive ranging

The performance of the velocity filtering method as applied to optical-flow passive ranging under real-world conditions is evaluated. The theory of the 3-D Fourier transform as applied to constant-speed moving points is reviewed, and the space-domain shift-and-add algorithm is derived from the general 3-D matched filtering formulation. The constant-speed algorithm is then modified to fit the actual speed encountered in the optical flow application, and the passband of that filter is found in terms of depth (sensor/object distance) so as to cover any given range of depths. Two algorithmic solutions for the problems associated with pixel interpolation and object expansion are developed, and experimental results are presented     

LMI approach to the mixed H2/H∞filtering design for discrete-time uncertain systems

The problem of full-order robust filtering design for discrete-time uncertain linear systems is addressed. The uncertain parameters are assumed to belong to convex bounded domains (polytope type uncertainty). The main purpose is to design a stable linear filter such that the filtering error output signal remains bounded. For that, the parameterization of all linear filters assuring quadratic stability with an H_∞ attenuation constraint to the filtering error system is provided in terms of linear matrix inequalities (LMIs). Then, through the definition of an auxiliary cost, an upper bound to the filtering error variance is minimized, providing a mixed H₂/H _∞ guaranteed cost filtering design. Standard optimization procedures with global convergence assured can be used to solve the problem, as illustrated by an example     

A New Approach to Estimation of Initial Conditions and Smoothing Problems

A unified approach utilizing the Kalman-Bucy filtering technique istaken to solve the estimation problem of initial conditions and thesmoothing problem in linear dynamic systems. The equivalencebetween the forward integration method and the backward integrationmethod of the smoothing solution is proved. Complete analyticalsolutions of filtering and smoothing problems of rectilinear motion ofa randomly accelerated spacecraft are derived when the vehicle istracked by the ranging system at the ground station.     

Nullifying ACF grating lobes in stepped-frequency train of LFM pulses

An effective way to increase the bandwidth of a coherent pulse-train is to add a frequency step /spl Delta/f between consecutive pulses. A large /spl Delta/f implies a large total bandwidth, hence improved range resolution. However, when the product of the frequency step times the pulse-duration t/sub p/, is larger than one (t/sub p/ /spl Delta/f > 1), the autocorrelation function (ACF) of the stepped-frequency pulse-train suffers from ambiguous peaks, known as "grating lobes." It is well known that replacing the fixed-frequency pulses with linear FM (LFM) pulses of bandwidth B can reduce those grating lobes. We present a simple analytic expression for the ambiguity function (AF) and ACF of such a signal and derive from it very simple relationships between /spl Delta/f, B, and t/sub p/ that will place s exactly where the grating lobes are located, and thus remove them completely.     

Theorem for the combination of bistatic radar measurements using least squares

In order to improve position finding performance, least squares method is often used to combine the measurement sets of bistatic radar system. However, which measurement sets can be combined by least squares method and which cannot have received little attention until now. We address this issue based on 2 measurements of bistatic radar system, for example (/spl rho/, /spl theta//sub T/), and present a new theorem, with proof, which shows that the least squares estimator can be obtained by combining any two measurement sets if these measurement pairs are disjoint. We provide an example that satisfies this condition, which shows that the least square combination of measurement sets yield improved performance especially in the vicinity of the transmitter and the receiver.     

Control of a large space structure using MMAE/MMAC techniques

The application of moving-bank multiple model adaptive estimation and control (MMAE/MMAC) algorithms to an actual spade structure (Space Integrated Controls Experiment (SPICE)) being examined at Phillips Laboratory at Kirtland AFB, NM, is presented. The structure consists of a large platform and a smaller platform connected by three legs in a tripod fashion. Kalman filtering and LQG (linear system, quadratic cost, Gaussian noise) control techniques are utilized as the primary design tools for the components of the MMAE/MMAC. Implementing a bank of filters or controllers increases the robustness of the algorithms when uncertainties exist in the system model, whereas the moving bank is utilized to reduce the computational load. Several reduced-order models are developed from the truth model using modal analysis and modal cost analysis. The MMAE/MMAC design with a substantially reduced-order filter model provides an excellent method to estimate a wide range of parameter variations and to quell oscillations in the structure.     

利用遗传算法和LMI设计固定结构H2/H∞飞行控制律

 在设计飞翼式无人机(UAV)的横航向飞行控制系统时,为了使无人机具有较好的动态特性和阵风抑制能力,同时又便于工程实现,提出了固定结构的H₂/H_∞控制律设计方法。对于由此遇到的双线性矩阵不等式(BMI)问题,先用线性矩阵不等式(LMI)方法得到控制律参数和H₂/H_∞性能指标的映射关系,再用此映射关系作为适应度函数,用改进的遗传算法求解使H₂/H_∞性能最优的控制律参数。仿真结果表明,使用固定结构的H₂/H_∞控制方法的无人机动态响应迅速平滑,在侧风干扰下的滚转角振荡幅值仅是原经典控制方法的一半。     

1/spl phi/ 3W grid-connection PV power inverter with partial active power filter

This paper presents a single-phase three-wire (1/spl phi/ 3W) grid-connection photovoltaic (PV) power inverter with a of partial active power filter (PAPF) feature, which can not only deal with PV power but filter current harmonics and improve power factor. Once the processed power exceeds the switch ratings, the inverter can reduce its output reactive power and harmonic power, while still supplying the maximum real power generated by the PV arrays. In the derivation of control laws, a limit circle is defined to confine the output power of the inverter. To determine the power that the inverter can process, the instantaneous reactive power of a 1/spl phi/ 3W system is defined and used to calculate reactive power, which can avoid complex detections of phase angle and magnitude of the fundamental component of a nonlinear load current. Simulation results and experimental measurements have verified the proposed algorithm and the feasibility of the inverter.