A STUDY ON DISTRIBUTED RECEDING HORIZON CONTROL

We consider a distributed control problem comprising of multiple sub-systems with one-controller at each sub-system. We apply a recent result about suboptimal receding horizon control that analytically relates a receding horizon control suboptimal solution and system performance loss to quantify the necessary number of iterations for the dual and primal decomposition algorithm to achieve a solution that guarantees stability. We also use this result to explore the idea of "incremental robustness", meaning that the overall system is robustly stable and its performance varies gracefully with the inclusion of sub-systems and sub-controllers. We demonstrate these ideas in a consensus seeking and a formation control problem and provide simulation results. To our best knowledge, this is the first time the result is applied to a distributed receding horizon control framework based on dual and primal decomposition

Anytime Control using Input Sequences with Markovian Processor Availability

We study an anytime control algorithm for situations where the processing resources available for control are time-varying in an a priori unknown fashion. Thus, at times, processing resources are insufficient to calculate control inputs. To address this issue, the algorithm calculates sequences of tentative future control inputs whenever possible, which are then buffered for possible future use. We assume that the processor availability is correlated so that the number of control inputs calculated at any time step is described by a Markov chain. Using a Lyapunov function based approach we derive sufficient conditions for stochastic stability of the closed loop.Comment: IEEE Transactions on Automatic Control, to be publishe

Stochastic Stability of Event-triggered Anytime Control

We investigate control of a non-linear process when communication and processing capabilities are limited. The sensor communicates with a controller node through an erasure channel which introduces i.i.d. packet dropouts. Processor availability for control is random and, at times, insufficient to calculate plant inputs. To make efficient use of communication and processing resources, the sensor only transmits when the plant state lies outside a bounded target set. Control calculations are triggered by the received data. If a plant state measurement is successfully received and while the processor is available for control, the algorithm recursively calculates a sequence of tentative plant inputs, which are stored in a buffer for potential future use. This safeguards for time-steps when the processor is unavailable for control. We derive sufficient conditions on system parameters for stochastic stability of the closed loop and illustrate performance gains through numerical studies.Comment: IEEE Transactions on Automatic Control, under revie

Two Applications of Instantaneous Frequency to Signal Analysis and Estimation

本論文提出瞬時頻率在信號分析與信號估測上的兩個應用。第一個應用是分析名為復古現象的飛行載具縱向長周期振動。在此處，提出利用一個希爾伯特-黃轉換(HHT)來分析此時域上的物理測量數據。這個方法是以稱為經驗模態分解(EMD)的方式產生一組本質模態函數(IMF)為基礎。HHT適用於非穩態與非線性的數據分析，及找出數據包括頻率的瞬時特性是其的主要概念。此外，結合快速傅利業轉換(FFT)與EMD呈現出與HHT不同的結果。在復古的分析中，利用實際動態GPS測量所得的飛行數據，我們呈現出非穩態信號分析(HHT)和傳統以傅利業為基礎之方法的比較。 在本論文的第二個部分，我們提出一個利用適應性全通帶式凹谷濾波器(ANFA)搭配上高斯-牛頓演算法作為GPS抗窄頻干擾系統的應用。在模擬中考慮了穩態及非穩態的干擾。ANFA可以即時的估測干擾的瞬時頻率且它比傳統的時域適應預估器有較好的均方預估誤差(MSPE)與信號雜訊改善率(SNR)。This thesis deals with two applications of instantaneous frequency to signal analysis and estimation. The first application is the analysis of aircraft longitudinal long-period oscillation named phugoid phenomenon. A Hilbert-Huang Transform (HHT) is proposed here to analyze the physical measurements in time domain. It is based on the empirical mode decomposition (EMD), which generate a set of intrinsic mode functions (IMF). The HHT is applicable to non-stationary and nonlinear data analysis, and finding out the instantaneous characteristics including frequency of the data is its main part. Besides, combining Fast Fourier Transform (FFT) with EMD shows the different results with HHT. In the phugoid analysis, we present the comparison between the non-stationary signal analysis, HHT, and the conventional Fourier based method from the real-time flight test data measured by kinematic GPS. In the second part of this thesis, an application of adaptive all-pass based notch filter (ANFA) with Gaussian-Newton adaptive algorithm in a GPS narrowband anti-jamming system was presented. In the simulations, there are several stationary and non-stationary interferences considered. The ANFA can estimate the instantaneous frequency of the jamming in real-time, and it achieves a better performance than the conventional time-domain adaptive predictors in terms of mean squared prediction error (MSPE) and signal-to-noise ratio (SNR) improvement.1. Introduction………………………………………………………1 2. Hilbert-Huang Transform…………………………………………4 2.1 Background of the Technology………………………………4 2.2 Details of Hilbert-Huang Transform………………………5 3. Application of the Hilbert-Huang Transform……………12 3.1 Background of Research……………………………………12 3.2 Research Methods and Analysis Results………………13 Appendix 3.1………………………………………………………33 Appendix 3.2………………………………………………………35 4. Design of GPS Narrowband Anti-Jamming Receiver by Adaptive All-pass Based Notch Filter…………………………37 4.1 Introduction of the Anti-jamming System Design……37 4.2 Signal Model Description……………………………38 4.3 Linear Predictor………………………………………40 4.4 Adaptive All-pass Based Notch Filter…………………41 4.5 Design Steps…………………………………………………42 4.6 Adaptive Algorithm…………………………………………44 4.7 Simulation Results…………………………………………48 5. Conclusions……………………………………………………58 5.1 Concluding Remarks…………………………………………58 5.2 Future Works…………………………………………………59 5.3 Acknowledgement……………………………………………60 Bibliography………………………………………………………6

A Study of Estimation and Communication Tradeoff using an Event-based Approach

In this paper, we consider estimating the state of a linear time-invariant system over a network subject to limited sensor communications. A sensor locally computes the state estimate for the system from its observations and send it to a remote estimator under the constraint that the total transmission times are no more than a pre-specified value. The sensor needs to decide when to send the local estimate in order to minimize the average estimation error covariance at the remote estimator. Offline scheduling and online scheduling policies are two typical solutions. The main contribution of this paper is that we propose a novel form of hybrid scheduling policies, which combine the two conventional ones and demonstrate that the estimator performance is improved when compared with the optimal offline schedule while the computation complexity is reduced when compared with the optimal online schedule. Therefore, the proposed schedules provide a trade-off between the two classic approaches in terms of estimation quality and computation complexity

Algorithms for Control with Limited Processing and Communication Resources

In networked and embedded systems, it is often the case that the communication and processing resources are shared among multiple processes or control loops. Thus, the availability of these resources for any particular loop is usually time-varying. Even though the availability on average may be sufficiently large, at particular time steps, only limited communication bandwidth or processor attention may be available. This is the reason for the recent interest in the area of control with limited communication and processing resources.</p