Multi-rate Sampling Systems Research Articles

Sequential fusion estimation for multisensor multirate systems with measurement outliers

AbstractThis paper investigates the suboptimal sequential fusion estimation problem for multisensor multirate networked systems with colored measurement noises under the interference of measurement outliers. The saturation function is used to constrain the innovation polluted by measurement outliers. Due to diverse physical restrictions, the sampling period of the sensor is assumed to be different from the update period of the system state, thereby better reflecting the engineering practice. The lifting technique is used to convert the multirate sampling system into a single‐rate form. By solving the matrix difference equation, an upper bound of the filtering error covariance is obtained, and the filter gain is then derived, which can minimize the upper bound of the error covariance. Finally, a simulation example is given to demonstrate the effectiveness of the proposed sequential fusion method for multirate sampling systems under outlier interference.

Biprobes Blade Tip Timing Method for Frequency Identification Based on Active Aliasing Time-Delay Estimation and Dealiasing

Rotating blades are key turbomachinery components with high failure risk due to harsh working conditions. Thus, monitoring the running state of blades is urgently required. Blade tip timing (BTT) is regarded as a potential technology for blade vibration monitoring owing to its noncontact nature and low cost. However, severe undersampling and strict probe layout hinder the application of BTT. As a result of severe undersampling, aliasing and its suppression are the main research topics in BTT. However, in this article, a biprobes method for BTT based on the utilization of aliasing is proposed to identify the natural frequencies of blades. Active aliasing is used in this method to produce aliasing findings at various equivalent sampling frequencies, and the closed-form robust Chinese remainder theorem is used for dealiasing. Unlike the conventional multirate sampling systems for BTT that use a multiprobe configuration or varied speed, the suggested method utilizes varying delay durations to obtain varying equivalent sample frequencies. Furthermore, to ensure that active aliasing and dealiasing form a closed loop, an included angle coprime layout is proposed. Finally, the robustness and effectiveness of the proposed method are verified through numerical and experimental validation.

Outlier-resistant interval observer design for multirate time-delayed systems under the adaptive event-triggered protocols

In this paper, an interval observer has been presented for a type of multirate time-delayed systems subject to measurement outliers under the adaptive event-triggered protocol (AETP). First of all, the multirate sampling system is studied to meet the practical requirements. Meanwhile, for relieving the communication burden, an AETP is considered to schedule the measurement information received by the observer. The augmented system is built at a consistent sampling/update rate by using the lifting technique. Moreover, the occurrence of measurement outliers would pose some serious threats to the reliability of the systems. For the addressed issue, an outlier-resistant interval observer is developed by means of saturation function to weaken the impact of the measurement outliers. A sufficient condition is proposed by using the positive system theory and Lyapunov stability theory to ensure that the interval observer is effective and the error system is input-to-state stable. Besides, the gain matrices of the interval observer are obtained by solving a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed interval observer is verified by a numerical simulation.

Estimator for Multirate Sampling Systems With Multiple Random Measurement Time Delays

The optimal linear estimation problem is studied for multirate sampling systems with multiple random measurement time delays (TDs). The considered multirate sampling scheme is that the sensor uniformly samples at a slow rate and the state uniformly updates at a fast rate. Known stochastic variable sequences obeying Bernoulli distributions are adopted to depict random measurement TDs, including missing measurements as a special case. First, using a state iterating method, the original system with multirate sampling and delayed measurements is transformed into a state-space model with single-rate sampling and delay-free measurements at measurement sampling (MS) instants. Then, by utilizing projection theory, a nonaugmented recursive optimal linear state filter is presented based on the established model in the linear minimum variance sense, where the estimators for the process noise are involved. Furthermore, the state estimator at state update instants is achieved through filtering or prediction based on the filter at MS instants. Finally, the centralized fusion estimator and the distributed covariance intersection fusion estimator are proposed for the multisensor case. Simulation research on a vehicle suspension system verifies the effectiveness of the algorithms.

On Some Sufficiency-Type Stability and Linear State-Feedback Stabilization Conditions for a Class of Multirate Discrete-Time Systems

This paper presents and discusses the stability of a discrete multirate sampling system whose sets of sampling rates (or sampling periods) are the integer multiple of those operating on all the preceding substates. Each of such substates is associated with a particular sampling rate. The sufficiency-type stability conditions are derived based on simple conditions on the norm, spectral radius and numerical radius of the matrix of the dynamics of a system parameterized at the largest sampling period.

Model Following Adaptive Control of Multirate Sampling Systems

This paper deals with model following adaptive control of linear time-invariant systems with two sampling rates : a slower one for the output and a faster one for the input. It is known that intersample ripples often arise in the outputs of the closed-loop multirate sampling systems although multirate control has interesting advantages. In this paper, a ripple-suppressed multirate model following control scheme is presented. A state observer is designed at the output sampling instants and a filter is constructed at the input sampling instants in order to estimate the output at the intersample instants of the outputs. Next, an adaptive version of the algorithm for systems with unknown parameters is shown. Experimental results applied to a position servo system with a supersonic sensor are given to indicate the effectiveness.

Modeling and Simulation of Dynamic Structure Heterogeneous Flow Systems

The author presents the Heterogeneous Flow System Specification (HFSS), a formalism suited to represent combined (discrete/continuous) systems. The new formalism is based on the concept of sampling that is described in general terms to include multirate sampling systems. The HFSS formalism permits the construction of continuous/discrete input/output models in a modular and hierarchical manner. Hierarchical systems have a dynamic structure nature that can be changed over time. To show an application of the HFSS formalism, the author presents a new formalism to numerically solve differential equations with discontinuities using multirate integration methods. Applications of combined and dynamic structure systems are presented.