State estimation of fast-rate systems using slow-rate image sensors

Tani, Jacopo; Mishra, Sandipan; Wen, John T.

doi:10.1109/acc.2013.6580809

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…In vision-based control system [5], it often takes a long period to obtain and process the information of one frame image, while the controller has a fast updating period. Additionally, multirate cases are quite common in chemical process industry [22] and mechanical systems [23]. By the virtue of DUEA technique, several robust control methods have been developed for multi-rate systems, see [24].…”

Section: Introductionmentioning

confidence: 99%

Predictor-Based Extended State Observer for Disturbance Rejection Control of Multirate Systems With Measurement Delay

Sun

Yang

et al. 2023

IEEE Trans. Ind. Electron.

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Section: Introductionmentioning

confidence: 99%

Predictor-Based Extended State Observer for Disturbance Rejection Control of Multirate Systems With Measurement Delay

Sun

Yang

et al. 2023

IEEE Trans. Ind. Electron.

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“…Note that multi-rate control systems subject to more than one sampling/updating frequency are quite common in many practical applications, such as hard disk drive head position control systems [33], chemical process industry [34], mechanical systems [35], and NCSs [36], [37]. Actually, there are different reasons that practical systems are subject to multirate.…”

Section: Introductionmentioning

confidence: 99%

“…On the one hand, [36], [37] proposed a new framework of multi-rate NCS in order to reduce communication/energy burden, it has been shown that compared with single-rate design, multi-rate approach can achieve an impressive reduction of the communication bandwidth. On the other hand, due to the restrictions of sensor hardwares or data processing speed, it is common to generate measurement output at a relatively slow-rate, while a fast-rate sampled-data controller is generally applied to enhance the control performance and reduce the possible vibration excitations [33], [35]. For example, a new prediction-correction method was proposed to reconstruct states and disturbances in [31], [33], where estimate needs to be corrected by using the latest sampled output at every sampling time instant.…”

Section: Introductionmentioning

confidence: 99%

“…Taking the Euclidean norm of the two sides of(35), we arrive at||x((i + 1)T )|| ≤ ||A d ||||x(iT )|| + || T As dsBK||||e x (iT )|| + || (i+1)T iT e A((i+1)T −s) B(d(s) − d(iT ))ds|| + || T As dsB||(δ 0 || x(iT )|| + δ 1 ) ≤ ||A d || + || T As dsB||δ 0 ||x(iT )|| + || T As dsBK||||e x (iT )|| + δ 0 || T As dsB||||e x (iT )|| + || (i+1)T iT e A((i+1)T −s) B(d(s) − d(iT ))ds|| + || T As dsB||δ 1 .…”

mentioning

confidence: 99%

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Predictor-Based Periodic Event-Triggered Control for Dual-Rate Networked Control Systems With Disturbances

Sun

Yang

et al. 2022

IEEE Trans. Cybern.

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This paper considers the problem of periodic eventtriggered control design for dual-rate networked control system subject to non-vanishing disturbance. The plant considered in this paper is a kind of dual-rate networked control system, where sensor samples the measurement output at a slow-rate and actuator updates the control input at a fast-rate. Despite the slow-rate sampling of sensor, a new output predictor-based observer is proposed to accurately estimate system state and disturbance in the inter-sample time interval, and an active antidisturbance controller that updates at a fast-rate is accordingly proposed, such that the desirable control performance and disturbance rejection performance can be achieved. At each fastrate updating time instant, we use the prediction technique to generate a data packet including the computed current control input and the predicted values of the control inputs for the future finite steps, and design a new periodic event-triggered mechanism to determine whether to transmit the data packet via communication network or not. The proposed control method is easily implemented in digital platform since it has a discretetime form. To verify the effectiveness of the proposed control method, we finally present the simulation results of a practical speed control system.

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“…The WKS theorem prescribes limits to the frequency content of the reconstructed signal based on the sampling period. However, the image blur contains more information on the dynamics of the observed feature than the centroid provides [10][11][12], which can be exploited to address this sampling limitation. In essence, 1 Copyright c 2014 by ASME we treat the image sensor as a temporal to spatial (pixel domain) transformation.…”

Section: Introductionmentioning

confidence: 99%

On Derivative Sampling From Image Blur for Reconstruction of Band-Limited Signals

Tani

Mishra

Wen

2014

Volume 3: Industrial Applications; Modeling for Oil and Gas, Control and Validation, Estimation, and Control of Automotive Syst

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Image sensors are typically characterized by slow sampling rates, which limit their efficacy in signal reconstruction applications. Their integrative nature though produces image blur when the exposure window is long enough to capture relative motion of the observed object relative to the sensor. Image blur contains more information on the observed dynamics than the typically used centroids, i.e., time averages of the motion within the exposure window. Parameters characterizing the observed motion, such as the signal derivatives at specified sampling instants, can be used for signal reconstruction through the derivative sampling extension of the known sampling theorem. Using slow image based sensors as derivative samplers allows for reconstruction of faster signals, overcoming Nyquist limitations. In this manuscript, we present an algorithm to extract values of a signal and its derivatives from blurred image measurements at specified sampling instants, i.e. the center of the exposure windows, show its application in two signal reconstruction numerical examples and provide a numerical study on the sensitivity of the extracted values to significant problem parameters. Fig. 10 shows the evolution of the means of the reconstruction errorsε (i) Exposure Window

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State estimation of fast-rate systems using slow-rate image sensors

Cited by 5 publications

References 13 publications

Predictor-Based Extended State Observer for Disturbance Rejection Control of Multirate Systems With Measurement Delay

Predictor-Based Extended State Observer for Disturbance Rejection Control of Multirate Systems With Measurement Delay

Predictor-Based Periodic Event-Triggered Control for Dual-Rate Networked Control Systems With Disturbances

On Derivative Sampling From Image Blur for Reconstruction of Band-Limited Signals

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