Design of Lifted Dual-Rate Digital Controllers for X-38 Vehicle

Shieh, Leang-San; Wang, Weimin; Bain, John; Sunkel, John W.

doi:10.2514/2.4608

Cited by 29 publications

(15 citation statements)

References 15 publications

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“…According to the lifting methodology [Bamieh et al, 1991;Shieh et al, 2000], we use an evaluative state-feedback equation derived from the original discrete-time state-feedback equation to develop a lifted digital controller so that the developed lifted digital controller of the sampled-data system during a period (t = kT ∼ kT + T ) can closely match the control input of the original continuoustime system, which is shown in Fig. 4.…”

Section: Lifted Prediction-based Digital Redesign Methodsmentioning

confidence: 99%

Lifted Digital Redesign of Prediction-Based Digital Controller for Hybrid Chaotic System

Wang

Tsai

et al. 2004

Int. J. Bifurcation Chaos

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Tracking a periodic orbit of a chaotic attractor has been a considerable challenge since it often encounters numerical sensitivity. In this paper, a lifted prediction-based low-gain digital controller obtained from a predesigned high-gain analog controller is developed and applied to the hybrid chaotic system. The new proposed digital tracker with a relatively longer sampling time is insensitive to numerical errors and performs better than the one developed via the existing prediction-based digital redesign method. The Chen and Chua attractors are used as illustrative examples to demonstrate the effectiveness of the proposed lifted digital redesign method.

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Section: Lifted Prediction-based Digital Redesign Methodsmentioning

confidence: 99%

Lifted Digital Redesign of Prediction-Based Digital Controller for Hybrid Chaotic System

Wang

Tsai

et al. 2004

Int. J. Bifurcation Chaos

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“…6, one can see that the disruptive property is satisfied; that is, As another example, we consider the X-38 vehicle model which is a prototype flight test vehicles for crew return vehicle [13]. In [13], the X-38 is operated by a multi-rate digital controller whose holder operates four times faster than the sampler (i.e., R = T s /T a = 4) with T a = 0.04 sec and T s = 0.16 sec. The X-38 model has 3 inputs, 9 outputs, and 11 states (A ∈ R 11×11 , B ∈ R 11×3 , and C ∈ R 9×11 ).…”

Section: Procedures Of Attack Signal Generationmentioning

confidence: 99%

“…These multi-rate sampling schemes have been widely studied in the literature for specific purposes. For example, a faster actuation than sensing has been adopted to improve control performance such as inter-sample behavior, disturbance rejection, and so on [13]- [17]. On the other hand, faster sensing has advantages on state feedback control design, acceleration control, and security problem [18]- [20].…”

Section: Introductionmentioning

confidence: 99%

Masking attack for sampled‐data systems via input redundancy

Kim

Park

Shim

et al. 2019

IET Control Theory & Applications

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In this paper, we introduce a new vulnerability of cyber-physical systems to malicious attack. It arises when the physical plant, that is modeled as a continuous-time LTI system, is controlled by a digital controller. In the sampled-data framework, most anomaly detectors monitor the plant's output only at discrete time instants, and thus, nothing abnormal can be detected as long as the sampled output behaves normal. This implies that if an actuator attack drives the plant's state to pass through the kernel of the output matrix at each sensing time, then the attack compromises the system while remaining stealthy. We show that this type of attack always exists when the sampleddata system has an input redundancy, i.e., the number of inputs being larger than that of the outputs or the sampling rate of the actuators being higher than that of the sensors. Simulation results for the X-38 vehicle and for the other numerical examples illustrate this new attack strategy possibly brings disastrous consequences.

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“…On way to address the sampled-data control is to develop a discrete-time model for the controlled, continuous-time plant and then pursue a digital controller based on the discretized model. This approach has been basically applicable for linear time-invariant (LTI) systems [8,9,12,13,14,15,16,10,11].…”

Section: Introductionmentioning

confidence: 99%

“…In practical applications, however, hardware restrictions can make two periods different essentially. There have been some investigations focusing on the multirate digital control of LTI systems from several disparate perspectives [12,13,14,15,16]. However, until now, no tractable method for the multirate digital fuzzy control has been proposed, with perhaps a few exceptions [6].…”

Section: Introductionmentioning

confidence: 99%

Stabilization of Multirate Sampled-Data Fuzzy Systems Based on an Approximate Discrete-Time Model

Kim

Park

Joo

2006

Fuzzy Systems and Knowledge Discovery

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This paper studies a stabilization problem for a multirate digital control of fuzzy systems based on the approximately discretized model. In the multirate control scheme, a numerical integration scheme is used to approximately predict the current state from the state measured at the sampling points. It is shown that the multirate digital fuzzy controller stabilizing an approximate discrete-time fuzzy model would also stabilize the sampled-data fuzzy system in the sufficiently small control update time. Furthermore, some sufficient conditions for the stabilization of the approximate discrete-time fuzzy model are provided under the delta-operator frame work, which are expressed as the linear matrix inequalities (LMIs) and thereby easily tractable by the convex optimization techniques. A numerical example is demonstrated to visualize the feasibility of the developed methodology.

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Design of Lifted Dual-Rate Digital Controllers for X-38 Vehicle

Cited by 29 publications

References 15 publications

Lifted Digital Redesign of Prediction-Based Digital Controller for Hybrid Chaotic System

Lifted Digital Redesign of Prediction-Based Digital Controller for Hybrid Chaotic System

Masking attack for sampled‐data systems via input redundancy

Stabilization of Multirate Sampled-Data Fuzzy Systems Based on an Approximate Discrete-Time Model

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