Observers for linear systems with quantized outputs

SUMMARYThis study addresses a discretization method with Lebesgue sampling for a type of nonlinear system, and proposes a control method based on the discrete system model. A cart-pendulum system is used as an example. Applying this control method to some real system, a crucial problem is how to implement the controller. To overcome the problem, an impulsive Luenberger observer is introduced with numerical forward mapping from the current system state to the one-step-ahead state by the well-known RungeKutta method. As a result, a cart-pendulum system with a rotary encoder, whose quantization interval is relatively large, can be controlled effectively. Numerical simulations are performed to verify the effectiveness of the proposed method. C⃝ 2014 Wiley Periodicals, Inc. Electron Comm Jpn, 97(11): 10-18, 2014; Published online in Wiley Online Library (wileyonlinelibrary.com).

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“…Thus the system states are estimated with regard to quantization using the ILO [6,8]. In the ILO, the estimated statex at quanti-…”

Section: The Impulsive Luenberger Observermentioning

confidence: 99%

Discretization and Control of Rotating Pendulum under Lebesgue Sampling

Ohsaki

Iwase

Hatakeyama

2014

Elect Comm in Japan

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“…When a continuous-time plant is controlled through a digital controller, side effects such as time-delays, asynchronism, quantization, (see Elia and Mitter (2001) and references therein), can turn into an excessive performance degradation like the appearance of limit cycles, chaotic phenomena or even instability of the closed-loop system, (Ceragioli & De Persis, 2007;Delchamps, 1990). Concerning the effect of quantization in control systems, such a topic has been extensively addressed by researchers over the last years; see, e.g., Brockett and Liberzon (2000), Ceragioli and De Persis (2007), Coutinho, Fu, and de Souza (2010), Delchamps (1990), Fu and Xie (2005), Liberzon (2003), Sur and Paden (1997) and Tarbouriech and Gouaisbaut (2012) just to cite a few. ✩ This work has been supported by ANR project LimICoS contract number 12 BS03 00501.…”

Section: Introductionmentioning

confidence: 98%

Stabilization of continuous-time linear systems subject to input quantization

2015

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“…The design of observer in quantized output system is proposed in [12]. The approach in [12] is developed in [13]. The effectiveness of the related approach [13] is verified through simulations.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome the problem, an actual state is estimated from a quantized state. The design of observer in quantized output system is proposed in [12]. The approach in [12] is developed in [13].…”

Section: Introductionmentioning

confidence: 99%

State estimation in quantized feedback control system

Ohtsuka

Zanma

Liu

2014

2014 IEEE 13th International Workshop on Advanced Motion Control (AMC)

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Recently, by development of communication techniques, control via communication is expected to take important part in networked control systems (NCSs) and so on. The main problem of the NCSs is that data are transmitted via a communication channel which has a constraint of capacity by converting a continuous signal into a discrete signal by using quantizer to compress the amount of information. Therefore, the discrete signal has a margin of error called quantization error. In the quantized feedback control systems, we use an observer to estimate a state if the state is not available, and use the estimated state in feedback control. In such cases, the system may be unstable and degraded the performance since the states estimation is not performed properly due to the quantization error. Hence, an state estimator must be designed with taking into account the effect of quantization error. In this paper, we propose a designing state estimator method in discrete-time systems with the quantized output. The effectiveness of the proposed method is illustrated with experiments.

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Observers for linear systems with quantized outputs

Cited by 27 publications

References 9 publications

Discretization and Control of Rotating Pendulum under Lebesgue Sampling

Discretization and Control of Rotating Pendulum under Lebesgue Sampling

Stabilization of continuous-time linear systems subject to input quantization

State estimation in quantized feedback control system

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