Stochastic analysis and control of real-time systems with random time delays

Nilsson, Johan; Bernhardsson, Bo; Wittenmark, Björn

doi:10.1016/s0005-1098(97)00170-2

Cited by 842 publications

(314 citation statements)

References 7 publications

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“…A lot of work is done to deal with this delay with observers and predictors [10][11][12][13][14] and to prove the stability of systems suffering from variable transmission delays [15,16]. There is not much literature about wireless control applications.…”

Section: Introductionmentioning

confidence: 99%

Low‐Latency Wireless Data Transfer for Motion Control

Boeij

Haazen

Smulders

et al. 2009

Journal of Control Science and Engineering

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This paper discusses a new approach for wireless motion control. Existing wireless techniques suffer from large closed loop delays of several milliseconds, which is unacceptable in precision motion systems. These large delays are mainly caused by the protocol used, since these are optimized for transferring large amounts of data, not to minimize transmission delay. A new protocol and wireless system are proposed that reduce the closed loop transmission delay to less than 300 microseconds. The system has been verified in a real control system, and measurements show the performance, which is more than ten times better than existing techniques.

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Section: Introductionmentioning

confidence: 99%

Low‐Latency Wireless Data Transfer for Motion Control

Boeij

Haazen

Smulders

et al. 2009

Journal of Control Science and Engineering

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“…Many issues arise in the design of networked controllers and the associated communication systems, including bit rate limitations [WB99, NE00, TSM98], communication delays [NBW98], data packet loss [XHH00], transmission errors [SSK99], and asynchronicity [Özg89]. In this paper we consider only the first issue, i.e., bit rate limitations.…”

Section: Introductionmentioning

confidence: 99%

Joint Optimization of Wireless Communication and Networked Control Systems

Xiao

Johansson

Hindi

et al. 2005

Switching and Learning in Feedback Systems

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Abstract. We consider a linear system, such as an estimator or a controller, in which several signals are transmitted over wireless communication channels. With the coding and medium access schemes of the communication system fixed, the achievable bit rates are determined by the allocation of communications resources such as transmit powers and bandwidths, to different channels. Assuming conventional uniform quantization and a standard white-noise model for quantization errors, we consider two specific problems. In the first, we assume that the linear system is fixed and address the problem of allocating communication resources to optimize system performance. We observe that this problem is often convex (at least, when we ignore the constraint that individual quantizers have an integral number of bits), hence readily solved. We describe a dual decomposition method for solving these problems that exploits the problem structure. We briefly describe how the integer bit constraints can be handled, and give a bound on how suboptimal these heuristics can be. The second problem we consider is that of jointly allocating communication resources and designing the linear system in order to optimize system performance. This problem is in general not convex. We present an iterative heuristic method based on alternating convex optimization over subsets of variables, which appears to work well in practice.

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“…그러나 FTNCS를 실제 시스템에 적용하기 위해서는 네트 워크 전송지연과 데이터 분실(packet loss)에 따른 시스템의 성 능저하 또는 불안정 문제를 반드시 해결할 필요가 있다 [12,15]. 전송지연/분실 문제를 해결하기 위해서 확률제어 [15,16], 예측제어 [17,18], 견실제어 [19] …”

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Fault-Tolerant Control System for Unmanned Aerial Vehicle Using Smart Actuators and Control Allocation

Yang¹,

Kim²,

Lee³

2011

Journal of Institute of Control, Robotics and Systems

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This paper presents a FTNCS (Fault-Tolerant Networked Control System) that can tolerate control surface failure and packet delay/loss in an UAV (Unmanned Aerial Vehicle). The proposed method utilizes the benefits of self-diagnosis by smart actuators along with the control allocation technique. A smart actuator is an intelligent actuation system combined with microprocessors to perform self-diagnosis and bi-directional communications. In the event of failure, the smart actuator provides the system supervisor with a set of actuator condition data. The system supervisor then compensate for the effect of faulty actuators by re-allocating redundant control surfaces based on the provided actuator condition data. In addition to the compensation of faulty actuators, the proposed FTNCS also includes an efficient algorithm to deal with network induced delay/packet loss. The proposed algorithm is based on a Lagrange polynomial interpolation method without any mathematical model of the system. Computer simulations with an UAV show that the proposed FTNCS can achieve a fast and accurate tracking performance even in the presence of actuator faults and network induced delays.

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Stochastic analysis and control of real-time systems with random time delays

Cited by 842 publications

References 7 publications

Low‐Latency Wireless Data Transfer for Motion Control

Low‐Latency Wireless Data Transfer for Motion Control

Joint Optimization of Wireless Communication and Networked Control Systems

Fault-Tolerant Control System for Unmanned Aerial Vehicle Using Smart Actuators and Control Allocation

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