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JournalISSN: 2330-7706

Journal of Control and Decision 

Taylor & Francis
About: Journal of Control and Decision is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Computer science & Control theory (sociology). It has an ISSN identifier of 2330-7706. Over the lifetime, 309 publications have been published receiving 2351 citations. The journal is also known as: JCD.

Papers published on a yearly basis

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Journal ArticleDOI
TL;DR: In this paper, a modular rewriting system for translating optimization problems written in a domain-specific language (DSL) to forms compatible with low-level solver interfaces is described.
Abstract: We describe a modular rewriting system for translating optimization problems written in a domain-specific language (DSL) to forms compatible with low-level solver interfaces. Translation is facilit...

358 citations

Journal ArticleDOI
TL;DR: This work describes how event-driven, rather than synchronous, communication can guarantee convergence in cooperative distributed optimization while provably maintaining optimality in distributed systems.
Abstract: The event-driven paradigm offers an alternative to the time-driven paradigm for modelling, sampling, estimation, control and optimization. This has come about largely as a consequence of systems being increasingly networked, wireless and consisting of distributed communicating components. The key idea is that control actions need not be dictated by time steps taken by a “clock”; rather, an action should be triggered by an “event” which may be a well-defined condition on the system state, including the possibility of a simple time step, or a random state transition. We provide an overview of recent developments in event-driven approaches and focus on two areas to illustrate their value. First, in distributed systems, we describe how event-driven, rather than synchronous, communication can guarantee convergence in cooperative distributed optimization while provably maintaining optimality. Second, in hybrid systems where events naturally decompose state trajectories into different discrete states (modes), we...

84 citations

Journal ArticleDOI
Gang Tao1
TL;DR: In this paper, the authors present a tutorial on direct adaptive failure compensation-based solutions for different types of control systems: state tracking using state feedback, output tracking using either state feedback or output feedback, for linear, parametric, and actuation uncertainties.
Abstract: A resilient control system is expected to have the capacity to restore the desired system stability and tracking performance in the presence of uncertain system faults such as actuator failures. While redundant actuators are used for actuator failure accommodation, uncertain actuator failures, whose failure time, pattern, and values may be unknown, can bring new challenges to feedback control design as such uncertain failures can introduce large structural, parametric, and actuation uncertainties. Two technical issues are associated with using redundant actuators: how redundant actuators should be coordinated for effective failure compensation control, and how a feedback control law should be adaptively designed to compensate uncertain actuator failures. In this paper, we present a tutorial on direct adaptive failure compensation-based solutions to these issues for different types of control systems: state tracking using state feedback, output tracking using state feedback or output feedback, for linear, ...

75 citations

Journal ArticleDOI
TL;DR: In this article, the authors explored the relationship between dual decomposition and the consensus-based method for distributed optimisation by examining the similarities between the two approaches and their relationship to gradient-based constrained optimisation.
Abstract: In this paper, we explore the relationship between dual decomposition and the consensus-based method for distributed optimisation. The relationship is developed by examining the similarities between the two approaches and their relationship to gradient-based constrained optimisation. By formulating each algorithm in continuous-time, it is seen that both approaches use a gradient method for optimisation with one using a proportional control term and the other using an integral control term to drive the system to the constraint set. Therefore, a significant contribution of this paper is to combine these methods to develop a continuous-time proportional-integral distributed optimisation method. Furthermore, we establish convergence using Lyapunov stability techniques and utilising properties from the network structure of the multi-agent system.

70 citations

Journal ArticleDOI
TL;DR: In this article, a fault-tolerant control (FTC) approach is proposed to simultaneously compensate for actuator faults, model mismatch and parameter variations in aircraft systems, which successfully combines the properties of active and passive FTCs to accommodate faults while retaining acceptable system performance.
Abstract: Effectiveness in flight control is achieved by maintaining specified performance despite the presence of faults and reliability implies taking the necessary measures to correct the fault before it leads to substantial performance deterioration and instability. In order to achieve both effectiveness and reliability, in this paper, we propose a fault-tolerant control (FTC) approach that is able to simultaneously compensate for actuator faults, model mismatch and parameter variations in aircraft systems. The proposed control design successfully combines the properties of active and passive FTCs to accommodate faults while retaining acceptable system performance. A passive baseline controller is designed using sliding mode theory and an active controller is designed using a model reference adaptive approach. The proposed control paradigm retains system performance under fault free conditions and triggers corrective measures only when necessary, hence ensuring flight effectiveness and enhancing system’s reliab...

58 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202336
202290
202150
202039
201925
201819