S.M. Azizi

Cooperative actuator fault accommodation in formation flight of unmanned vehicles using relative measurements

In this article, the cooperative fault accommodation in formation flight of unmanned vehicles is investigated through a hierarchical framework. Three levels are envisaged, namely a low-level fault recovery (LLFR), a formation-level fault recovery (FLFR) and a high-level (HL). In the LLFR module, a recovery controller is designed by using an estimate of the actuator fault. A performance monitoring module is introduced at the HL hierarchy to identify a partially low-level (LL) recovered vehicle due to inaccuracy in the fault estimate which results in violating the error specification of the formation mission. The HL supervisor then activates the FLFR module to compensate for the performance degradations of the partially LL recovered vehicle at the expense of the other healthy vehicles. Both centralised and decentralised control approaches are developed for our proposed cooperative fault recovery technique. A robust H ∞ controller is designed in which the parameters of the controller are adjusted to accommodate for the partially LL-recovered vehicle by enforcing that the other healthy vehicles allocate more control effort to compensate for the performance degradations of the faulty vehicle. Numerical simulations for a formation flight of five satellites are provided in the deep space, which do indeed confirm the validity and effectiveness of our proposed analytical work.

A Hierarchical Architecture for Cooperative Actuator Fault Estimation and Accommodation of Formation Flying Satellites in Deep Space

A new cooperative fault accommodation algorithm based on a multi-level hierarchical architecture is proposed for satellite formation flying missions. This framework introduces a high-level (HL) supervisor and two recovery modules, namely a low-level fault recovery (LLFR) module and a formation-level fault recovery (FLFR) module. At the LLFR module, a new hybrid and switching framework is proposed for cooperative actuator fault estimation of formation flying satellites in deep space. The formation states are distributed among local detection and estimation filters. Each system mode represents a certain cooperative estimation scheme and communication topology among local estimation filters. The mode transitions represent the reconfiguration of the estimation schemes, where the transitions are governed by information that is provided by the detection filters. It is shown that our proposed hybrid and switching framework confines the effects of unmodeled dynamics, disturbances, and uncertainties to local parameter estimators, thereby preventing the propagation of inaccurate information to other estimation filters. Moreover, at the LLFR module a conventional recovery controller is implemented by using estimates of the fault severities. Due to an imprecise fault estimate and an ineffective recovery controller, the HL supervisor detects violation of the mission error specifications. The FLFR module is then activated to compensate for the performance degradations of the faulty satellite by requiring that the healthy satellites allocate additional resources to remedy the problem. Consequently, fault is cooperatively recovered by our proposed architecture, and the formation flying mission specifications are satisfied. Simulation results confirm the validity and effectiveness of our developed and proposed analytical work.

A distributed Kalman filter for actuator fault estimation of deep space formation flying satellites

In this paper, a new distributed Kalman filter scheme is proposed to estimate actuator faults for deep space formation flying satellites. The method can also be applied to large-scale systems such as sensor networks and power systems. For a hierarchical large-scale system, the overlapping block-diagonal state space (OBDSS) representation of the system is transformed into our proposed constrained-state block-diagonal state space (CSBDSS) model. The proposed model becomes purely diagonal which simplifies and allows the distributed implementation of the Kalman filters. The constrained-state condition needs to be satisfied at each Kalman filtering iteration which is shown to be equivalent to solving local constrained optimization cost functions. Simulation results presented confirm the effectiveness of our proposed analytical work.

A sub-optimal distributed Kalman filter with fusion feedback for acyclic systems

In this paper, a new distributed Kalman filter is proposed for state estimation of systems with acyclic digraph, namely acyclic systems. This method can be applied to a number of large-scale systems including sensor networks and formation flying missions. An acyclic system can be represented by an overlapping block-diagonal state space (OBDSS) model, which requires an extensive communication overhead for implementing a centralized Kalman filter scheme. The OBDSS model is transformed into our proposed constrained-state block-diagonal state space (CSBDSS) model, which is purely diagonal and simplifies the implementation of a distributed Kalman filter scheme. Corresponding to each Kalman filter iteration a specific constrained-state condition needs to be satisfied that is embedded with a fusion feedback. Simulation results confirm the effectiveness of our proposed analytical work.

Cooperative actuator fault accommodation of formation flying vehicles with absolute measurements

In this paper, a new cooperative fault accommodation algorithm is proposed for multiple-vehicle formation flying missions embedded with absolute measurements. This framework provides two recovery modules, namely a low-level fault recovery (LLFR) module and a formation-level fault recovery (FLFR) module. The framework also includes a high-level (HL) supervisor. In the LLFR module, a conventional recovery controller (RC) based on a given fault severity estimate is employed. In case that the LLFR controller cannot fully recover the faulty vehicle due to an imprecise fault estimate, the error bounds imposed by the mission specifications can be violated and the supervisor identifies this violation and activates the FLFR module. This module is responsible for reconfiguring the weighted absolute measurement formation (WAMF) digraph, applying a robust controller, and imposing constraints on the desired input vectors of the partially LL-recovered vehicle and its neighbor vehicles. Consequently, the formation mission specifications can still be guaranteed so that the fault is cooperatively recovered by our proposed scheme. Simulation results for a satellite formation in planetary orbital environment (POE) confirm the validity and effectiveness of our analytical work.

A decentralized cooperative actuator fault accommodation of formation flying satellites in deep space

In this paper, a new fault accommodation framework that is based on a decentralized cooperative scheme is proposed for formation flying satellites. A low-level fault recovery (LLFR) module uses conventional estimation techniques to determine the severity of a fault. It then activates a recovery controller (RC) to accomplish the design specifications. Due to existence of a biased estimate of the fault, a high-level (HL) supervisor will detect any possible violations of the performance specifications, and consecutively activates the formation-level fault recovery (FLFR) module. This module compensates for performance degradations of the faulty satellite by requiring that the healthy satellites do allocate additional resources. Consequently, our proposed cooperative architecture recovers the fault while the decentralized control requirements and the error performance specifications are satisfied. Simulation results presented confirm the effectiveness of our proposed analytical work.

Cooperative fault accommodation in formation flying satellites

In this paper a new fault accommodation algorithm based on a two-level architecture is proposed for satellite formation missions. In this two-level framework, the notion of formation-level fault recovery (FLFR) is proposed, and the task of performance monitoring (PM) is defined in the high level (HL). By using the information provided by the PM module, the FLFR is capable of accommodating the ldquounhealthy satelliterdquo that is partially recovered (due to the inexact and inaccurate estimation of the fault by the fault diagnosis and identification (FDI) modules) in the low-level fault recovery (LLFR), but is detected and labeled as ldquounhealthyrdquo by the PM module. Consequently, fault is cooperatively recovered by our proposed architecture, and the specifications of formation mission are satisfied. Simulation results confirm the validity and effectiveness of our proposed algorithm.

A distributed and cooperative supervisory estimation of multi-agent systems - Part I: Framework

In this work, we propose a framework for supervisory cooperative estimation of multi-agent linear time-invariant (LTI) systems. We introduce a group of sub-observers, each estimating certain states that are conditioned on given input, output, and state information. The cooperation among the sub-observers is supervised by a discrete-event system (DES) supervisor. The supervisor makes decisions on selecting and configuring a set of sub-observers to successfully estimate all states of the system. Moreover, when certain anomalies are present, the supervisor reconfigures the set of selected sub-observers so that the impact of anomalies on the estimation performance is minimized. This framework is applicable to any multi-agent system including large-scale industrial processes. In this paper (Part I), our proposed framework for supervisory estimation is developed based on the notion of sub-observers and DES supervisory control. In the companion paper (Part II), a DES-based combinatorial optimization method for selection of an optimal set of sub-observers is presented, the feasibility of the overall integrated sub-observers is validated, and the application of our proposed method in a practical industrial process is demonstrated through numerical simulations.

Optimal distributed and cooperative supervisory estimation of multi-agent systems subject to unreliable information

In this work, a novel framework for optimal cooperative supervisory estimation of multi-agent linear time-invariant (LTI) systems is proposed which is applicable to a large class of multi-agent systems. This framework was recently developed by the authors based on the notion of sub-observers and a discrete-event system (DES) supervisory control. Each sub-observer estimates certain states that are conditioned on given inputs, outputs, and states information. Moreover, the cooperation among the sub-observers is managed by a DES supervisor. In this work, our proposed supervisory estimation framework is extended to the combinatorial optimization domain. When certain anomalies (faults) are present in the system, or the sensors and sub-observers become unreliable, the proposed optimal DES supervisor makes decisions regarding the selection and reconfiguration of sets of sub-observers to estimate all the system states, while simultaneously a performance index that incorporates the communication cost, computation cost, and reconfiguration cost, and the number of invalid state estimates is minimized. The application of our proposed methodology in a practical industrial process is demonstrated through numerical simulations.

A distributed and cooperative supervisory estimation of multi-agent systems - Part II: Verification and case study

A framework for supervisory cooperative estimation in multi-agent linear time-invariant (LTI) systems is presented in the companion work (Part I). We introduced a set of sub-observers such that each estimates some states with a given set of input, output, and state information. A discerete-event system (DES) supervisory control framework is used for cooperation among the sub-observers. The supervisor selects a set of sub-observers to successfully estimate all states of the multi-agent system. In addition, in presence of a fault in the system, the supervisor reconfigures the set of selected sub-observers to minimize the fault impact on the estimation performance. Our general framework can be applied to any multi-agent system including industrial processes. In the companion paper (Part I), our proposed framework for the supervisory estimation is developed based on the notion of subobservers and DES supervisory control. In this paper (Part II), a DES-based combinatorial optimization method for selection of an optimal set of sub-observers is presented, the feasibility of the overall integrated sub-observers is validated, and the application of our proposed method in a practical industrial process is demonstrated through numerical simulations.