Mohammad Reza Davoodi

Simultaneous fault detection and consensus control design for a network of multi-agent systems

The problem of simultaneous fault detection and consensus control (SFDCC) of linear continuous-time multi-agent systems is addressed in this paper. A mixed H ∞ / H - formulation of the SFDCC problem is presented and distributed detection filters are designed using only relative output information among the agents. With our proposed methodology, all agents reach either a state consensus or a model reference consensus while simultaneously collaborate with one another to detect the occurrence of faults in the team. Indeed, each agent not only can detect its own fault but also is capable of detecting its neighbors faults. It is shown that through a decomposition approach the computational complexity of solving the distributed problem is significantly reduced as compared to an optimal centralized solution. The extended linear matrix inequalities (LMIs) are used to reduce the conservativeness of the SFDCC results by introducing additional matrix variables to eliminate the couplings of Lyapunov matrices with the system matrices. It is shown that under a special condition on the network topology the faulty agent can be isolated in the team. Simulation results corresponding to a team of autonomous unmanned underwater vehicles (AUVs) demonstrate and illustrate the effectiveness and capabilities of our proposed design methodology.

Simultaneous fault detection and control design for a network of multi-agent systems

The problem of simultaneous fault detection and control (SFDC) of linear continuous-time multi-agent systems is addressed in this paper. A mixed H∞/H- formulation of the SFDC problem by using distributed detection filters subject to only relative output measurements is presented. Using our proposed methodology, all agents reach a model reference consensus while simultaneously the agents collaborate with one another to detect the occurrence of faults in the team. Indeed, each agent not only can detect its own fault but also is capable of detecting its neighbors faults. It is shown that through a decomposition approach the computational complexity of solving the problem is effectively reduced. The extended linear matrix inequalities (LMIs) is used to reduce the conservativeness of the SFDC results by introducing additional matrix variables to eliminate the couplings of Lyapunov matrices with the system matrices. Simulation results corresponding to a team of unmanned underwater vehicles (UUVs) illustrate the effectiveness and capabilities of the proposed design methodology.

Simultaneous fault detection, isolation and control tracking design using a single observer-based module

In this paper, the problem of simultaneous fault detection, isolation and tracking (SFDIT) design for linear continuous-time systems is considered. An H∞/H- formulation of the SFDIT problem using a dynamic observer is developed. A single module based on a dynamic observer is designed which produces two signals, namely the residual and the control signals. The SFDIT module is designed such that the effects of disturbances and reference inputs on the residual signals are minimized (for accomplishing fault detection) subject to the constraint that the transfer matrix function from the faults to the residuals is equal to a pre-assigned diagonal transfer matrix (for accomplishing fault isolation), while the effects of disturbances, reference inputs and faults on the specified control output are minimized (for accomplishing fault-tolerant control and tracking problems). Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. Simulation results for an autonomous unmanned underwater vehicle (AUV) illustrate the effectiveness of our proposed design methodology.

Nonlinear Suboptimal Tracking Controller Design Using State-Dependent Riccati Equation Technique

In this brief, a new technique for solving a suboptimal tracking problem for a class of nonlinear dynamical systems is presented. Toward this end, an optimal tracking problem using a discounted cost function is defined and a control law with a feedback-feedforward structure is designed. A state-dependent Riccati equation (SDRE) framework is used in order to find the gains of both the feedback and the feedforward parts, simultaneously. Due to the significant properties of the SDRE technique, the proposed method can handle the presence of input saturation and state constraint. It is also shown that the tracking error converges asymptotically to zero under mild conditions on the discount factor of the corresponding cost function and the desired trajectory. Two simulation and experimental case studies are also provided to illustrate and demonstrate the effectiveness of our proposed design methodology.

On design of suboptimal tracking controller for a class of nonlinear systems

In this paper, a new technique for solving the suboptimal tracking problem for a class of nonlinear dynamical systems based on the pseudo linearization is presented. Towards this end, an optimal tracking problem using a discounted cost function is defined and a control law with a feedback feedforward structure is designed. A state-dependent Riccati equation (SDRE) is solved in order to minimize the cost function in a suboptimal way. Due to the significant properties of the SDRE technique, the proposed method can handle the presence of input saturation, state constraint, time delay, and chaotic behavior. Two numerical examples are provided to illustrate the effectiveness and capabilities of the proposed design methodology.

Event-triggered fault detection for discrete-time linear systems

In this paper the problem of event-triggered fault detection filter for discrete-time linear systems is considered and a multi-objective formulation of the problem is presented based on H∞, H- and generalized H2 performance criteria. For each performance index, sufficient conditions are presented based on linear matrix inequalities (LMIs) to design the fault detection observer. In order to reduce the conservativeness of the multi-objective problem, extended LMIs are used to eliminate the couplings of Lyapunov matrices with the system state space matrices. It is shown that through an event-triggered data transmission mechanism, the amount of data that is sent to the fault detection module is decreased dramatically. Simulation results corresponding to a remotely operated underwater vehicle (ROV) demonstrate and illustrate the effectiveness and capabilities of our proposed design methodology.

Integrated fault detection, isolation and control design for continuous-time Markovian jump systems with uncertain transition probabilities

In this paper, the problem of integrated fault detection, isolation and control (IFDIC) design of continuous-time Markovian jump linear systems with uncertain transition probabilities is presented. A single Markovian jump module designated as IFDIC under a mixed H∞/H- framework is considered and designed in order to simultaneously achieve the desired detection, isolation and control objectives. The conventional mixed H∞/H- approach leads to conservative results due to the selection of identical Lyapunov matrices. Consequently, extended linear matrix inequalities (LMIs) methods are used in this work to reduce the conservativeness by introduction of additional matrix variables so that the couplings of the Lyapunov matrices with the system matrices are eliminated. Simulation results for the GE F-404 aircraft engine system illustrate the effectiveness of our proposed design methodologies. Comparisons with relevant work in the literature are also provided to demonstrate the utility of our proposed solutions.

A single dynamic observer-based module for design of simultaneous fault detection, isolation and tracking control scheme

ABSTRACT The problem of simultaneous fault detection, isolation and tracking (SFDIT) control design for linear systems subject to both bounded energy and bounded peak disturbances is considered in this work. A dynamic observer is proposed and implemented by using the H∞/H−/L1 formulation of the SFDIT problem. A single dynamic observer module is designed that generates the residuals as well as the control signals. The objective of the SFDIT module is to ensure that simultaneously the effects of disturbances and control signals on the residual signals are minimised (in order to accomplish the fault detection goal) subject to the constraint that the transfer matrix from the faults to the residuals is equal to a pre-assigned diagonal transfer matrix (in order to accomplish the fault isolation goal), while the effects of disturbances, reference inputs and faults on the specified control outputs are minimised (in order to accomplish the fault-tolerant and tracking control goals). A set of linear matrix inequality (LMI) feasibility conditions are derived to ensure solvability of the problem. In order to illustrate and demonstrate the effectiveness of our proposed design methodology, the developed and proposed schemes are applied to an autonomous unmanned underwater vehicle (AUV).

Event-triggered fault detection for discrete-time linear multi-agent systems

This paper studies the design and development of event-triggered fault detection (FD) filters for discrete-time linear multi-agent systems. For each agent, an FD filter is designed that receives the output measurements from its neighboring agents whenever specific event conditions are satisfied. With our proposed methodology all agents collaborate with one another to detect the occurrence of faults in the team and each agent not only can detect its own fault but also is capable of detecting its neighbors fault. The filter parameters and the event conditions are designed such that a mixed H∞/H- performance index is guaranteed and it is shown that by using an event-triggered technique, the amount of data that is sent by each agent to its neighboring agents is dramatically decreased. Sufficient conditions for the solvability of the problem are obtained in terms of linear matrix inequalities (LMIs) where extended LMI characterizations are used to reduce the conservativeness of the multi-objective H∞/H- problem. Simulation results corresponding to a team of autonomous unmanned underwater vehicles demonstrate and illustrate the effectiveness and capabilities of the proposed methodology.

Event-Triggered Suboptimal Tracking Controller Design for a Class of Nonlinear Discrete-Time Systems

In this paper, using the state-dependent Riccati equation approach, an event-triggered technique is proposed to solve the tracking problem for a broad class of nonlinear discrete-time networked control systems. It is shown that the proposed tracking controller leads to an asymptotically stable system, while the information exchange between the controller and the actuator can be directly affected with predictable results by changing a parameter of the controller called the triggering factor. The proposed method is experimentally validated on a laboratory three-tank system. The obtained results demonstrate the effectiveness of the proposed event-triggered technique for solving the tracking problem of a nonlinear system in a networked control framework.