15,466 research outputs found
Supervisory Control Problems of Hierarchical Finite State Machines
International audienceThe situation under consideration is that of a given Discrete Event System (DES), whose behavior has to be modified by means of a feedback control (named Supervisor) in order to achieve a given set of requirements that the initial DES did not satisfy. To do so, the DES is modeled as a Hierarchical Finite State Machine (HFSM). Further, instead of translating the HFSM to ordinary state machines and using classical synthesis tools on the resulting FSM, we here present algorithms that solve the Supervisory Control Problem (for a particular case of forbidden state avoidance problem) as well as the Optimal Control Problem without expanding the HFS
Decentralized Hybrid Formation Control of Unmanned Aerial Vehicles
This paper presents a decentralized hybrid supervisory control approach for a
team of unmanned helicopters that are involved in a leader-follower formation
mission. Using a polar partitioning technique, the motion dynamics of the
follower helicopters are abstracted to finite state machines. Then, a discrete
supervisor is designed in a modular way for different components of the
formation mission including reaching the formation, keeping the formation, and
collision avoidance. Furthermore, a formal technique is developed to design the
local supervisors decentralizedly, so that the team of helicopters as whole,
can cooperatively accomplish a collision-free formation task
Supervisory Control of Asynchronous and Hierarchical Finite State Machines
International audienceIn this paper, modular supervisory control of a class of Discrete Event Systems is investigated. Discrete event systems are modeled by a Hierarchical Finite State Machine. The basic problem of interest is to solve the State Avoidance Control Problem. We provide algorithms that, based on a particular decomposition of the set of forbidden configurations, locally solve the control problem (i.e. on each component without computing the whole system) and produce a global supervisor ensuring the desired property. This kind of objectives may be useful to perform dynamic interactions between different parts of a syste
Real-time plasma state monitoring and supervisory control on TCV
In ITER and DEMO, various control objectives related to plasma control must be simultaneously achieved by the plasma control system (PCS), in both normal operation as well as off-normal conditions. The PCS must act on off-normal events and deviations from the target scenario, since certain sequences (chains) of events can precede disruptions. It is important that these decisions are made while maintaining a coherent prioritization between the real-time control tasks to ensure high-performance operation. In this paper, a generic architecture for task-based integrated plasma control is proposed. The architecture is characterized by the separation of state estimation, event detection, decisions and task execution among different algorithms, with standardized signal interfaces. Central to the architecture are a plasma state monitor and supervisory controller. In the plasma state monitor, discrete events in the continuous-valued plasma state are modeled using finite state machines. This provides a high-level representation of the plasma state. The supervisory controller coordinates the execution of multiple plasma control tasks by assigning task priorities, based on the finite states of the plasma and the pulse schedule. These algorithms were implemented on the TCV digital control system and integrated with actuator resource management and existing state estimation algorithms and controllers. The plasma state monitor on TCV can track a multitude of plasma events, related to plasma current, rotating and locked neoclassical tearing modes, and position displacements. In TCV experiments on simultaneous control of plasma pressure, safety factor profile and NTMs using electron cyclotron heating (ECH) and current drive (ECCD), the supervisory controller assigns priorities to the relevant control tasks. The tasks are then executed by feedback controllers and actuator allocation management. This work forms a significant step forward in the ongoing integration of control capabilities in experiments on TCV, in support of tokamak reactor operation
Real-time plasma state monitoring and supervisory control on TCV
In ITER and DEMO, various control objectives related to plasma control must be
simultaneously achieved by the plasma control system (PCS), in both normal operation as
well as off-normal conditions. The PCS must act on off-normal events and deviations from
the target scenario, since certain sequences (chains) of events can precede disruptions. It is
important that these decisions are made while maintaining a coherent prioritization between
the real-time control tasks to ensure high-performance operation.
In this paper, a generic architecture for task-based integrated plasma control is proposed.
The architecture is characterized by the separation of state estimation, event detection,
decisions and task execution among different algorithms, with standardized signal interfaces.
Central to the architecture are a plasma state monitor and supervisory controller. In the plasma
state monitor, discrete events in the continuous-valued plasma state are modeled using finite
state machines. This provides a high-level representation of the plasma state. The supervisory
controller coordinates the execution of multiple plasma control tasks by assigning task
priorities, based on the finite states of the plasma and the pulse schedule.
These algorithms were implemented on the TCV digital control system and integrated
with actuator resource management and existing state estimation algorithms and controllers.
The plasma state monitor on TCV can track a multitude of plasma events, related to plasma
current, rotating and locked neoclassical tearing modes, and position displacements.
In TCV experiments on simultaneous control of plasma pressure, safety factor profile and
NTMs using electron cyclotron heating (ECH) and current drive (ECCD), the supervisory
controller assigns priorities to the relevant control tasks. The tasks are then executed by
feedback controllers and actuator allocation management. This work forms a significant step
forward in the ongoing integration of control capabilities in experiments on TCV, in support of
tokamak reactor operation.EURATOM 633053Netherlands Organization for Scientific Research 680.47.43
Real-time plasma state monitoring and supervisory control on TCV
In ITER and DEMO, various control objectives related to plasma control must be simultaneously achieved by the plasma control system (PCS), in both normal operation as well as off-normal conditions. The PCS must act on off-normal events and deviations from the target scenario, since certain sequences (chains) of events can precede disruptions. It is important that these decisions are made while maintaining a coherent prioritization between the real-time control tasks to ensure high-performance operation. In this paper, a generic architecture for task-based integrated plasma control is proposed. The architecture is characterized by the separation of state estimation, event detection, decisions and task execution among different algorithms, with standardized signal interfaces. Central to the architecture are a plasma state monitor and supervisory controller. In the plasma state monitor, discrete events in the continuous-valued plasma state arc modeled using finite state machines. This provides a high-level representation of the plasma state. The supervisory controller coordinates the execution of multiple plasma control tasks by assigning task priorities, based on the finite states of the plasma and the pulse schedule. These algorithms were implemented on the TCV digital control system and integrated with actuator resource management and existing state estimation algorithms and controllers. The plasma state monitor on TCV can track a multitude of plasma events, related to plasma current, rotating and locked neoclassical tearing modes, and position displacements. In TCV experiments on simultaneous control of plasma pressure, safety factor profile and NTMs using electron cyclotron heating (ECI I) and current drive (ECCD), the supervisory controller assigns priorities to the relevant control tasks. The tasks are then executed by feedback controllers and actuator allocation management. This work forms a significant step forward in the ongoing integration of control capabilities in experiments on TCV, in support of tokamak reactor operation.Peer reviewe
Variable abstraction and approximations in supervisory control synthesis
This paper proposes a method to simplify Extended Finite-state Automata (EFA) in such a way the least restrictive controllable supervisor is preserved. The method is based on variable abstraction, which involves the identification and removal of irrelevant variables from a model. Variable abstraction preserves controllability, and the paper shows how approximations can be used to ascertain least restrictiveness of the synthesis result. The approach has the modelling benefits of Extended Finite-state Automata, leads to optimal control solutions, and reduces the synthesis cost. An example of a manufacturing system illustrates the contributions
- …