Formalism Of Hybrid Automata Research Articles

Intelligent control of an UAV with a cable-suspended load using a neural network estimator

Unmanned aerial vehicles (UAVs) have been proved very useful in civil and military sectors: defense, security, shipping, construction, agriculture, entertainment, etc. Some of these applications, especially those related to transport and logistic operations, require the use of suspended loads that may make the vehicle unstable. In order to deal with this non-linear complex system with a changing mass, further research on modelling and control must be developed. In this work, a new intelligent control strategy is proposed and applied to a quadrotor with a cable-suspended load. The UAV carrying a suspended load has two different dynamic behaviors, depending on the state of the cable. Thus, we proposed to model the complete system using the hybrid automata formalism. Using this novel UAV model approach, a hybrid control is designed based on feedback linearization controllers combined with an artificial neural network, which acts as an online estimator of the unknown mass. The suspended load is dealt with as an external disturbance. Simulation results show how the on-line learning control scheme increases the robustness of the control and it is able to stabilize the quadrotor without any information about neither the position of the load nor the tension of the cable. Additionally, the computational complexity of the proposal is studied to show the feasibility of the implementation of this intelligent control strategy on real hardware.

Switched learning adaptive neuro-control strategy

The generalized learning algorithm can be efficiently used as control strategy, but it has some drawbacks such as: sensitivity to the training dataset, poor robustness against changes in the system, difficulty to generate the control signals without destabilising the plant, tuning of the controller, etc. To overcome some of these issues, in this work a new switched neural adaptive control strategy is proposed. It is based on the combination of an adaptive artificial neural network, a PID regulator, an estimated inverse model of the plant and two switches to route the signals properly in the control scheme. The technique is described using the hybrid automata formalism. In order to test the validity of this proposal, it is applied to the control of a quadrotor unmanned aerial vehicle (UAV), subjected to changes in its mass and wind disturbances. Simulation results show how the on-line learning increases the robustness of the controller, reducing the effects of the mass change and of the wind on the UAV stabilization, thus improving the UAV trajectory tracking.

Simulation and evaluation of conflict interactions in information systems

The work describes the scenario of conflict interactions in information system and intruder security using the formalism of hybrid automata. Analysis of probability of winning on both sides in the conflict. The possibility of abstraction from a concrete kind of density distributions for the time the parties to the conflict in their possible States. Based on the destructive effects of information distribution models in information system shows the mutual influence of the spread of the destructive processes information on process state changes subjects information system. With this approach, based on a view of information system in the form of a two-dimensional cellular automaton. The results of experimental research of confirming the theoretical conclusions.

Hybrid Systems Control Based on Smart Space Technology

The paper presents an approach to hybrid systems control based on smart space technology. The approach proposed bears two primary distinctive features: first, hybrid system control is decentralized and various control functions are implemented in separate services, communicating via ontology-based smart space; second, the services are represented by a hybrid automata formalism allowing to employ a model-driven development for hybrid control systems. The approach is illustrated by practical communication scenario of several physical devices in the context of smart home environment.

Uncertainty of asymptotic dynamics in bioresource management simulation

Specific features of simulating a system that experiences structural changes in the course of its development are studied by the example of a controlled biological population. The problem of whether nonattracting chaotic sets can arise in dynamic systems with more than one attractor is considered in this context. The formalism of hybrid automata as applied to simulation problems of biological processes is described. Specific features of the phase portrait of the developed dynamic model are characterized by locally disconnected boundaries of basins of attraction of two attractors. The conclusion on limited predictability of the dynamics of some controlled natural systems is made, which is a consequence of uncertainty with respect to the motion of the system towards one of possible stable states.

A Hybrid Automaton Model of the Cement Mill Control

Cement milling circuits are controlled by linear quadratic strategies with the purpose of retaining the circuit stability. Generally, the controlled variables of milling circuits present discontinuities over the range of values they take during the plant operation. The design of linear quadratic control algorithms is based on linear approximations of the nonlinear differential equations that hold over the continuous time ranges of the controlled variables. These approximations make the practical implementation of these algorithms less effective than expected and for this reason there is the need to verify the range of the variable values over which the algorithms can retain the circuit stability before commissioning them. In this paper, an alternative model to that of the nonlinear differential equations is developed for the verification of the milling circuit stability. The model is based on the rectangular hybrid automata formalism. This formalism provides a more systematic and formal way of modeling the plant operation over different ranges of variables presenting discontinuities and does not require to develop informal textual description of the conditions under which different sets of differential equations model the plant operation within the different continuous ranges of the variables. In order to use this model for verifying the circuit stability, the requirements for the circuit stability are expressed in the form of a logical proposition of the ranges of the values within which certain variables of the cement milling circuit must remain. The circuit stability is verified by finding whether the states that are defined by the logical proposition are included in the state space of the automaton. There are, however, cases in which existing algorithms that search into the state space either do not terminate or take very long times in identifying the existence or not of the desired state. After the elapse of a significant portion of time the analyst does not know whether this long time is due to algorithm termination problem or to the very large number of remaining computations. In this paper, a new algorithm was developed which does not search into the state space of the automaton as most of the other algorithms do, but computes the number of automaton iterations required for reaching a state. If this is a finite number one can conclude that the desired state is reachable. This algorithm was used in verifying the circuit stability.