Application of Multi-agent Optimization Methods Based on the Use of Linear Regulators and Interpolation Search for a Single Class of Optimal Deterministic Control Systems

2021 ◽  
pp. 217-244
Author(s):  
Andrei V. Panteleev ◽  
Maria Magdalina S. Karane
Keyword(s):  
Control Systems ◽  
Optimization Methods ◽  
Single Class ◽  
Interpolation Search ◽  
Multi Agent ◽  
Deterministic Control ◽  
Linear Regulators

scholarly journals Drone Swarms as Networked Control Systems by Integration of Networking and Computing

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2642
Author(s):  
Godwin Asaamoning ◽  
Paulo Mendes ◽  
Denis Rosário ◽  
Eduardo Cerqueira
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Cooperative Behavior ◽  
Networked Control ◽  
Multi Agent Systems ◽  
Wireless Communication Network ◽  
Self Organized ◽  
Design Choice ◽  
Multi Agent ◽  
Computational Systems

The study of multi-agent systems such as drone swarms has been intensified due to their cooperative behavior. Nonetheless, automating the control of a swarm is challenging as each drone operates under fluctuating wireless, networking and environment constraints. To tackle these challenges, we consider drone swarms as Networked Control Systems (NCS), where the control of the overall system is done enclosed within a wireless communication network. This is based on a tight interconnection between the networking and computational systems, aiming to efficiently support the basic control functionality, namely data collection and exchanging, decision-making, and the distribution of actuation commands. Based on a literature analysis, we do not find revision papers about design of drone swarms as NCS. In this review, we introduce an overview of how to develop self-organized drone swarms as NCS via the integration of a networking system and a computational system. In this sense, we describe the properties of the proposed components of a drone swarm as an NCS in terms of networking and computational systems. We also analyze their integration to increase the performance of a drone swarm. Finally, we identify a potential design choice, and a set of open research challenges for the integration of network and computing in a drone swarm as an NCS.

scholarly journals Approximate Controllability of Sobolev Type Nonlocal Fractional Stochastic Dynamic Systems in Hilbert Spaces

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Mourad Kerboua ◽  
Amar Debbouche ◽  
Dumitru Baleanu
Keyword(s):  
Control Systems ◽  
Hilbert Spaces ◽  
Dynamic Systems ◽  
Approximate Controllability ◽  
Dynamic Control ◽  
Sufficient Conditions ◽  
Sobolev Type ◽  
Stochastic Dynamic ◽  
Deterministic Control ◽  
Stochastic Dynamic Systems

We study a class of fractional stochastic dynamic control systems of Sobolev type in Hilbert spaces. We use fixed point technique, fractional calculus, stochastic analysis, and methods adopted directly from deterministic control problems for the main results. A new set of sufficient conditions for approximate controllability is formulated and proved. An example is also given to provide the obtained theory.

Reconfigurable Embedded Control Systems

2011 ◽  
pp. 235-273
Author(s):  
Mohamed Khalgui ◽  
Olfa Mosbahi
Keyword(s):  
Control Systems ◽  
Research Work ◽  
User Requirements ◽  
Multi Agent Systems ◽  
Embedded Control ◽  
Embedded Control Systems ◽  
Temporal Properties ◽  
Logic Computation ◽  
Multi Agent ◽  
Hardware Faults

The chapter deals with distributed multi-agent reconfigurable embedded control systems following the component-based International Industrial Standard IEC61499 in which a Function Block (abbreviated by FB) is an event-triggered software component owning data and a control application is a distributed network of Function Blocks that have classically to satisfy functional and to meet temporal properties described in user requirements. The authors define a new reconfiguration semantic where a crucial criterion to consider is the automatic improvement of the system’s performance at run-time, in addition to its protection when hardware faults occur. To handle all possible cases in industry, the authors classify thereafter the reconfiguration scenarios into three forms before the authors define an architecture of reconfigurable multi-agent systems where a Reconfiguration Agent is affected to each device of the execution environment to apply local reconfigurations, and a Coordination Agent is proposed for any coordination between devices in order to guarantee safe and adequate distributed reconfigurations. A Communication Protocol is proposed in our research work to handle coordinations between agents by using well-defined Coordination Matrices. The authors specify both the reconfiguration agents to be modelled by nested state machines, and the Coordination Agent according to the formalism Net Condition/Event Systems (Abbreviated by NCES) which is an extension of Petri nets. To verify the whole architecture, the author check by applying the model checker SESA in each device functional and temporal properties described in the temporal logic “Computation Tree Logic”, but the authors have also to check any coordination between devices by verifying that whenever a reconfiguration is applied in a device, the Coordination Agent and other concerned devices should react as described in user requirements. The chapter’s contributions are applied to two Benchmark Production Systems available in our research laboratory.

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