scholarly journals Formal Approach to Control Design of Complex and Dynamical Systems

2017 ◽  
Vol 108 ◽  
pp. 2512-2516
Author(s):  
Hela Kadri ◽  
Samir Ben Ahmed ◽  
Simon Collart-Dutilleul
Keyword(s):  
Dynamical Systems ◽  
Control Design ◽  
Formal Approach

A New Approach to the Control Design of Fuzzy Dynamical Systems

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Ye-Hwa Chen
Keyword(s):  
Dynamical Systems ◽  
Optimization Problem ◽  
Closed Form Solution ◽  
Control Design ◽  
Form Solution ◽  
Bottom Line ◽  
New Approach ◽  
Fuzzy Dynamical System ◽  
The Cost ◽  
Fuzzy Dynamical Systems

A new approach to the control design for fuzzy dynamical systems is proposed. For a fuzzy dynamical system, the uncertainty lies within a fuzzy set. The desirable system performance is twofold: one deterministic and one fuzzy. While the deterministic performance assures the bottom line, the fuzzy performance enhances the cost consideration. Under this setting, a class of robust controls is proposed. The control is deterministic and is not if-then rules-based. An optimal design problem associated with the control is then formulated as a constrained optimization problem. We show that the problem can be solved and the solution exists and is unique. The closed-form solution and cost are explicitly shown. The resulting control is able to guarantee the prescribed deterministic performance and minimize the average fuzzy performance.

Control of Multichaotic Systems Using the Extended OGY Method

2015 ◽  
Vol 25 (08) ◽  
pp. 1550096 ◽  
Author(s):  
Ensieh Nobakhti ◽  
Ali Khaki-Sedigh ◽  
Nastaran Vasegh
Keyword(s):  
Dynamical Systems ◽  
Decentralized Control ◽  
Chaotic Maps ◽  
Control Design ◽  
Complex Dynamical Systems ◽  
Design Scheme ◽  
Simulation Results ◽  
The Individual ◽  
Systems Simulation

This paper considers the problem of controlling coupled chaotic maps. Coupled chaotic maps or multichaotic subsystems are complex dynamical systems that consist of several chaotic sub-systems with interactions. The OGY methodology is extended to deal with the control of such systems. It is shown that the decentralized control design scheme in which the individual controllers share no information is not generally able to control multichaotic systems. Simulation results are used to support the main conclusions of the paper.

Coordination Control for Multiagent Interconnected Systems

2011 ◽  
Author(s):  
Wassim M. Haddad ◽  
Sergey G. Nersesov
Keyword(s):  
Dynamical Systems ◽  
Lyapunov Functions ◽  
Nonlinear Dynamical Systems ◽  
Control Design ◽  
Interconnected Systems ◽  
Time Varying ◽  
Design Framework ◽  
Coordination Control ◽  
Nonlinear Dynamical ◽  
Stabilizing Controllers

This chapter describes a stability and control design framework for time-varying and time-invariant sets of nonlinear dynamical systems. The framework is applied to the problem of coordination control for multiagent interconnected systems predicated on vector Lyapunov functions. In multiagent systems, several Lyapunov functions arise naturally where each agent can be associated with a generalized energy function corresponding to a component of a vector Lyapunov function. The chapter characterizes a moving formation of vehicles as a time-varying set in the state space to develop a distributed control design framework for multivehicle coordinated motion control by designing stabilizing controllers for time-varying sets of nonlinear dynamical systems. The proposed cooperative control algorithms are shown to globally exponentially stabilize both moving and static formations.

Model Predictive Control Design for Dynamical Systems Learned by Echo State Networks

2019 ◽  
Vol 3 (4) ◽  
pp. 1044-1049 ◽  
Author(s):  
Luca Bugliari Armenio ◽  
Enrico Terzi ◽  
Marcello Farina ◽  
Riccardo Scattolini
Keyword(s):  
Dynamical Systems ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Control Design ◽  
Echo State Networks
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