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This necessitates extensive simulation of controllers to ensure stability and performance.
In this paper, a methodology for the synthesis of repetitive controllers to ensure periodic reference tracking and harmonic disturbance rejection is cast in a robust control framework.
In this paper we develop a concrete procedure for designing feedback controllers to ensure that the resultant dynamics of turbulence will preserve certain prescribed physical constraints.
Secondly, we design linear state feedback controllers and adaptive controllers to ensure the stabilization of the discontinuous neural networks with a generalized H∞ disturbance attenuation level ρ.
Traffic engineers and technicians are faced with the challenge of testing traffic controllers to ensure that they comply with different software and hardware requirements prior to deployment.
Simple examples are shown to illustrate the type of sensing and observation required by the controllers to ensure pre-defined performance.
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Thus some level of intelligence must be embedded into each agent's controller to ensure higher degree of system dependability.
The second algorithm is a quasi-continuous high-order sliding mode controller to ensure the speed tracking.
Nonlinear characteristics of wind turbine structure and generator operational behavior demand for high-quality optimal controller to ensure both stability and safe performance (Aghdam and Allahbakhsh 2014).
Thereafter, taking benefit of the asymptotic behavior of an adaptive observer, we synthesize a backstepping controller to ensure the output tracking of a nominal reference trajectory.
Taking advantage of the plant knowledge, we design a course angle controller to ensure closed-loop stability.
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