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The problem of the multi-objective controller synthesis is to construct a controller that stabilizes the closed loop system and, simultaneously, achieves all the prescribed specifications.
In this paper, proposed method afford to construct a controller in a recursive way and it enforces incremental exponential stability of an underwater vehicle and not just global asymptotic stability.
Using the solution of proposed modified algebraic Riccati equation, we can construct a controller which depends on the maximum value of the time derivative of time-varying delay and guarantees a prescribed H∞ norm bound of the closed-loop transfer matrix from the disturbance to the controlled output.
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Contrary to the conventional control approaches these focus on constructing a controller by using the model of the rate-based system.
Compared with existing approaches in the literature, the new design approach constructs a controller with simpler forms and less restrictions.
The proposed approach in this paper provides a recursive way of constructing a controller and it enforce incremental input to state stability of a vehicle and not just global asymptotic stability.
Therefore, this work constructed a controller with artificial intelligence technology by first using an artificial neural network as the predictor and then using the traveling particle swarm optimizer that is ideal for continuous optimization problems as the algorithm for optimization.
Therefore, it is important to present a novel control scheme to construct a robust controller with good closed-loop capability.
If these necessary conditions are complemented by suitable coupling constraints, they allow to construct a desired controller that stabilizes the closed-loop system with Δc = Δ.
Second, construct a linear controller for the cart subsystem and steer the position and velocity of the cart to the origin.
There are several advantages in this method for synchronizing chaotic systems: (a) it presents a systematic procedure for construct a proper controller in chaos synchronization; (b) it can be applied to a variety of chaotic systems with lower triangular structure.
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