An Optimal Robust Tuning Method for First Order plus Dead Time Systems with Parameter Uncertainty

Robust Tuning of Dynamic Matrix Controllers for First Order plus Dead Time Models

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Remote-Tuning – Case Study of PI Controller for the First-Order-Plus-Dead-Time Systems

Analytical approach to tuning of model predictive control for first-order plus dead time models

Model predictive control (MPC) is an effective control strategy in the presence of system constraints. The successful implementation of MPC in practical applications requires appropriate tuning of the controller parameters. An analytical tuning strategy for MPC of first-order plus dead time (FOPDT) systems is presented when the constraints are inactive. The available tuning methods are generall...

Efficient and Robust Parameter Tuning for Heuristic Algorithms

The main advantage of heuristic or metaheuristic algorithms compared to exact optimization methods is their ability in handling large-scale instances within a reasonable time, albeit at the expense of losing a guarantee for achieving the optimal solution. Therefore, metaheuristic techniques are appropriate choices for solving NP-hard problems to near optimality. Since the parameters of heuristi...

Fractional order robust adaptive intelligent controller design for fractional-order chaotic systems with unknown input delay, uncertainty and external disturbances

In this paper, a fractional-order robust adaptive intelligent controller (FRAIC) is designed for a class of chaotic fractional order systems with uncertainty, external disturbances and unknown time-varying input time delay. The time delay is considered both constant and time varying. Due to changes in the equilibrium point, adaptive control is used to update the system's momentary information a...