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This paper intends to propose a performance adaptive-robust strategy for the design of control systems implemented on the industrial applications. This adaptive-robust control (ARC) strategy is taking into account both adaptive control advantages and robust control benefits and uses the same integral criterion for the process identification and for the control algorithm design. An optimal integral...
A loop transfer recovery (LTR) control method based on Genetic Algorithm (GA) — Back Propagation (BP) neural network is proposed for Hammerstein model of pH neutralization process with typical nonlinear characteristics in this paper. GA-BP neural network is used to establish the inverse model of nonlinear part, so that the LTR control based on inverse system method can be used to recover the performance...
The adaptive-robust control strategy, proposed in this paper, combines the advantages of robust and adaptive control, while minimizing the computational load. Usually, a lot of mathematical operations are necessary, which limit the real time applicability of such strategies. By developing a simple, yet useful rule, the number of operations needed to determine if a new controller is needed has been...
The paper discusses the application of a direct adaptive controller to a flow controlled artificial ventilation problem. The case study focuses on patients diagnosed with Chronic Obstructive Pulmonary Disease (COPD), which require artificial/mechanical ventilation. The controller ensures peak pressures below critical values, by manipulating the flow delivered by the ventilator. The simulation study...
The paper considers a problem of ship autopilot design based on the input-output feedback linearization method combined with the robust and adaptive control approaches. At first, the nonlinear ship model of Norrbin type is linearized with the use of the simple system nonlinearity cancellation. Next, as exact values of the model parameters are not known, the ensuing inaccuracies are taken as disturbances...
In this paper an improved robust evolving cloud-based controller (RECCo) for a class of nonlinear processes is introduced. The controller is based on parameter-free premise (IF) part. The consequence in this case is given in the form of PID-type controller. The three adjustable parameters of PID controller are updated on-line with a stable adaptation mechanism based on Lyapunov approach such that...
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