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In proposed asymmetrical FLC algorithm, the fuzzy functions of error input close to zero are used for fine-tuning, and the error input away from zero are used for coarse tuning.
To reduce the noise below 400 Hz, an active control system was designed with one reference, one error input and one control output.
In this paper, a model reference adaptive control strategy is used to design an iterative learning controller for a class of repeatable nonlinear systems with uncertain parameters, high relative degree, initial output resetting error, input disturbance and output noise.
A primary feature of the modelling is that dynamic mesh forces are calculated using a detailed contact analysis at each time step as the gears roll through the mesh; there is no need to externally specify the excitation in the form of time-varying mesh stiffness, static transmission error input, or the like.
In this paper, we derive an output tracking error model based on signals filtered from plant input and output, and then present a new output-based adaptive iterative learning controller for repeatable linear systems with unknown parameters, high relative degree, initial resetting error, input disturbance and output noise.
With zero error input, the output of the prediction step will also be zero.
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The boundedness of the estimation error (input-to-state stability property) and the observer stability conditions are stated as infinite-dimensional linear programming problems.
In this paper an adaptive neuro-fuzzy inference system (ANFIS) controller using error and derivative of error inputs is proposed for the speed control of a separately excited DC motor (SEDM) using chopper circuit.
The error inputs and the corresponding control outputs are experimentally measured in the pilot survey using the developed experimental setup shown in Figure 2.
Furthermore, the process of adjustment for case-mix takes account of some reasons for variation, but many other important factors (data error, inputs, processes and care pathways) are unmeasured [ 15].
At the top of each column of points, we list the regulator whose addition constitutes the lowest-error input set for the given number of regulatory inputs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com