In further work it will be necessary to concentrate on gathering as much experimental data as possible to be able to truly validate the designed model (finding out the dependencies of stiffness and damping coefficients, improving the accuracy of static force approximator
, including pneumatic lines into the model etc.
The ADP scheme solves the Bellman equation iteratively only for the state points obtained from closed-loop simulation with the local function approximator
The Cerebellar Model Arithmetic Computer (CMAC) algorithm provides a computationally-efficient and accurate nonlinear approximator
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Any other static approximator
can also be utilized, which indeed is a good idea in order to avoid the inferior interpolation and extrapolation capabilities of polynomials.
We will use a radial basis function approximator
for this so that
One approach to identify a nonlinear i/o system is to use a model structure that can be considered as a general approximator
to the nonlinear mapping f , such as neural networks.
To map the multi-input and multi-output (MIMO) relationship, neural networks have been well recognized as a kind of universal function approximator
(Hagan and Demuth 1996; Hornik et al.
Consequently, geographic distance between populations may be a good approximator
of gene flow in salmon species; however, inferring barriers to migration on the basis of geographical or physical features alone can be misleading (Waples, 1991).
He proposed to adopt fuzzy inputs and/or fuzzy weights in neural networks to allow the use of neural networks as a universal approximator
(Buckley and Hayashi, 1994; Feuring, Buckley, and Hayashi, 1998; Jiao et al.
It is a universal function approximator
that typically works much better in practical applications than most traditional and polynomial-based function approximations methods.
It is a universal and efficient approximator
with temporal properties.