Descripción

"simple systems can be controlled satisfactorily using classical control techniques and standard sensor arrays. these systems are generally of low complexity and typically have a single input and a single output (siso). classical design techniques are accompanied by a range of graphical and simple, but mature, mathematical tools which aid in the design, making the design procedure accessible even for the non experienced engineer. unfortunately, many systems today are highly complex, nonlinear and have multiple inputs and multiple outputs (mimo), hence classical techniques are more difficult to apply, if at all possible, and standard sensing may not be sufficient.
robust control and artificial intelligence techniques offer an alternative to classical control techniques, where the design of truly multivariable controllers, which can take into account plant uncertainty and which posses new forms of perception (e.g. vision) and autonomy, are sought; furthermore, these techniques can also enable one to deal with various nonlinearities which may be present in the system. although these techniques are based on more advanced mathematical concepts than traditional classical control methodologies, and require additional computational resources due to its newly found ""intelligence"", they enable the design of highly complex control systems which are guaranteed to satisfy certain stability, performance and autonomy properties.
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