319 research outputs found
A recent electronic control circuit to a throttle device
The main objective of this paper is to conceive a recent electronic control circuit to the throttle device. The throttle mechanical actuator is the most important part in an automotive gasoline engine. Among the different control strategies recently reported, an easy to implement control scheme is an open research topic in the analog electronic engineering field. Hence, by using the nonlinear dwell switching control theory, an analog electronic control unit is proposed to manipulate an automotive throttle plate. Due to the switching mechanism is commuting between a stable and an unstable controllers, the resultant closed-loop system is enough robust to the control objective
This fact is experimentally evidenced. The proposed electronic controller uses operational amplifiers
along with an Arduino unit. This unit is just employed to generate the related switching signal that
can be replaced by using, for instance, the timer IC555. Thus, this study is a contribution on design
and realization of an electronic control circuit to the throttle device.Peer ReviewedPostprint (published version
State Estimation of Open Dynamical Systems with Slow Inputs: Entropy, Bit Rates, and relation with Switched Systems
Finding the minimal bit rate needed to estimate the state of a dynamical
system is a fundamental problem. Several notions of topological entropy have
been proposed to solve this problem for closed and switched systems. In this
paper, we extend these notions to open nonlinear dynamical systems with
slowly-varying inputs to lower bound the bit rate needed to estimate their
states. Our entropy definition represents the rate of exponential increase of
the number of functions needed to approximate the trajectories of the system up
to a specified \eps error. We show that alternative entropy definitions using
spanning or separating trajectories bound ours from both sides. On the other
hand, we show that the existing definitions of entropy that consider supremum
over all \eps or require exponential convergence of estimation error, are not
suitable for open systems. Since the actual value of entropy is generally hard
to compute, we derive an upper bound instead and compute it for two examples.
We show that as the bound on the input variation decreases, we recover a
previously known bound on estimation entropy for closed nonlinear systems. For
the sake of computing the bound, we present an algorithm that, given sampled
and quantized measurements from a trajectory and an input signal up to a time
bound , constructs a function that approximates the trajectory up to an
\eps error. We show that this algorithm can also be used for state estimation
if the input signal can indeed be sensed. Finally, we relate the computed bound
with a previously known upper bound on the entropy for switched nonlinear
systems. We show that a bound on the divergence between the different modes of
a switched system is needed to get a meaningful bound on its entropy
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