Exact(12)
The PI controller is capable of automatically online tuning the control gains based on the gradient descent method and the supervisory controller is developed to eliminate the effect of the approximation error introduced by the PI controller upon the system stability in the Lyapunov sense.
It is shown that there is an allowable region for tuning the control gain without loosing the stability.
The literature still lacks use of recently developed evolutionary algorithms for cruise control that could leverage road safety by tuning the control parameters.
Simulated results showing the effect of tuning the control loop parameters based on the frequency response of each axis are presented.
Moreover, for the leader-following case, the Lyapunov stability analysis shows that the consensus tracking errors can be made arbitrarily small by tuning the control parameters.
We provide guidelines for tuning the control algorithm and computing the Kalman gain in the linear state space model in innovation form.
Similar(48)
The reconfigurable responses are realized by tuning the controlling voltages of the two varactor diodes thereby resulting compact size and less loss.
Then, an adaptive PID control algorithm is designed to auto-tune the control gain of the controller through the gain estimation.
Finally, the output of the learning agent using actor critic neural network is used to dynamically tune the control signal of local controller.
A number of options may then be initiated: altering the parameters of the semi-active unit, or re-tuning the control parameters in the active unit, or concurrently adjusting the two.
Adaptive control has been extremely developed by using intelligent algorithms to automatically tune the control parameters namely fuzzy logic, particle swarm optimization, bacterial search algorithm, and etc.
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