Simultaneously, from both the theoretical analysis and a concrete example, smaller critical values for gain parameter and rescaling transformation parameter are obtained to effectively reduce the control effort and the rate of change of controller than the design of the related papers.
When the dynamic behavior of the structure change, the controller and reconstructor must be updated to cope with the changes in the structure behavior, in order to maintain both performance and robustness.
Furthermore, when the initial conditions of the system change, the controller with the previous parameters would be not optimum in the new conditions.
The presented principle doesn't change the controller structure and any degradation in the steady state performance is dealt with fixing that state variable which is associated with the sensor fault to the zero value.
The proposed BSMC can able to accommodate a constant disturbance of 10 kNm without any appreciable change in controller performance.
Plane crashes, for instance, have been attributed to an accumulation of micro-risk events (a missed signal, a tired driver, a late train, a change in controller shifts, etc). that occur simultaneously to create a major and much more serious event.
If we change the controller (8) to the following form: begin{aligned}[b] u(t) =& - frac{beta}{2}e(t) - frac{k}{2} operatorname {sgn}bigl(e(t) bigr biglvert e(t) bigrvert ^{alpha} & - frac{k}{2} biggl( int_{t - tau(t)}^{t} e^{T}(s)e(s),ds biggr)^{frac{1 + alpha}{2}} biggl(frac{e(t)}{ Vert e(t) Vert ^{2}} biggr),quad t ge0, end{aligned} (15) then the following corollary can be derived.
The actions available to a SIPS include [56]: load shedding, generation start up/rejection, switching of shunt reactors, line tripping, tap changes, adjusting controller set points, tap blocking, controlled islanding, HVDC control and switching of braking resistors.
