Actuator and sensor fault detection and isolation of an actuated seat via nonlinear multi-observers

Figures & data

Fig. 1. Open chain with tree structure.

Fig. 2. Different joints of the seat.

Table 1.  Joints significations.

r1	Tracking position expressed in m
θ2	Angle of the seating expressed in rad
θ3	Angle of the legrest expressed in rad
r4	Footrest position expressed in m
θ5	Angle of the seat-back expressed in rad
r6	Headrest position expressed in m

Fig. 3. The approximation of θ₂with cubic polynomial.

Fig. 4. Majorant curve for the finite time convergent observer.

Fig. 5. Multi-observers for actuators faults detection and isolation.

Table 2.  Actuators faults signature table.

	res1	res2	res3	res4	res5
	1	0	0	0	0
	0	1	0	0	0
	0	0	1	0	0
	0	0	0	1	0
	0	0	0	0	1

Fig. 6. Multi-observers for sensors faults detection and isolation.

Table 3.  Sensors faults signature table.

	res1	res2	res3	res4	res5
sensor1	1	0	0	0	0
sensor2	0	1	0	0	0
sensor3	0	0	1	0	0
sensor4	0	0	0	1	0
sensor5	0	0	0	0	1

Table 4.  Parameters of the model.

Parameter	Value	Unit
M	17	kg
m4	2	kg
m6	1	kg
L3	0.3	m
L6	0.2	m
l6	0.7	m
β	0.327	rad
h0	0.324
C5	1.57
g	9.81
P23	9.81
P25	23.053

Fig. 7. Detection of the tracking actuator fault.

Fig. 8. Detection of the legrest actuator fault.

Fig. 9. Detection of the footrest actuator fault.

Fig. 10. Detection of the seat-back actuator fault.

Fig. 11. Detection of the headrest actuator fault.

Fig. 12. Detection of the legrest position sensor fault.

Fig. 13. Detection of the seat-back position sensor fault.