74 6. ROLLOVER CONTROL STRATEGIES AND ALGORITHMS
Without Control
Traditional PID Control
Optimized H∞ Control
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0/8
-1
-1.2
0 2 4 6 8 10
Time (s)
Rollover Index
Figure 6.10: Rollover indices of the vehicle under the double-lane change maneuver.
As shown in Figure 6.11, the maximum absolute value of the rollover indices are more than
1 for the vehicle without a controller. So, the vehicle rolls over when it moves in a straight line
or at cornering with an unpredictable bump without control. However, the rollover risk can be
avoided by the differential braking force using a traditional PID control method and optimized
H-infinity control method. Also, it can be found that the maximum value of the rollover index
of vehicle with the optimized H-infinity control method is lower and varies more smoothly
than that with the traditional PID control method in a tripped rollover situation. erefore,
the optimized H-infinity controller can obviously prevent vehicle rollover in a tripped rollover
situation.
6.3 MODEL PREDICTION CONTROL METHOD
Model predictive control features good control effect, strong robustness, and low requirement
for model accuracy and it can be used to control complex process effectively. So, model predictive
control is designed to prevent vehicle rollover by many researchers [35, 64, 65].
Model prediction control consists of three modules: MPC controller, controlled object,
and state solver. As shown in Figure 6.12, the MPC controller is responsible for combining
the prediction model, objective function and constraint condition to obtain the optimization
solution, getting the optimal control sequence u
.t/ of the current moment, then sending the