By Yaobin Chen and Lingxi Li (Auth.)
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8 s. 4 and the same initial conditions in optimal braking control. 10: Simulation Results of Braking a UW-Car System With Optimal Parameters. 11: Simulation Results of Braking a UW-Car System Without Optimal Parameters. 245), in approximately 9 seconds. Compared to the two sets of figures and data, we can conclude that the optimal braking control is effective. 3 Set-Point Velocity Control Simulation in Rough Terrain À Á The initial states are chosen as: qð2Þ 0 ¼ ½ 0:01 0 0 0 0 T . 04sin(5x) is investigated.
The dynamic model of a UW-Car system is obtained by applying Lagrange’s motion equations, for both the case of running on flat ground and on rough terrain. Based on the model, velocity control and optimal braking strategy are discussed. A terminal sliding mode control method is proposed for velocity control, which guarantees that the UW-Car system can always keep the body upright and the seat in a desired position. Compared to the LQR method, the TSMC method presents better performance. A strategy of optimal braking with optimal parameters computed by a GA is proposed, which guarantees that the UW-Car system stops in a short distance by implementing online switching three terminal sliding mode controllers.
It turns out that the TSMC controller guarantees the inclination angle of the body to be approximately zero and the seat to vibrate very slightly near a certain position. With the TSMC controller it takes a long time for the UW-Car system to accelerate to the desired velocity, but for other parameters such as overshoot, the speed changes are excellent. 2 Optimal Braking Control Simulation on Flat Ground We verify the effectiveness of optimal braking control by the simulation in MATLAB. The limitation of seat displacement is jlmax j ¼ 0:2.
Advances in Intelligent Vehicles by Yaobin Chen and Lingxi Li (Auth.)