In this paper, a novel Suspension Travel Tracking Preview Control (STTPC) algorithm is proposed for the multi-axis vehicle. This study considers specific structural suspension designs for multi-axle vehicles and develops specific control algorithms accordingly. The underlying principle of the algorithm is to make full use of the working space of the suspension so that the suspension displacement tracks the road excitation. In this way, the body acceleration due to external input, road excitation, can be reduced. In addition, the algorithm can take advantage of the acquired road elevation information to enable the actuators to respond in advance, thus further improving the system response and reducing the negative effects of time delay. In the paper, the dynamics of the full vehicle active suspension system is modeled first, and then the control law of the algorithm is derived based on the tracking problem of optimal control theory. Finally, simulations based on MATLAB/Simulink platform are performed under both deterministic and stochastic road profiles to verify the effectiveness of the proposed algorithm.
KEYWORDS: Roads, Detection and tracking algorithms, Signal filtering, Design and modelling, Systems modeling, Stochastic processes, Simulations, Sensors, Control systems, Matrices
In this paper, a novel Suspension Travel Tracking Preview Control (STTPC) algorithm is proposed for the off-road vehicle. The research takes the specific structural suspension design of off-road vehicles into consideration and develops a specific control algorithm accordingly. The underlying principle of the algorithm is to make full use of the working space of the suspension to make the suspension displacement track the road excitation. Thus, the body acceleration caused by the external input, road excitation, can be reduced. In addition, the unknown input Kalman observer is combined with the proposed preview control algorithm to solve the problem of obtaining the preview information and estimating the suspension state information driving. Finally, simulations based on MATLAB/Simulink platform are performed to verify the effectiveness of the preview control algorithm and unknown input observer under deterministic and stochastic road profiles.
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