Model predictive control–based steering control algorithm for steering efficiency of a human driver in all-terrain cranes

When heavy-duty commercial vehicles (HDCVs) must engage in emergency braking, uncertain conditions such as the brake pressure and road profile variations will inevitably affect braking control. To minimize these uncertainties, we propose a combined longitudinal and lateral controller method based on stochastic model predictive control (SMPC) that is achieved via Chebyshev–Cantelli inequality. In our method, SMPC calculates braking control inputs based on a finite time prediction that is achieved by solving stochastic programming elements, including chance constraints. To accomplish this, SMPC explicitly describes the probabilistic uncertainties to be used when designing a robust control strategy. The main contribution of this paper is the proposal of a braking control formulation that is robust against probabilistic friction circle uncertainty effects. More specifically, the use of Chebyshev–Cantelli inequality suppresses road profile influences, which have characteristics that are different from the Gaussian distribution, thereby improving both braking robustness and control performance against statistical disturbances. Additionally, since the Kalman filtering (KF) algorithm is used to obtain the expectation and covariance used for calculating deterministic transformed chance constraints, the SMPC is reformulated as a KF embedded deterministic MPC. Herein, the effectiveness of our proposed method is verified via a MATLAB/Simulink and TruckSim co-simulation.

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Instability load analysis of a telescopic boom for an all-terrain crane

Zhuo²,

Zai-kang³

et al. 2022

Mech. Sci.

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Abstract. The instability load for the telescopic boom of an all-terrain crane is investigated in this paper. Combined with structural characteristics of the telescopic boom, each boom section is divided into several substructures, and the fixed-body coordinate system of each substructure is established based on the co-rotational method. A 3D Euler–Bernoulli eccentric beam element of the telescopic boom is derived. On the premise of considering the discretization of gravity and wind load, internal degrees of freedom of the substructure are condensed to the boundary nodes, forming a geometrical nonlinear super element. According to the nesting mode of the telescopic boom, a constraint way is established. The unstressed original length of the guy rope is calculated with a given preload so as to establish the equilibrium equations of the boom system with the external force of the guy rope and the corresponding tangent stiffness matrix. Regarding the above work, a new method for calculating the structural equilibrium path and instability load of telescopic boom structure is presented by solving the governing equations in a differential form. Finally, the method is validated by examples with different features.

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Model predictive control–based steering control algorithm for steering efficiency of a human driver in all-terrain cranes

Cited by 3 publications

References 13 publications

Multiple Vehicle Tracking Using Meanshift Algorithm and 8-point Connectivity

Multiple Vehicle Tracking Using Meanshift Algorithm and 8-point Connectivity

Stochastic model predictive braking control for heavy-duty commercial vehicles during uncertain brake pressure and road profile conditions

Instability load analysis of a telescopic boom for an all-terrain crane

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