No abstract

No abstract

The traditional frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar two-dimensional (2D) super-resolution (SR) estimation algorithm for target localization has high computational complexity, which runs counter to the increasing demand for real-time radar imaging. In this paper, a fast joint direction-of-arrival (DOA) and range estimation framework for target localization is proposed; it utilizes a very deep super-resolution (VDSR) neural network (NN) framework to accelerate the imaging process while ensuring estimation accuracy. Firstly, we propose a fast low-resolution imaging algorithm based on the Nystrom method. The approximate signal subspace matrix is obtained from partial data, and low-resolution imaging is performed on a low-density grid. Then, the bicubic interpolation algorithm is used to expand the low-resolution image to the desired dimensions. Next, the deep SR network is used to obtain the high-resolution image, and the final joint DOA and range estimation is achieved based on the reconstructed image. Simulations and experiments were carried out to validate the computational efficiency and effectiveness of the proposed framework.

As the possibility of faults in active suspension actuators are higher and more severe compared to other components, this study presents a fault-tolerant control approach based on the second-order sliding mode control method. The aim of the controller is to improve riding comfort, guarantee handling stability, and provide adequate suspension stroke in the presence of disturbances and actuator faults. A nonlinear full-vehicle suspension system and hydraulic actuator with nonlinear characteristics are adopted for accurate control. Firstly, a nonlinear sliding manifold based on a nonsingular fast terminal sliding mode controller is introduced to suppress the sprung mass heave, pitch, and roll motions arising from road disturbances. Secondly, a second-order sliding mode-based super twisting controller is utilized to track the desired forces generated by the nonsingular fast terminal sliding mode controller with actuator faults and uncertainties. The controllers are robust against disturbances, uncertainties, and faults. Moreover, the stability of the super twisting controller is proved by the strong Lyapunov functions. Finally, numerical simulations are performed to demonstrate the effectiveness of the controller. Four different conditions, random road profile, bump road excitation, single-wheel bump excitation, and partial faults are considered. The main contributions of this study are: (1) combination of the above algorithms to deal with actuator faults and improve active suspension performance; (2) the controller proposed in this study has a simple structure. Simulation results indicate that the nonsingular fast terminal sliding mode super twisting controller can guarantee the performance of the closed-loop system under both faulty and healthy conditions.

As the deviation error will accumulate during the data acquisition and transcoding process of an active suspension system, this paper presents a sliding-mode-based quantized feedback control method. The aim of the controller is to improve the vertical performance of vehicles in the presence of external interferences. A 7-DOF suspension model with nonlinear springs and actuator dynamics is built for the control purpose. Firstly, a static quantizer on the uplink channel and a dynamic quantizer on the downlink channel are considered in the sliding mode controller to reduce the cumulative error and suppress the sprung mass motions. Secondly, an event trigger mechanism is introduced in the controller design process to reduce energy consumption and operation frequency of the actuator. The overall stability of the designed controller is proved by the Lyapunov functions. Finally, numerical simulations are carried out to evaluate the efficacy of the proposed controller. Different quantitative and trigger conditions are discussed, and the random road excitation is considered as the external disturbance input. The results of the control method indicate that the designed controller can improve the riding comfort with little loss of handling stability compared with the passive system. In addition, the trigger mechanism can improve the working efficiency of actuators effectively.