Approximation-Free Prespecified Time Bionic Reliable Control for Vehicle Suspension

Developing a solution to suppress vibration with low energy consumption is an interesting and significant topic for vehicle suspension. This paper proposes an approximation-free prespecified time energy-efficient fault-tolerant control scheme for active suspensions. Inspired by the X-shaped asymmetric structures that existed in animal limbs, the energy consumption can be significantly reduced, without changing the hardware structure and optimization, only by introducing bionic dynamics. Moreover, the states can converge to a neighborhood of zero within a pre-specified finite time interval by employing the designed bionic control framework. Note that the settling time is independent of the initial values of states and the controller parameters. Meanwhile, system uncertainties, external perturbations, and actuator faults can be handled effectively by the presented approximation-free controller. The knowledge of actuator faults, perturbation, and suspension model is not required for controller design. By using the designed approximation-free prespecified time bionic fault-tolerant controller, excellent ride comfort can be achieved with low energy consumption. Experiments are performed and corresponding comparison results are provided to demonstrate the superiority of the developed control method. Note to Practitioners —Vehicle active suspensions offer a higher degree of control freedom to isolate vibrations, however, are associated with expensive energy consumption. Model uncertainties, non-linearities, external disturbances, and actuator faults in real-world environments can lead to performance degradation. Motivated by this, this paper designs a bio-inspired energy-saving prespecified time approximation-free fault-tolerant controller. By employing dynamical properties inspired by X-type structures that exist in animal limbs or bones, efficient energy-saving control can be achieved. The transient responses are constrained to a prescribed region and converge to a given steady-state region within a pre-assigned time. The proposed controller does not require approximation structures such as neural networks or fuzzy rules. Consequently, the controller exhibits a simple structure that can be readily implemented and deployed in practical suspension systems. Experimental results obtained from practical suspension platforms under different road excitations demonstrate satisfactory energy saving and vibration suppression performance of the presented control scheme.