Off-road vehicles always experience serious uncertain longitudinal and lateral slips when running on soft and slope terrains, and the parameters of the vehicle, such as the cornering stiffness and the slip of wheel, are always not constants. In this paper, the control strategies for the torque of each wheel and the steering angle of rear wheels are proposed to maintain a stable velocity and approach an ideal reference model for the off-road vehicle by using second-order sliding mode (SOSM) techniques. An observer is constructed to estimate the actual sideslip angle of the vehicle with the consideration of the uncertainties and disturbances of the system. Then, with the conditions of the bounded derivative of these uncertainties and disturbances, the composite super-twisting (ST) controllers combined with a velocity controller of SOSM are designed to generate the total longitudinal traction, differential traction of two sides, and steering angle of rear wheels. On this basis, the proposed controllers have been verified to lead good robustness for maintaining the stable velocity and approaching the ideal reference model. In comparison with the conventional yaw moment controllers without the rear wheel steering, the proposed controllers are shown to be more effective.

An active equalization method based on redundant battery is proposed in this paper. A redundant battery is added to a battery pack consisting of several series batteries. According to the capacity and SOC (state of charge) of series batteries in the battery pack, one of these batteries is in parallel with the redundant battery in a certain time period. On the one hand, the energy is transferred between the redundant battery and the equalized batteries. On the other hand, during the charging or discharging process, the redundant battery acts as a power source, which reduces the current of the equalized battery. By adjusting the length of time that redundant battery and series batteries are connected in parallel, the purpose of battery equalization will be achieved. The balance current is limited only by the maximum charge-discharge ratio of the batteries. As long as the sum of the difference of series batteries capacity is less than the redundant battery capacity, the balance of all batteries can be achieved. Compared with other active equalization methods, the energy storage element (redundant battery) is used to be the main component of the equalization circuit in this method. It not only has the advantages of simple equalization circuit and large equalization current, but also has higher energy density of battery pack. In this paper, the equalization circuit is given, and the equalization strategy with accurate battery parameters and uncertain battery parameters is proposed. The experimental results also verify the correctness of the theoretical analysis and modeling.

As tire forces approach road friction limits, vehicles may always exhibit performance degradation and even instability. The actual capacity of the available road friction imposes coupled limits on a vehicle's longitudinal and lateral accelerations. In this paper, a varying speed method is proposed to design feasible speeds and accelerations, which ensure that the autonomous vehicle will not reach the tire-road friction limits during traversing a clothoid-based path. With the consideration of uncertain traction losses and vehicle parameters, a second-order super-twisting (ST) based speed control strategy is proposed to track above feasible speeds based on varying speed method, and to stabilize the sliding-mode variable of the speed tracking error with relative degree 1. Meanwhile, a second-order quasi-continuous (QC) based path-following control strategy is proposed to follow a desired transition path, and to stabilize the sliding-mode variable of the composite path-following errors with relative degree 2. On this basis, the proposed controllers have been verified to lead good robustness for tracking the ideal speeds and following the desired paths. As compared with the boundary of the autonomous vehicle running at a constant speed, the feasible speed boundary using varying speed method without exceeding the tire-road friction limits can be enlarged up to about 1.59 times, which is decided by the direction change between the entry and exit points of the desired path.

Polymer electrolyte membrane fuel cell (PEMFC) air-feed subsystem is usually affected negatively by system uncertainty and unavailable variable. This paper investigates a discrete neural network control with an observer for the oxygen excess ratio (OER) control. The control goal is to avoid oxygen starvation and maintain the optimal net power. Specifically, by utilizing coordinate transformation and Euler approximation, the discrete strict-feedback form is obtained, and the backstepping technique can be applied. To estimate the unavailable variable with the measurable system output, a discrete neural network observer is proposed. Besides, the discrete neural network controller is designed to tackle the system uncertainty and achieve an ideal OER tracking. Finally, the system tracking error is proved to be semi-globally uniformly ultimately bounded by Lyapunov stability theory. Numerical simulations and hardware-in-loop (HIL) experiments are presented to demonstrate the effectiveness and superiorities of the proposed controller.

Polymer electrolyte membrane fuel cell (PEMFC) air supply systems are usually affected negatively by model uncertainties, external disturbance and unmeasured variables. In this paper, we propose a composite adaptive type-2 fuzzy controller based on a high-gain observer and a disturbance observer for oxygen excess ratio (OER) of PEMFC air supply systems. Firstly, the derivatives of system output, which are unavailable due to limited sensors, are estimated via the high-gain observer. Then, interval type-2 fuzzy logic systems (IT2 FLSs) are adopted to approximate the unknown system dynamics and the disturbance observer is designed to estimate compound disturbance including unknown external disturbance and fuzzy approximation error. Finally, in order to improve the tracking performance, two composite adaptive updating laws are constructed by utilizing the estimated tracking error and the modeling error. Theoretical analysis shows that the system tracking error is uniformly ultimately bounded by Lyapunov stability theory. Numerical simulations and hardware-in-loop (HIL) experiments are presented to demonstrate the effectiveness and superiority of the proposed controller.

This article addresses the steering control problem for steer-by-wire (SbW) systems subject to the unknown uncertainty, external disturbance and unavailable variable. Before the controller design, an adaptive neural network-based observer and a disturbance observer are constructed to estimate the angular velocity signal and the compound disturbance, respectively. Then, to guarantee the transient and steady-state performance of steering tracking error within the quantitative boundary, a prescribed performance function is constructed by user-designed tracking accuracy and settling time. Finally, the controller is designed based on the backstepping scheme and the neural network with a composite learning scheme is proposed for the approximation of lumped uncertainty. The Lyapunov stability theory shows that the signals involved in the system are semiglobal uniformly ultimately bounded and the tracking error converges to a preset range at finite time. Different numerical simulations and experiments are implemented to verify the effectiveness of the developed control scheme.