Sensor and actuator attacks, which propagate the injected false data through CAN bus, make real threats to the security of the control of autonomous vehicles. This paper attempts to solve the secure event-triggered path following control problem of autonomous vehicles subject to both sensor and actuator attacks. Firstly, a more general physical security model is established to characterize the impacts of sensor and actuator attacks on measurements and control actions. Then, feedback linearization method based on Lie derivative is exploited to linearize the established nonlinear attacked model. Thus, the nonlinear path following control is transformed into a linear case which will facilitate to the following networked-based analysis and design. Based on the established secure model, the event-triggered control scheme is utilized to alleviate communication burden under sampled-data control framework. Furthermore, the sliding control design is augmented to mitigate the malicious impacts caused by such false data injection attacks due to its inherent robustness to abnormal attack signal. Remarkably, the proposed secure sliding control can be plugged into the original control scheme rather than changing its existing control structure. Criteria for formal stability analysis and controller design are also provided and expressed in terms of some numerically tractable linear matrix inequalities. Finally, both simulation and experimental verification cases are shown to verify the composite control scheme.

For effective energy regeneration and vibration dampening, energy regenerative suspension systems have received more studies recently. This paper presents the dynamic modeling and a test system of a regenerative shock absorber system which converts vibration motion into rotary motion through the adjustment of hydraulic flow. Hydraulic circuit configuration achieves the one way flow and energy regeneration during both compression and extension strokes. The dynamic modeling is performed for the evaluation of design concept and the feasibility studies of regenerative shock absorber system theoretically. Based on simulated results, the efficiency of hydraulic transmission is optimized and validated in test system. The results show that the performance of hydraulic fluid, the features of rotary motion and the capability of energy regeneration are verified and compared between dynamic modeling and experiments. Meanwhile, the average power of 118.2W and 201.7W with the total energy conversion of 26.86% and 18.49% can be obtained based on experiments under sinusoidal inputs with 0.07854m/s and 0.1256m/s respectively.

Aiming at the low-cost, wide-range, and accurate measurement requirement for Microelectromechanical System (MEMS) Inertial Measurement Unit (IMU) on a multi-rotor Unmanned Aerial Vehicle (UAV), the paper designs a heterogeneous parallel redundancy configuration scheme. In redundant MEMS IMUs, a high-cost and small-range MEMS gyroscope is combined with low-cost and large-range MEMS gyroscopes. Then, an adaptive data fusion method of redundant MEMS gyroscopes is proposed. By the designed experiments based on the simulation data and the sensor measurement data, the proposed method has been proved that it can effectively improve the angular rate measurement performance of the multi-rotor UAV and broaden the angular rate measurement range on the basis of saving the configuration cost and volume of the micro IMU.

This paper presents a control strategy named Auxiliary Surfaces Sliding Mode Control (AS-SMC) by using Positive Invariant Set (PIS) to control a class of continuous nonlinear systems with state constraints. The PIS can be regarded as a special kind of sliding surface, and its invariance ensures that the system state can satisfy the constraints in the convergence process. Stability analysis and a PIS theory proof are given. The control strategy is successfully tested in numerical simulations and even applied to the coaxial unmanned helicopter flight control system effectively on a hardware in the loop (HIL) platform. The results verify the effectiveness of the proposed control strategy for the experimental set-up.

Using an MEMS Inertial Measurement Unit (MEMS IMU) array mounted on foot is a feasible approach to improve the pedestrian tracking accuracy for the pedestrian navigation system (PNS). Based on the in-house developed IMU array, the paper proposes a new integrated framework that combines adaptive deck reckoning (ADR) with the modified zero velocity update (ZUPT). In the proposed ADR algorithm, the IMUs with large drift errors on the array are selected and removed according to the step length and the track angle computed by each IMU on the array. Then, by using the step length and the track angle of each step computed by remaining IMUs, the foot position extracted from the traditional ZUPT model is estimated on the basis of least squares (LS) so as to improve the traveled distance calculation accuracy. Compared with the traditional IMU array fusion method based on a maximum likelihood estimator (MLE) when it is used in the PNS, which is approximately taking the mean value of array readings, the proposed method is equivalent to adaptively fusing the array readings and thus improves the pedestrian tracking accuracy. To compare the proposed method with MLE, two different types of walking tracks are designed. The 161 m straight line experiments show that the end position by ADR/modified ZUPT method is much closer to the one of the reference trajectory compared with the MLE in repeated walks, and the closed-loop tracks about 300 m show that the positioning error with respect to the total traveled distance is less than 0.6% (1σ), which is higher than 1% (1σ) of MLE.