Sliding Mode Control in Heavy Vehicle Safety

In this paper, an original method about heavy-vehicle rollover risk prediction is presented and validated experimentally. It is based on the calculation of the load transfer ratio (LTR), which depends on the estimated vertical forces using high-order sliding-mode (HOSM) observers. Previously, a tractor model is developed. The validation tests were carried out on an instrumented tractor rolling on the road at various speeds and lane-change maneuvers. Many scenarios have been experienced: driving tests in a straight line, a curve, and a zigzag line, and brake tests to emphasize the rollover phenomenon and its prediction to set off an alarm to the driver. In this paper, the vehicle dynamic parameters (masses, inertia, stiffness, etc.) and the static-force infrastructure characteristics (road profile, radius of curvature, longitudinal and lateral slopes, and skid resistance) are measured or calculated before the tests.

In this paper, an original method about heavy vehicles rollover risk prediction is presented and validated experimentally. It is based on the calculation of the LTR (load transfer ratio) which depends on the estimated vertical forces using high order sliding mode observers. The validation tests were carried out on an instrumented truck rolling on the road at various speeds and lane-change manoeuvres. Many scenarios have been experienced: driving on straight line, curve line and zigzag to emphasize the rollover phenomenon and its prediction to set off an alarm to the driver.

The benefit of data fusion in improving the performance of Higher Order Sliding Mode (HOSM) observer is brought out in this paper. This improvement in the performance of HOSM observer, resulted in the improvement of active vibration control of a piezo actuated structure, when controlled by a Discrete Sliding Mode Controller (DSMC). The structure is embedded with two piezo sensors for measuring the first two vibrating modes. The fused output of sensors is applied to the HOSM observer for generating state estimates, these states generated are applied to the DSMC, designed for the fourth order linear time invariant model of the structure. In the simulation study, the structure is excited at the first and second mode resonance. It is found that better vibration suppression is obtained, when the states generated by the fused output of sensors is applied as controller input, than the vibration suppression obtained by applying the states generated by using individual sensor output. The closed loop performance of DSMC obtained with HOSM observer is compared with the closed loop performance obtained with the conventional observer. Results obtained shows that better vibration suppression is obtained when the states generated by HOSM observer is applied as controller input.

High Order Sliding Mode Control and Observation for DP Systems

Modelling heavy vehicle lane changing

The rollover stability of the tank truck was quite poor compare with others due to the influence of the oscillating liquid inside the tank. In addition, it was also affected by road excitation during driving. Therefore, the paper presents the impact of the road profiles in turning and lane change maneuvers on the rollover stability characteristics of a liquid tank truck. Firstly, the study applies the quasi-static method and the roll model to built the dynamic model of a circular cross-section tank truck. After that, the Lagrange method and the D'Alembert's principle are used to set up the differential equations which are then used to investigate rollover stability of vehicle corresponding with each liquid level. The research used the value of the load transfer ratio (LTR), crest factor of LTR and the roll angle of suspension to evaluate vehicle stability in the time domain and the transfer function magnitude of LTR in the frequency domain. The simulation results had shown that the tank truck tends to a rollover phenomenon at the fluid level in tank of 50% and 75% (0.8m and 1.2m) when the vehicle ran survey road profiles in a steady state turning maneuver and in a lane change maneuver as there was not the road excitation. The research results can provide recommendations when operating liquid tank truck, developing control systems and warning of rollover.

This work propose the sliding mode controller (SMC)-based field oriented control (FOC) for brushless direct current (BLDC) motor, and in later part investigated the speed and position estimation using higher order sliding mode observer (HOSMO), which may come as a solution for sensorless operation. The main idea of this work is to improve the dynamic response and reduce torque ripples in the BLDC motor with the proposed techniques. Speed tracking performance has been analyzed with different statistical performance and torque ripples with percentage variation with respect to the applied external torque. Further, rotor position and speed estimation using HOSMO is validated against real-time measured values and checked for percentage error. To validate the results of proposed approach, the SMC with HOSMO is implemented on a STM32Nucleo-144 development board and its performance is analyzed by hardware-in-the-loop co-simulations for reference tracking. Results shows that the designed SMC is a promising candidate for the BLDC motor control, with characteristics of improved speed tracking response for a wide speed range with minimum values for error performance indices and torque ripples are reduced by 5.84%.

In this chapter the design of active steering assistance systems for heavy vehicles is discussed. These kinds of systems are oriented to avoid the rollover and prevent lane departure of the vehicle. The methodology herein illustrated is based on the super-twisting algorithm. An estimator relying on high order sliding mode observer is developed in order to get information on the vehicle dynamics, such as lateral acceleration limit and the height of the center of gravity. The lateral position and lateral speed are controlled using sliding mode control in order to ensure the stability of the vehicle and avoid accidents. While in standard practical situations the lateral offset and the relative yaw angle are typically measured and the road curvature can be assumed known, the identification of some relevant parameters of the model needs to be carried out in order to increase the robustness of the control system, as discussed in the chapter. Simulation and experimental results are reported, making reference to a tractor model, in order to show the quality of the presented concept.

The main focus of this study is to develop a finite‐time super‐twisting sliding mode control strategy for the quadrotor based on a higher‐order sliding mode observer (HOSMO). 12 state variables are required to describe the motion of the quadrotor, of which six state variables, namely the position, altitude, and orientation, are assumed to be obtained from the sensors. The remaining state variables, i.e. the linear and angular velocities, are determined using the HOSMO. Besides, the HOSMO aids in determining the unknown bounded lumped disturbances acting on the quadrotor. The output of the HOSMO is utilised for implementing the finite‐time super‐twisting sliding mode controller (FTSTSMC). The proposed FTSTSMC ensures finite‐time convergence of tracking error with chattering attenuation. The chattering analysis for a super‐twisting algorithm is presented in this work. Moreover, the overall system stability is investigated using the Lyapunov theory, and an expression for the time of convergence of the tracking and estimation error is presented. The effectiveness of the proposed methodology is established using numerical simulations and its performance is compared to a finite‐time sliding mode observer coupled with a combination of proportional–integral–derivative and continuous sliding‐mode controller. This is then validated in real‐time using the DJI Matrice 100.

This paper develops a new method to control uncertain robot manipulators by using only position measurements. The controller is designed based on a combination of a computed torque controller (CTC) with a higher-order sliding-mode observer and a fuzzy compensator. First, three higher-order sliding-mode (SM) observers (second-order SM, third-order SM and third-order SM linear (TOSML) observers) are designed and compared to verify whether the TOSML observer is the best for observing velocity and identifying uncertainty. A combined CTC-TOSML controller was then designed. Although this controller scheme can overcome the drawbacks of conventional CTCs, its tracking performance can still be improved. To enhance capability of the tracking performance, a CTC-TOSML controller plus fuzzy compensator called a CTC-TOSML-Fuzzy controller is proposed. The proposed controller increases the potential of the CTC for real robot applications. Finally, computer simulation results on a PUMA560 robot are discussed to verify the effectiveness of the proposed strategy.

For the problem of multi-missiles intercepting single maneuvering target, the cooperative guidance law with impact time and angle constraints was presented. Firstly, considering the system dynamics equation and the multi-agent consensus algorithm, a second order sliding mode controller along the line of sight(LOS) was proposed based on integral sliding mode control concept to guarantee salvo interception. Then an higher order sliding mode observer (HOSMO) was designed to estimate external disturbances of the perpendicular to the LOS. In addition, the sliding mode controller with HOSMO was proposed to guarantee the LOS angles converge to desired commands and the LOS angle rates converge to zero. Moreover, the stability of the two subsystem channels were proved by Lyapunov theorem. Simulation results illustrate the effectiveness of the proposed cooperative guidance law.

Experimental Validation of Unknown Inputs Estimation Via High Order Sliding Mode Observer

Quasi-continuous high-order sliding mode controller and observer design for flexible hypersonic vehicle

In this paper, the permanent magnet synchronous motor (PMSM) servo system with backlash is studied. Since the mechanical transmission of the servo system uses gears, screw rods, on the one hand, the proper backlash can ensure the normal operation of the transmission mechanism; on the other hand, the existence of backlash nonlinearity will reduce the rigidity of the transmission mechanism, affect the tracking performance of the system, and even lead to mechanical resonance. In order to eliminate the influence of the backlash nonlinearity, the modeling and identification of the backlash nonlinearity are introduced, and the influence of the backlash is compensated in the regulator. In addition, in order to reject the possible model deviation and uncertain interference, reduce steady states fluctuations, a high-order sliding mode observer (HOSMO) based nonsingular terminal sliding mode control (NTSMC) is designed. After simulation verification, the compound controller proposed in this paper can effectively reduce the influence of the backlash nonlinearity and improve the position tracking performance of the system.

This article proposes a new sliding mode control (NSMC) reaching law to improve the speed-tracking and anti-interference performance of permanent magnet synchronous motors (PMSMs). The NSMC improves the sliding mode control (SMC) in approaching speed and reducing chattering. First, considering that the external load interference will adversely affect the control system, a high-order sliding mode observer (HOSMO) is designed to observe the load torque, and the observed value is compensated to the output of the speed controller. Then, combined with the Landau algorithm, a variable adaptive gain algorithm is introduced to decrease the impact of inertia mismatch on the system control performance. The algorithm identifies the rotational inertia online, reduces the effect of load disturbance on the identification performance, and updates the identification results to the observation in processors and controllers. Experimental results show that the proposed control method reduces the speed and current fluctuations of the system when load torque and inertia vary and improves the system’s robustness.