Control Moment Research Articles

A Novel Adaptive Non-Singular Fast Terminal Sliding Mode Control for Direct Yaw Moment Control in 4WID Electric Vehicles

This study proposes an adaptive non-singular fast terminal sliding mode control (NFTSMC)-based direct yaw moment control (DYC) strategy to enhance driving stability in four-wheel independent drive (4WID) electric vehicles. Unlike conventional SMC, the proposed method dynamically adapts to system uncertainties and reduces chattering, a critical issue in control applications. The approach begins with the development of an NFTSMC method, analyzing its performance to identify areas for improvement. To enhance robustness and responsiveness, a novel adaptive NFTSMC method is introduced. This method integrates a non-singular fast terminal sliding mode surface with a novel adaptive fast-reaching control law that combines an adaptive switching mechanism and a fast-reaching law. The designed adaptive switching law adjusts the sliding gain in real time based on system conditions, reducing chattering without needing an upper bound on uncertainties as required by traditional NFTSMC methods. Concurrently, the fast-reaching law ensures rapid convergence from any initial condition and accurate tracking performance. Simulation results across various steering maneuvers, including step, sinusoidal, and fish-hook inputs, demonstrate that the proposed method significantly improves tracking accuracy and driving stability over traditional SMC and NFTSMC methods. Marked reductions in RMS and peak yaw rate errors, and effective chattering mitigation, highlight advancements in vehicle safety and stability.

Handling Qualities sizing for aerial vehicles based on control moment polytopes

Handling Qualities sizing for aerial vehicles based on control moment polytopes

Tailless control of a four-winged flapping-wing micro air vehicle with wing twist modulation

This paper describes the tailless control system design of a flapping-wing micro air vehicle in a four-winged configuration, which can provide high control authority to be stable and agile in flight conditions from hovering to maneuvering flights. The tailless control system consists of variable flapping frequency and wing twist modulation. The variable flapping frequency creates rolling moments through differential vertical force from flapping mechanisms that can be independently driven on the left and right sides. The wing twist modulation changes wing tension, resulting in vertical and horizontal force variations during one flap cycle and generating pitching and yaw moments. We presume that the wing geometry and implementation method of wing-root actuation are related to the control authority of wing twist modulation. Then, the control system's performance is analyzed for various wing geometries and implementation methods, including wing length, leading-edge thickness, camber angle, and vein configuration. Furthermore, the cross-coupling effect is examined for the wing twist modulation, and a control surface interconnect is designed to compensate for the decrease of pitch control authority and adverse rolling moment. The refined wing and control mechanism demonstrated its high control authority without significant loss of vertical force and power efficiency. The flight experiments validated that the control system based on wing twist modulation is suitable for four-winged flapping-wing micro air vehicles, providing sufficient control moment and minimizing the cross-coupling effect.

Study of Yaw Moment Control Strategy of Four Wheel Independent Drive Electric Vehicle

Abstract A yaw moment control strategy for four wheel independent drive electrics vehicle is proposed in this paper. The control strategy is a hierarchical architecture which containing a yaw motion generation layer and a longitudinal force distribution layer. The yaw motion generation layer consists of feedforward control and feedback control. Unlike previous strategy, in this paper, yaw rate is considered as the only control variable which is feasible to be detected in practice. The feedforward control is used to enhance overshoot in transient condition while the feedback control is to change vehicle steady state steering characteristic and extend its lateral limit. The longitudinal force distribution layer is designed based on vehicle wheel load transfer model. It makes each tire fully utilized its lateral force limits. Based on these two layers, a control model is built accordingly. Both steady state and transient state experiments are conducted in Carsim simulation associated with the built Simulink control model. The simulation results show that proposed control strategy can enhance vehicle handling performance in steady state and transient state. Experiments were conducted on an electric vehicle which evaluated the accuracy of the established model and the effect of the proposed yaw moment control strategy.

New Approach of Hybrid Momentum Exchange Devices for Spacecraft Attitude Control System

Control moment gyroscopes (CMGs) are a favorable choice for spacecraft attitude control systems thanks to their torque amplification capability. However, their performance is hindered by geometric singularities, which can severely limit control capabilities during attitude maneuvers. This paper proposes a hybrid attitude control system incorporating a single reaction wheel into the standard minimum redundant four-CMG pyramid configuration, providing an additional degree-of-freedom to avoid and escape singularities effectively. A comprehensive mathematical analysis of the system’s Jacobian matrix, using row echelon form, is performed alongside a geometrical analysis of the hybrid configuration’s momentum envelope. These analyses demonstrate the reflection of a reaction wheel inclusion into the system of four CMGs in the improvement of the system’s capacity to avoid/escape singularity. Additionally, an asymptotic control law and an adapted steering law are developed to optimize control performance. The effectiveness of the proposed hybrid system is validated through simulation, which includes a comparative analysis with traditional CMG-only system. The results highlight the superiority of the hybrid system in handling singularities.

Research on Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicle Based on State Estimation.

This paper proposes a hierarchical framework-based solution to address the challenges of vehicle state estimation and lateral stability control in four-wheel independent drive electric vehicles. First, based on a three-degrees-of-freedom four-wheel vehicle model combined with the Magic Formula Tire model (MF-T), a hierarchical estimation method is designed. The upper layer employs the Kalman Filter (KF) and Extended Kalman Filter (EKF) to estimate the vertical load of the wheels, while the lower layer utilizes EKF in conjunction with the upper-layer results to further estimate the lateral forces, longitudinal velocity, and lateral velocity, achieving accurate vehicle state estimation. On this basis, a hierarchical lateral stability control system is developed. The upper controller determines stability requirements based on driver inputs and vehicle states, switches between handling assistance mode and stability control mode, and generates yaw moment and speed control torques transmitted to the lower controller. The lower controller optimally distributes these torques to the four wheels. Through closed-loop Double Lane Change (DLC) tests under low-, medium-, and high-road-adhesion conditions, the results demonstrate that the proposed hierarchical estimation method offers high computational efficiency and superior estimation accuracy. The hierarchical control system significantly enhances vehicle handling and stability under low and medium road adhesion conditions.

Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control

In order to improve the driving stability of distributed-drive intelligent electric vehicles under different roadway attachment conditions, this paper proposes a multi-parameter control algorithm based on the estimation of road adhesion coefficients. First, a seven-degree-of-freedom (7-DOF) vehicle dynamics model is established and optimized with a layered control strategy. The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. A Speedgoat-CarSim hardware-in-the-loop simulation platform was established, and typical driving scenarios were simulated to assess the stability and accuracy of the proposed control algorithm. The results demonstrate that the proposed algorithm significantly enhances vehicle-handling stability across both high- and low-adhesion road conditions.

Development of a direct yaw moment control strategy for an articulated bus equipped with on-board electric motors

Development of a direct yaw moment control strategy for an articulated bus equipped with on-board electric motors

Disturbance Robust Attitude Stabilization of Multirotors with Control Moment Gyros.

This paper presents a novel control framework for enhancing the attitude stabilization of multirotor UAVs using Control Moment Gyros (CMGs) and a Disturbance Robust Drive Law (DRDL). Due to their lightweight and compact structure, multirotor UAVs are highly susceptible to disturbances such as wind, making it challenging to achieve stable attitude control using rotor thrust alone. To address this issue, we employ CMGs to provide robust attitude control and apply Fast Terminal Sliding Mode Control (FTSMC) to ensure fast and accurate convergence within a finite time. The combination of CMGs' torque amplification capability with the DRDL enables the system to effectively avoid singularities and maintain stable control performance in the presence of disturbances. Simulation results demonstrate that the CMG-equipped hexarotor utilizing the DRDL rapidly converges to the target attitude despite external disturbances, while minimizing oscillations in both motor speed and gimbal movement. Additionally, compared to the pseudo-inverse control method, the proposed approach significantly improves singularity avoidance and disturbance mitigation. The proposed control framework enhances the stability and reliability of UAV operations and demonstrates its potential for high-performance control in challenging disturbance environments.

Cooperative Control of Distributed Drive Electric Vehicles for Handling, Stability, and Energy Efficiency, via ARS and DYC

Distributed drive electric vehicles (DDEV), characterized by their independently drivable wheels, offer significant advantages in terms of vehicle handling, stability, and energy efficiency. These attributes collectively contribute to enhancing driving safety and extending the all-electric range for sustainable transportation. Nonetheless, the challenge persists in designing a control strategy that effectively coordinates the objectives of handling, stability, and energy efficiency under both lateral and longitudinal driving conditions. To this end, this paper proposes a cooperative control strategy for DDEVs, incorporating active rear steering (ARS) and direct yaw moment control (DYC) to enhance handling capabilities, stability, and energy efficiency. A stability boundary is delineated using an analytical expression that correlates with the front wheel steering angle, and an adjustment factor is introduced to quantify vehicle stability based on this input parameter. This factor aids in establishing a coordinated control reference for handling and stability. At the upper-level motion control layer, a model predictive control method is developed to track this reference and implement ARS and DYC for superior performance. Specifically, the rear lateral force serves as the control command for ARS, which is converted into a rear wheel steering angle using a tire inverse model. Meanwhile, the front lateral force is modeled as linear-time-varying to simplify calculations. At the lower-level torque allocation layer, the adjustment factor is utilized to balance tire workload rate and in-wheel motors’ (IWM) energy consumption, enabling efficient switching between energy consumption and driving stability targets, and the torque allocation is conducted to acquire the expected IWMs’ command. Both the upper and lower-level optimization problems are formulated as convex problems, ensuring efficient and effective solutions. Simulations verify the effectiveness of this strategy in improving handling, stability, and energy economy under DLC cases, while maintaining high computational efficiency.

Modeling, Control and Guidance of an Autonomous Wheeled Mobile Robot AWMR: A Comparative Study Between Three Yaw Moment Control Techniques for Autopilot Design with Experimental Results

Modeling, Control and Guidance of an Autonomous Wheeled Mobile Robot AWMR: A Comparative Study Between Three Yaw Moment Control Techniques for Autopilot Design with Experimental Results

Lateral stability control for distributed drive autonomous vehicle with extreme path tracking

To enhance the path-tracking accuracy and lateral stability of autonomous vehicles under extreme conditions, this paper proposes a coordinated control strategy based on an Active Front Steering (AFS) system and Direct Yaw Moment Control (DYC). First, a path-tracking controller based on Model Predictive Control (MPC) is designed, which includes a Kalman filter to correct lateral stiffness in real-time and calculates the front wheel steering angle output based on path-tracking errors and current direct yaw moment. Next, we formulated the Direct Yaw Moment Control objective as a linear combination of stability and maneuverability objectives, and used a fuzzy controller to dynamically coordinate the weights of stability and maneuverability objectives. This process not only improves the adaptability of the control strategy but also enhances vehicle performance under various road conditions. Furthermore, a Sliding Mode Control (SMC) is employed to calculate the required direct yaw moment. This approach ensures vehicle stability during high-speed driving or changes in road surface adhesion. To optimize torque distribution, we employed a constrained quadratic programming method to minimize tire load rates, thereby improving vehicle energy efficiency and handling. Finally, through Hardware-in-the-Loop (HIL) testing, we validated that the proposed control strategy achieves excellent tracking accuracy, real-time performance, and lateral stability under different road adhesion conditions and vehicle speeds. The control strategy developed in this study not only exhibits theoretical innovation but also demonstrates significant effectiveness in practical applications, providing valuable insights for path-tracking and lateral dynamic control strategies of autonomous vehicles under extreme conditions.

Integration of in-wheel motor sensorless systems and hierarchical direct yaw moment control for distributed drive electric vehicles

Ensuring robust and reliable control of distributed vehicles powered by in-wheel motor systems poses a significant challenge due to the harsh operating environments and high costs of such motor systems. Poor motor control, parameter variations, and sensor malfunction under these conditions can compromise the vehicle yaw stability. Integrating permanent magnet synchronous motor (PMSM) sensorless systems with vehicle yaw moment control offers a cost-effective solution for this issue without wheel angular speed sensors while enhancing yaw stability. In this paper, a composite nonlinear feedback sliding mode controller that can enhance the PMSM speed response is proposed. The proposed scheme exhibits a rotor speed overshoot and transient time of only 0.64% and 0.07s, respectively, which are smaller and shorter compared with other methods under motor parameter changes. Subsequently, the key states and tire-road friction coefficients required for vehicle control were estimated using sensorless rotor speeds and unscented Kalman filters, enabling the integration of the PMSM sensorless system with the vehicle yaw moment control. Additionally, a fuzzy adaptive hybrid sliding mode method is presented for yaw moment control enhancement. This method maintained the smallest sideslip angle root mean square error during double lane changes (0.4192 deg) compared with other methods. Analysis results show that different motor controllers and parameter changes significantly affect the vehicle dynamics performance. The proposed integrated scheme is feasible and effectively enhances the yaw moment control via high-performance sensorless PMSM systems.

An MPC-DCM Control Method for a Forward-Bending Biped Robot Based on Force and Moment Control

For a forward-bending biped robot with 10 degrees of freedom on its legs, a new control framework of MPC-DCM based on force and moment is proposed in this paper. Specifically, the Diverging Component of Motion (DCM) is a stability criterion for biped robots based on linear inverted pendulum, and Model Predictive Control (MPC) is an optimization solution strategy using rolling optimization. In this paper, DCM theory is applied to the state transition matrix of the system, combined with simplified rigid body dynamics, the mathematical description of the biped robot system is established, the classical MPC method is used to optimize the control input, and DCM constraints are added to the constraints of MPC, making the real-time DCM approximate to a straight line in the walking single gait. At the same time, the linear angle and friction cone constraints are considered to enhance the stability of the robot during walking. In this paper, MATLAB/Simulink is used to simulate the robot. Under the control of this algorithm, the robot can reach a walking speed of 0.75 m/s and has a certain anti-disturbance ability and ground adaptability. In this paper, the Model-H16 robot is used to deploy the physical algorithm, and the linear walking and obstacle walking of the physical robot are realized.

On the problem of optimal control of rotation axis reorientation of a spacecraft

Various variants of the formulation of optimal control problem of the reorientation of the axis of dynamic symmetry of the spacecraft (spacecraft), which is the axis of rotation, are considered. It is assumed that the solution to this problem should be found in the class of movements with one directional (flat) rotation, provided that before and after the reorientation of the axis of rotation, the angular velocity of the spacecraft is the same. In this case, the angular motion of the spacecraft is controlled according to the "rotary jet engine" scheme, when the control moment is limited by the ellipsoid of rotation. The corresponding mathematical model of spacecraft motion for the control problem under consideration is given. In addition to the formulation of the problem of the steepest reorientation of the axis of rotation of the spacecraft, the optimal control problem is also formulated, for which optimal control for the full control moment is found. In order to analyze the formulation of the problem under consideration, the results of its reduction to the boundary value problem and to the isoperimetric variational problem are also presented.

Path tracking with switchable stability constraints for vehicle collision avoidance based on extended stability region

There is a certain conflict between vehicle stability and the performance of path-tracking under emergency conditions. In this paper, to make full use of the lateral capacity of vehicles, a path tracking method with switchable stability constraints is proposed. First, using the Lyapunov energy equation and Hurwitz’s theorem, the lateral stability region (SR) and the critical steering angle of steady steering at different longitudinal speeds are calculated. Based on this, the extended stability region (ESR) and the extended critical steering angle of the vehicle under the control of an additional yaw moment are obtained. Furthermore, the driving area during collision avoidance is divided into unsafe and safe areas, and based on the model predictive control strategy, a path-tracking controller with switchable stability constraints is established. In the unsafe area, the vehicle states are allowed to break through the SR temporarily, and to ensure path-tracking accuracy, the ESR is taken as the stability constraint. In the safe area, the stability constraint is switched to the SR, and to make the vehicle states quickly return to SR, a regain stability controller is established. Finally, a Simulink-CarSim simulation and a hardware-in-the-loop (HIL) experiment are conducted. The simulation results show that a balance between tracking effect and vehicle stability can be effectively achieved through the proposed path-tracking system under the investigated emergency conditions. The real-time performance of the proposed control strategy is validated through the HIL experiment.

Integrated Control of Intelligent Vehicle Driving Stability Using Three-Dimensional Phase Space

<div>To enhance vehicle dynamic stability during driving, we developed a three-dimensional phase space model that incorporates the sideslip angle of center of mass, yaw rate, and lateral load transfer rate. This model enabled real-time evaluation and active control of vehicle stability. First, longitudinal and lateral controllers were implemented to ensure precise vehicle trajectory. Second, a hierarchical control strategy was designed to actively manage the desired sideslip angle, yaw rate, and roll angle based on the vehicle’s destabilizing conditions, thereby maintaining the vehicle within a stable state space. We simulated and tested the stability analysis methods and integrated control strategies for both cars and trucks under DLC (double lane change) and CDC (circular driving condition) scenarios using joint simulations with CarSim/TruckSim and Simulink. The proposed integrated stability control strategy, which combined MPC-based trajectory tracking with direct yaw moment control and active suspension control, enhanced the vehicle’s directional and roll stability. This approach effectively mitigated vehicle instability under extreme conditions. Compared to the MPC lateral tracking control system, the performance of the integrated control system was significantly improved. In the DLC scenario, the maximum values of the sedan’s lateral deviation, sideslip angle, yaw rate, and vehicle roll angle decreased by 22.6%, 33.9%, 5.5%, and 1.2%, respectively. In the CDC scenario, the truck’s lateral acceleration, sideslip angle, yaw rate, and vehicle roll angle decreased by 7.5%, 46.8%, 8.2%, and 80%, respectively. Additionally, open-loop simulation tests were conducted under fishhook steering conditions for both passenger cars and trucks. The results further validated the effectiveness of the integrated control strategy, demonstrating its ability to significantly improve yaw rate and roll response, thereby enhancing overall vehicle stability under challenging driving conditions.</div>

Robust integrated control of autonomous vehicles path following with response performance improvement considering lateral stability

In this paper, a robust integrated control scheme is developed for autonomous vehicles path following considering both yaw stability and roll stability. First, a controller with H∞ and optimal guaranteed cost performances is presented, and the poles of the closed-loop system are configured in a given disk region to improve the state response performance. The controller outputs front and rear wheel angles for path following, as well as an external yaw moment and an external roll moment for lateral stability control. Secondly, the braking forces acted on four wheels are optimally distributed by means of quadratic programing. Besides, the steering angles of the four wheels conform to the Ackermann geometry relation. Finally, the proposed control scheme is verified by CarSim/Simulink co-simulation, the results show that the scheme has better performance on path following accuracy and stability of yaw and roll. Meanwhile, constraining the poles in a given disk region can improve the state response performance of the vehicle during operation.

Polynomial stability of a Rayleigh system with distributed delay

We consider the Rayleigh beam equation with a dynamic control moment with a distributeddelay term in the dynamic control. We establish the strong stability of this system and thenprove that the system with delay has the same rational decay rate as the system without delay.But we show that it is not exponentially stable. Our contribution is the introduction of thedistributed delay term in the control.

Two Adaptive Sliding Mode Control Algorithms for Vehicle Stability Enhancement

This paper discusses two adaptive sliding mode control (ASMC) algorithms for enhancing vehicle stability through direct yaw moment control (DYC). DYC is based on a logic process derived from the understeering and oversteering behavior of a cornering vehicle. Furthermore, to achieve DYC in a four-wheeled passenger vehicle, the reference yaw moment computed by the proposed algorihms is converted into a braking pressure that is to be applied to the four wheels. The objective is to minimize the yaw rate error and constrain the sideslip angle to an acceptable range. According to Lyapunov theory, complete stability analysis guarantees the closed-loop stability and robustness of a control system. Simulation results were used to compare the two ASMC algorithms, and both algorithms showed high performance even under critical operating conditions.