Optimization-based Control Allocation Research Articles

Optimization-Based Control for a Large-Scale Electrical Vertical Take-Off and Landing during an Aircraft’s Vertical Take-Off and Landing Phase with Variable-Pitch Propellers

The UAV industry has witnessed an unprecedented boom in recent years. Among various kinds of UAV platforms, the vertical take-off and landing (VTOL) aircraft with fixed-wing configurations has received more and more attention due to its flexibility and long-distance flying abilities. However, due to the fact that the advance ratio of regular propeller systems during the cruise phase is significantly higher than that during the VTOL phase, a variable-pitch propeller system is proposed and designed which can be applied without additional propulsion mechanisms during both flying stages. Thus, a VTOL aircraft platform is proposed based on the propulsion system constructed of variable-pitch propellers, and appropriate control manners are precisely analyzed, especially during its VTOL phase. As a basic propulsion system, a nonlinear model for variable-pitch propellers is constructed, and an optimization-based control allocation module is developed because of its multi-solution and high-order characteristics. Finally, the objective function is designed according to the stability and energy consumption requirements. Simulation experiments demonstrate that the proposed controller is able to lower energy consumption and maintain the stability of the aircraft while tracking aggressive trajectories for large-scale VTOLs with noises at the same time.

Path-Tracking Considering Yaw Stability With Passivity-Based Control for Autonomous Vehicles

In this paper, a new passivity-based control approach is designed to improve the robustness and stability of autonomous vehicles in performing path-tracking tasks. A port-Hamiltonian model is a special geometric structure and provides a systematic and insightful framework to describe many physical systems from an energy perspective. The passivity-based control establishes a new and simple structure to achieve the path-tracking task by the port-Hamiltonian structure. Firstly, the path-tracking error system is transformed into a port-Hamiltonian system with the perturbation. The energy-shaping method is utilized to ensure the asymptotic stability, and the stability proof of the closed-loop, path-tracking error system is given. The proposed real-time, passivity-based controller is directly dependent on the passive outputs, which is robust to parameter uncertainties caused by load changes. Moreover, the control performance of steering control will be degraded when the steering angle is saturated. The yaw-moment control is introduced to enhance the driving safety. In the wheel torque distribution, an optimization-based control allocation is designed to minimize the sum of tire loads and to make them more evenly distributed to each tire. Finally, simulations are implemented in MATLAB/Simulink and CarSim co-simulation to demonstrate the effectiveness of the designed strategy under different driving conditions.

Integrated Chassis Control and Control Allocation for All Wheel Drive Electric Cars with Rear Wheel Steering

This study investigates a control strategy for torque vectoring (TV) and active rear wheel steering (RWS) using feedforward and feedback control schemes for different circumstances. A comprehensive vehicle and combined slip tire model are used to determine the secondary effect and to generate desired yaw acceleration and side slip angle rate. A model-based feedforward controller is designed to improve handling but not to track an ideal response. A feedback controller based on close loop observation is used to ensure its cornering stability. The fusion of two controllers is used to stabilize a vehicle’s lateral motion. To increase lateral performance, an optimization-based control allocation distributes the wheel torques according to the remaining tire force potential. The simulation results show that a vehicle with the proposed controller exhibits more responsive lateral dynamic behavior and greater maximum lateral acceleration. The cornering safety is also demonstrated using a standard stability test. The driving performance and stability are improved simultaneously by the proposed control strategy and the optimal control allocation scheme.

Dual-layer optimization-based control allocation for a fixed-wing UAV

Many existing control allocation methods separate the high-level control design from their low-level allocation design, assuming that the constraints of actuators can be guaranteed by the allocator. This idea may not be suitable for the nonlinear fixed-wing unmanned aerial vehicle studied here, which hence motivates this work. In this paper, we propose a new dual-layer optimization-based control allocation method, in which the proposed allocator, on the one hand, can modify the pre-designed virtual signals from the high-level when the out-layer actuator, i.e., throttle, reaches its constraint. On the other hand, it reverts the conventional constrained allocator when the throttle constraints are inactive. Another feature is that under the proposed framework, the initial state of the augmented actuator dynamics serves as design parameters, bringing more degrees of freedom for allocation design without affecting the nominal stability. Apart from the control allocator, this paper also proposes a high-level flight controller based on the control-oriented model and a combination of nonlinear dynamic inversion and disturbance observer. Disturbance observer provides robustness by estimating the model errors between the control-oriented and true models, and compensating for them in the controller. High-fidelity simulation results under realistic wind disturbances are presented to demonstrate the performance of the proposed method.

Adaptive Robust Vehicle Motion Control for Future Over-Actuated Vehicles

Many challenges still need to be overcome in the context of autonomous vehicles. These vehicles would be over-actuated and are expected to perform coupled maneuvers. In this paper, we first discuss the development of a global coupled vehicle model, and then we outline the control strategy that we believe should be applied in the context of over-actuated vehicles. A gain-scheduled H ∞ controller and an optimization-based Control Allocation algorithms are proposed. High-fidelity co-simulation results show the efficiency of the proposed control logic and the new possibilities that could offer. We expect that both car manufacturers and equipment suppliers would join forces to develop and standardize the proposed control architecture for future passenger cars.

An Integrated Control of Differential Braking, Front/Rear Traction, and Active Roll Moment for Limit Handling Performance

This paper describes an integrated chassis control (ICC) algorithm of differential braking, front/rear traction torque, and active roll moment control. The integrated control algorithm is designed to maximize driving velocity and enhance vehicle lateral stability in cornering. The target longitudinal acceleration is determined based on the driver's intention and vehicle current status to ensure vehicle lateral stability in high-speed maneuvering. An optimization-based control allocation strategy is used to distribute the actuator control inputs optimally under consideration of tire and vehicle limitations. Closed-loop simulations of a driver-vehicle-controller system were conducted to investigate the performance of the proposed control algorithm. The performance of the ICC has been compared with those of individual chassis control systems, such as electronic stability control, four-wheel drive (4WD), and active roll control system. The simulation results show that the proposed ICC algorithm improves the performance in high-speed cornering with respect to driving speed without losing stability, compared with individual chassis control systems.

Integrated chassis control for optimized tyre force coordination to enhance the limit handling performance

This paper proposes a coordinated control algorithm of the differential braking, the front and rear traction torques and the active roll moment to enhance the limit-handling performance. The coordinated algorithm is designed to maximize the driving velocity while keeping the vehicle in a lane. First, the analysis of the cornering dynamics is described to consider the non-linear characteristics of the tyres during acceleration or deceleration. The target vehicle motions are determined on the basis of the driver’s intention and the current states of the vehicle. An optimization-based control allocation strategy is utilized to distribute the actuator control inputs optimally by considering the tyre and vehicle limitations. Closed-loop simulations of a driver–vehicle–controller system were conducted to investigate the performance of the proposed control algorithm. The performance of the coordinated algorithm was compared with those of the individual coordination algorithms. The simulation results show that the proposed integrated chassis controller improves the performance in high-speed cornering with respect to the driving speed without losing stability compared with simple coordination chassis control systems.

Vehicle motion control with subsystem prioritization

This paper presents a new approach for integrated vehicle motion control, coordinating multiple vehicle subsystems of a passenger car including friction brake system, near-wheel drive electric motors, wheel steer actuators, camber angle actuators, dynamic tire pressure system and actuators generating additional normal forces. The proposed algorithms are based on restriction weights into the cost function of optimization-based control allocation. Hardware-in-the-loop investigation using a test rig with hardware components of friction brake system and dynamic tire pressure system showed that the proposed approach allows to achieve lower energy consumption and energy losses without significant impairment of motion stability and vehicle handling as compared to conventional control allocation.

Wheel Torque Distribution Criteria for Electric Vehicles With Torque-Vectoring Differentials

The continuous and precise modulation of the driving and braking torques of each wheel is considered the ultimate goal for controlling the performance of a vehicle in steady-state and transient conditions. To do so, dedicated torque-vectoring (TV) controllers that allow optimal wheel torque distribution under all possible driving conditions have to be developed. Commonly, vehicle TV controllers are based on a hierarchical approach, consisting of a high-level supervisory controller that evaluates a corrective yaw moment and a low-level controller that defines the individual wheel torque reference values. The problem of the optimal individual wheel torque distribution for a particular driving condition can be solved through an optimization-based control-allocation (CA) algorithm, which must rely on the appropriate selection of the objective function. With a newly developed offline optimization procedure, this paper assesses the performance of alternative objective functions for the optimal wheel torque distribution of a four-wheel-drive (4WD) fully electric vehicle. Results show that objective functions based on the minimum tire slip criterion provide better control performance than functions based on energy efficiency.

Driving Control Algorithm for Maneuverability, Lateral Stability, and Rollover Prevention of 4WD Electric Vehicles With Independently Driven Front and Rear Wheels

This paper describes a driving control algorithm for four-wheel-drive (4WD) electric vehicles equipped with two motors at front and rear driving shafts to improve vehicle maneuverability, lateral stability, and rollover prevention. The driving control algorithm consists of the following three parts: 1) a supervisory controller that determines the control mode, the admissible control region, and the desired dynamics, such as the desired speed and yaw rate; 2) an upper level controller that computes the traction force input and the yaw moment input to track the desired dynamics; and 3) a lower level controller that determines actual actuator commands, such as the front/rear driving motor torques and independent brake torques. The supervisory controller computes the admissible control region, namely, the relationship between the vehicle speed and the maximum curvature of the vehicle considering the maximum steering angle, lateral stability, and rollover prevention. In the lower level controller, a wheel slip controller is designed to keep the slip ratio at each wheel below a limit value. In addition, an optimization-based control allocation strategy is used to map the upper level and wheel slip control inputs to actual actuator commands, taking into account the actuator constraints. Numerical simulation studies have been conducted to evaluate the proposed driving control algorithm. It has been shown from simulation studies that vehicle maneuverability, lateral stability, and rollover mitigation performance can be significantly improved by the proposed driving controller.