Safety-Aware Longitudinal and Lateral Control of Autonomous Vehicles

Safety is undoubtedly the most critical design requirement regarding autonomous vehicle controllers. This research considers an autonomous vehicle to keep a desired distance from the leader vehicle, as well as stay centered within the lane. To achieve this, the lateral control problem and the combined longitudinal and lateral control problem were studied. Adaptive control laws were proposed with the aid of the backstepping technique and the barrier function technique. Simulation was done to verify the effectiveness of the proposed control laws

Integrating Vehicle Slip and Yaw in Overarching Multi-Tiered Automated Vehicle Steering Control to Balance Path Following Accuracy, Gracefulness, and Safety

Balancing path following accuracy and error convergence with graceful motion in steering control is challenging due to the competing nature of these requirements, especially across a range of operating speeds and conditions. This paper demonstrates that an integrated multi-tiered steering controller considering the impact of slip on kinematic control, dynamic control, and steering actuator rate commands achieves accurate and graceful path following. This work is founded on multi-tiered sideslip and yaw-based models, which allow derivation of controllers considering error due to sideslip and the mapping between steering commands and graceful lateral motion. Observer based sideslip estimates are combined with heading error in the kinematic controller to provide feedforward slip compensation. Path following error is compensated by a continuous Variable Structure Controller (VSC) using speed-based path manifolds to balance graceful motion and error convergence. Resulting yaw rate commands are used by a backstepping dynamic controller to generate steering rate commands. A High Gain Observer (HGO) estimates sideslip and yaw rate for output feedback control. Stability analysis of the output feedback controller is provided, and peaking is resolved. The work focuses on lateral control alone so that the steering controller can be combined with other speed controllers. Field results provide comparisons to related approaches demonstrating gracefulness and accuracy in different complex scenarios with varied weather conditions and perturbations

Modeling and Robust Attitude Controller Design for a Small Size Helicopter

This paper addresses the design and application controller for a small-size unmanned aerial vehicle (UAV). In this work, the main objective is to study the modeling and attitude controller design for a small size helicopter. Based on a non-simplified helicopter model, a new robust attitude control law, which is combined with a nonlinear control method and a model-free method, is proposed in this paper. Both wind gust and ground effect phenomena conditions are involved in this experiment and the result on a real helicopter platform demonstrates the effectiveness of the proposed control algorithm and robustness of its resultant controller.Comment: 6 page

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Adaptive and Optimal Motion Control of Multi-UAV Systems

This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed

Lateral guidance of all-wheel steered multiple-articulated vehicles

Nowadays, roads are becoming more and more congested, resulting in increasing economic losses due to delays. One way to solve this problem is to persuade people use public transp ortation more frequently. To achieve this, public transportation has to be improved. One way to improve public transportation is to construct a new kind of vehicle that combines the advantages of both commuter busses and railroad vehicles. Such a vehicle could be an all-wheel steered multiple-articulated vehicle. In the city of Eindhoven in The Netherlands, a new kind of transportation system will be operational in the year 2003, which is based on such vehicles. To achieve a track following behaviour similar to railroad vehicles, these vehicles have to be equipped with a lateral guidance system for steering them along a prede¯ne d path. This thesis deals with the design of such a guidance system. To achieve good tracking performance, the guidance system has to be modelbased. Therefore, a dynamic vehicle model has been derived. This model describes the nonlinear planar dynamics of an all-wheel steered n-carriage multiple-articulated vehicle. To validate this model, its frequency responses have been compared with the frequency responses of a 125 degrees of freedom multi-body model. This comparison shows good performance between both models. In order to show that a dynamic vehicle model is required, a comparison has been made between the dynamic vehicle model and a model describing only the kinematics of the vehicle. The position of the vehicle with respect to the path to be followed is crucial for proper control and therefore a measurement method based on the utilization of rotation symmetric bar magnets is presented. These magnets are buried in the road. By utilizing the rotation symmetry, the position to the magnet can be determined independently of the measurement height and the strength of the magnet. One requirement is that two ¯eld components are measured. It is shown that the sensitivity of this method to slant of the magnet and/or vehicle can be reduced by using a second dual-axes ¯eld sensor instead of one. Validation measurements show that the distance to the magnet can be determined with about 2 cm accuracy with 90 slant of the magnet. The permanent magnets yield position information exclusively and only at discrete instances. For controller design, knowledge of the complete state of the vehicle is desirable. An extended Kalman ¯lter has been designed to obtain continuous estimates of this state. To keep the in°uence of varying vehicle parameters small, accelerometers are used as input of the Kalman ¯lter. The accelerometer o®sets, road banking angle and vehicle roll angle are estimated online, to reduce the e®ect of these parameters. The position information obtained from the permanent magnets is used to apply corrections to state predictions that are based on the accelerometer outputs. The discrete and asynchronous character of this position information has been dealt with by implementing the Kalman ¯lter in a multi-rate fashion. Articulation angle sensors, wheel encoders and rate gyros are added to the Kalman ¯lter to improve the performance and to obtain redundan cy of sensors. The vehicles that will be used in the public transportation system in Eindhoven have, apart from all-wheel steering, also independent electrical drives on each of the wheels, except the two wheels at the front. This independent drive can in principle also be used for steering the vehicle, by using the drives on one axle in a di®erential way. A singular value analysis shows that steering with normal steering angles is much more in°uential than using these di®erential torques. It has also been analyzed that both at low and high speed all-wheel steering is bene¯cial to reduce o®-tracking of the rear axles and to improve the yaw dynamics of the vehicle. Two di®erent controllers have been designed for steering the vehicle, based on the outputs of the Kalman ¯lter, along the path to be followed. The ¯rst of these controllers is a feedback linearizing controller. This controller can be considered to consist of two control loops. The inner loop linearizes the planar vehicle dynamics, under the assumption that the steering system dynamics can be neglected. The outer control loop is used to counteract parameter uncertainty and disturbances. For this outer loop, a PID controller has been used. The second controller is a so-called backsteppin g controller. With this controller, also the steering actuator dynamics are taken into account. To simulate the behavior of the lateral guidance system, a more complex vehicle model has been used. This model describes besides the planar vehicle dynamics also the dynamics of the susp ension system. A nonlinear tire model has been used in this model. Simulations with this 3D simulation model show good tracking performance for both the feedback linearizing controller and the backstepping controller. The backstepping controller shows improved tracking performance compared to the feedback linearizing controller. However, this goes at the cost of increased high frequent behavior or the lateral acceleration

Lateral guidance of all-wheel steered multiple-articulated vehicles

Nowadays, roads are becoming more and more congested, resulting in increasing economic losses due to delays. One way to solve this problem is to persuade people use public transp ortation more frequently. To achieve this, public transportation has to be improved. One way to improve public transportation is to construct a new kind of vehicle that combines the advantages of both commuter busses and railroad vehicles. Such a vehicle could be an all-wheel steered multiple-articulated vehicle. In the city of Eindhoven in The Netherlands, a new kind of transportation system will be operational in the year 2003, which is based on such vehicles. To achieve a track following behaviour similar to railroad vehicles, these vehicles have to be equipped with a lateral guidance system for steering them along a prede¯ne d path. This thesis deals with the design of such a guidance system. To achieve good tracking performance, the guidance system has to be modelbased. Therefore, a dynamic vehicle model has been derived. This model describes the nonlinear planar dynamics of an all-wheel steered n-carriage multiple-articulated vehicle. To validate this model, its frequency responses have been compared with the frequency responses of a 125 degrees of freedom multi-body model. This comparison shows good performance between both models. In order to show that a dynamic vehicle model is required, a comparison has been made between the dynamic vehicle model and a model describing only the kinematics of the vehicle. The position of the vehicle with respect to the path to be followed is crucial for proper control and therefore a measurement method based on the utilization of rotation symmetric bar magnets is presented. These magnets are buried in the road. By utilizing the rotation symmetry, the position to the magnet can be determined independently of the measurement height and the strength of the magnet. One requirement is that two ¯eld components are measured. It is shown that the sensitivity of this method to slant of the magnet and/or vehicle can be reduced by using a second dual-axes ¯eld sensor instead of one. Validation measurements show that the distance to the magnet can be determined with about 2 cm accuracy with 90 slant of the magnet. The permanent magnets yield position information exclusively and only at discrete instances. For controller design, knowledge of the complete state of the vehicle is desirable. An extended Kalman ¯lter has been designed to obtain continuous estimates of this state. To keep the in°uence of varying vehicle parameters small, accelerometers are used as input of the Kalman ¯lter. The accelerometer o®sets, road banking angle and vehicle roll angle are estimated online, to reduce the e®ect of these parameters. The position information obtained from the permanent magnets is used to apply corrections to state predictions that are based on the accelerometer outputs. The discrete and asynchronous character of this position information has been dealt with by implementing the Kalman ¯lter in a multi-rate fashion. Articulation angle sensors, wheel encoders and rate gyros are added to the Kalman ¯lter to improve the performance and to obtain redundan cy of sensors. The vehicles that will be used in the public transportation system in Eindhoven have, apart from all-wheel steering, also independent electrical drives on each of the wheels, except the two wheels at the front. This independent drive can in principle also be used for steering the vehicle, by using the drives on one axle in a di®erential way. A singular value analysis shows that steering with normal steering angles is much more in°uential than using these di®erential torques. It has also been analyzed that both at low and high speed all-wheel steering is bene¯cial to reduce o®-tracking of the rear axles and to improve the yaw dynamics of the vehicle. Two di®erent controllers have been designed for steering the vehicle, based on the outputs of the Kalman ¯lter, along the path to be followed. The ¯rst of these controllers is a feedback linearizing controller. This controller can be considered to consist of two control loops. The inner loop linearizes the planar vehicle dynamics, under the assumption that the steering system dynamics can be neglected. The outer control loop is used to counteract parameter uncertainty and disturbances. For this outer loop, a PID controller has been used. The second controller is a so-called backsteppin g controller. With this controller, also the steering actuator dynamics are taken into account. To simulate the behavior of the lateral guidance system, a more complex vehicle model has been used. This model describes besides the planar vehicle dynamics also the dynamics of the susp ension system. A nonlinear tire model has been used in this model. Simulations with this 3D simulation model show good tracking performance for both the feedback linearizing controller and the backstepping controller. The backstepping controller shows improved tracking performance compared to the feedback linearizing controller. However, this goes at the cost of increased high frequent behavior or the lateral acceleration