Advanced Feedback Linearization Control for Tiltrotor UAVs: Gait Plan, Controller Design, and Stability Analysis

Three challenges, however, can hinder the application of Feedback Linearization: over-intensive control signals, singular decoupling matrix, and saturation. Activating any of these three issues can challenge the stability proof. To solve these three challenges, first, this research proposed the drone gait plan. The gait plan was initially used to figure out the control problems in quadruped (four-legged) robots; applying this approach, accompanied by Feedback Linearization, the quality of the control signals was enhanced. Then, we proposed the concept of unacceptable attitude curves, which are not allowed for the tiltrotor to travel to. The Two Color Map Theorem was subsequently established to enlarge the supported attitude for the tiltrotor. These theories were employed in the tiltrotor tracking problem with different references. Notable improvements in the control signals were witnessed in the tiltrotor simulator. Finally, we explored the control theory, the stability proof of the novel mobile robot (tilt vehicle) stabilized by Feedback Linearization with saturation. Instead of adopting the tiltrotor model, which is over-complicated, we designed a conceptual mobile robot (tilt-car) to analyze the stability proof. The stability proof (stable in the sense of Lyapunov) was found for a mobile robot (tilt vehicle) controlled by Feedback Linearization with saturation for the first time. The success tracking result with the promising control signals in the tiltrotor simulator demonstrates the advances of our control method. Also, the Lyapunov candidate and the tracking result in the mobile robot (tilt-car) simulator confirm our deductions of the stability proof. These results reveal that these three challenges in Feedback Linearization are solved, to some extents.Comment: Doctoral Thesis at The University of Toky

An Omnidirectional Aerial Platform for Multi-Robot Manipulation

The objectives of this work were the modeling, control and prototyping of a new fully-actuated aerial platform. Commonly, the multirotor aerial platforms are under-actuated vehicles, since the total propellers thrust can not be directed in every direction without inferring a vehicle body rotation. The most common fully-actuated aerial platforms have tilted or tilting rotors that amplify the aerodynamic perturbations between the propellers, reducing the efficiency and the provided thrust. In order to overcome this limitation a novel platform, the ODQuad (OmniDirectional Quadrotor), has been proposed, which is composed by three main parts, the platform, the mobile and rotor frames, that are linked by means of two rotational joints, namely the roll and pitch joints. The ODQuad is able to orient the total thrust by moving only the propellers frame by means of the roll and pitch joints. Kinematic and dynamic models of the proposed multirotor have been derived using the Euler- Lagrange approach and a model-based controller has been designed. The latter is based on two control loops: an outer loop for vehicle position control and an inner one for vehicle orientation and roll-pitch joint control. The effectiveness of the controller has been tested by means of numerical simulations in the MATLAB c SimMechanics environment. In particular, tests in free motion and in object transportation tasks have been carried out. In the transportation task simulation, a momentum based observer is used to estimate the wrenches exchanged between the vehicle and the transported object. The ODQuad concept has been tested also in cooperative manipulation tasks. To this aim, a simulation model was considered, in which multiple ODQuads perform the manipulation of a bulky object with unknown inertial parameters which are identified in the first phase of the simulation. In order to reduce the mechanical stresses due to the manipulation and enhance the system robustness to the environment interactions, two admittance filters have been implemented: an external filter on the object motion and an internal one local for each multirotor. Finally, the prototyping process has been illustrated step by step. In particular, three CAD models have been designed. The ODQuad.01 has been used in the simulations and in a preliminary static analysis that investigated the torque values for a rough sizing of the roll-pitch joint actuators. Since in the ODQuad.01 the components specifications and the related manufacturing techniques have not been taken into account, a successive model, the ODQuad.02, has been designed. The ODQuad.02 design can be developed with aluminum or carbon fiber profiles and 3D printed parts, but each component must be custom manufactured. Finally, in order to shorten the prototype development time, the ODQuad.03 has been created, which includes some components of the off-the-shelf quadrotor Holybro X500 into a novel custom-built mechanical frame

On Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoring

A recently growing literature discusses the topics of direct yaw moment control based on model predictive control (MPC), and energy-efficient torque-vectoring (TV) for electric vehicles with multiple powertrains. To reduce energy consumption, the available TV studies focus on the control allocation layer, which calculates the individual wheel torque levels to generate the total reference longitudinal force and direct yaw moment, specified by higher level algorithms to provide the desired longitudinal and lateral vehicle dynamics. In fact, with a system of redundant actuators, the vehicle-level objectives can be achieved by distributing the individual control actions to minimize an optimality criterion, e.g., based on the reduction of different power loss contributions. However, preliminary simulation and experimental studies – not using MPC – show that further important energy savings are possible through the appropriate design of the reference yaw rate. This paper presents a nonlinear model predictive control (NMPC) implementation for energy-efficient TV, which is based on the concurrent optimization of the reference yaw rate and wheel torque allocation. The NMPC cost function weights are varied through a fuzzy logic algorithm to adaptively prioritize vehicle dynamics or energy efficiency, depending on the driving conditions. The results show that the adaptive NMPC configuration allows stable cornering performance with lower energy consumption than a benchmarking fuzzy logic TV controller using an energy-efficient control allocation layer

Experimental Study of Aerodynamic Disturbance Rejection On Multirotor Unmanned Aerial Vehicles

PID (Proportional-Integral-Derivative) controllers are the most widely used control algorithms in different industrial applications. Multirotor Unmanned Aerial Vehicles (UAVs) are not an exception in this regard. This success is due to the efficiency of this type of algorithms. In fact, they are easy to understand, to tune and to implement. Added to that, PID controllers perform surprisingly well in most operational cases, even when those start to become challenging. But this effectiveness becomes questionable when the conditions are far fro

Optimal torque vectoring control strategies for stabilisation of electric vehicles at the limits of handling

The study of chassis control has been a major research area in the automotive industry and academia for more than fifty years now. Among the popular methods used to actively control the dynamics of a vehicle, torque vectoring, the method of controlling both the direction and the magnitude of the torque on the wheels, is of particular interest. Such a method can alter the vehicle’s behaviour in a positive way under both sub-limit and limit handling conditions and has become even more relevant in the case of an electric vehicle equipped with multiple electric motors. Torque vectoring has been so far employed mainly in lateral vehicle dynamics control applications, with the longitudinal dynamics of the vehicle remaining under the full authority of the driver. Nevertheless, it has been also recognised that active control of the longitudinal dynamics of the vehicle can improve vehicle stability in limit handling situations. A characteristic example of this is the case where the driver misjudges the entry speed into a corner and the vehicle starts to deviate from its path, a situation commonly referred to as a ‘terminal understeer’ condition. Use of combined longitudinal and lateral control in such scenarios have been already proposed in the literature, but these solutions are mainly based on heuristic approaches that also neglect the strong coupling of longitudinal and lateral dynamics in limit handling situations. The main aim of this project is to develop a real-time implementable multivariable control strategy to stabilise the vehicle at the limits of handling in an optimal way using torque vectoring via the two independently controlled electric motors on the rear axle of an electric vehicle. To this end, after reviewing the most important contributions in the control of lateral and/or longitudinal vehicle dynamics with a particular focus on the limit handling solutions, a realistic vehicle reference behaviour near the limit of lateral acceleration is derived. An unconstrained optimal control strategy is then developed for terminal understeer mitigation. The importance of constraining both the vehicle state and the control inputs when the vehicle operates at the limits of handling is shown by developing a constrained linear optimal control framework, while the effect of using a constrained nonlinear optimal control framework instead is subsequently examined next. Finally an optimal estimation strategy for providing the necessary vehicle state information to the proposed optimal control strategies is constructed, assuming that only common vehicle sensors are available. All the developed optimal control strategies are assessed not only in terms of performance but also execution time, so to make sure they are implementable in real time on a typical Electronic Control Unit

Force-Canceling Mixer Algorithm for Vehicles with Fully-Articulated Radially Symmetric Thruster Arrays

A new type of fully-holonomic aerial vehicle is identified and developed that can optionally utilize automatic cancellation of excessive thruster forces to maintain precise control despite little or no throttle authority. After defining the physical attributes of the new vehicle, a flight control mixer algorithm is defined and presented. This mixer is an input/output abstraction that grants a flight control system (or pilot) full authority of the vehicle\u27s position and orientation by means of an input translation vector and input torque vector. The mixer is shown to be general with respect to the number of thrusters in the system provided that they are distributed in a radially symmetric array. As the mixer is designed to operate independently of the chosen flight control system, it is completely agnostic to the type of control methodology implemented. Validation of both the vehicle\u27s holonomic capabilities and efficacy of the flight control mixing algorithm are provided by a custom MATLAB-based rigid body simulation environment

Optimal handling characteristics for electric vehicles with torque vectoring.

Torque vectoring by virtue of independent electric motors is the focus of an increasing number of studies as electric vehicles gain prominence as the chosen direction for the automotive industry. Building on active yaw control systems developed over the past decades, torque vectoring benefits from the high-responsiveness and controllability of the electric motor actuator. Furthermore, and especially in the case of vehicles equipped with one independent motor per wheel, the overall performance envelope of the vehicle is significantly improved, as well as the ability to actively shape the vehicle handling. Much attention has been focussed on controller development and control allocation aspects of torque vectoring controllers, but little on the appropriate yaw rate reference. Optimal control studies have been successfully used to mimic the expert driver in both minimum-time circuit racing and high-sideslip rally driving, and can offer insight into how to optimally tune active chassis control systems, such as torque vectoring yaw control. The main aim of this thesis was to investigate the optimal handling characteristics of an electric vehicle with four independent electric motors at the limits of performance. A TV controller was first developed for a prototype sportscar with 4 independent motors, employing a model-based design process that encompassed real-time software in the loop testing. Real-world track testing demonstrated the controller was able to successfully modify the handling characteristic of the vehicle in both understeer and oversteer directions, achieving good controller performance in steady-state and transient manoeuvres. The limit performance of the TV-controlled vehicle was subsequently investigated in the simulation domain. Numerical techniques were used to solve optimal control problems for a single-track vehicle model with linear tyres and an external yaw moment term representing the overall yaw moment arising from the difference in torques at each wheel. For a U-turn manoeuvre, it was shown that torque vectoring significantly lowers manoeuvre time in comparison with the vehicle without TV active, and that modifying the passive understeer gradient does not affect manoeuvre time. The system dynamics were reformulated to include a feedback torque vectoring controller. The target yaw rate reference was varied and it was found that the manoeuvre time was highly sensitive to the yaw rate reference. For minimising laptime, the target understeer gradient should be set to the passive understeer gradient value. The methodology was repeated for a higher fidelity model including nonlinear tyres and lateral load transfer, and found that when the torque vectoring controller was included in the system dynamics, the manoeuvre time showed little sensitivity to the target understeer gradient. Following the contradictory results of the optimal control problems, the vehicle models were investigated next. Time optimal yaw rate gain surfaces were generated from further minimum-time optimal control problems. Open-loop manoeuvres investigating effects of tyre model, lateral load transfer and torque vectoring generation mechanism found that tyre modelling was the dominant differentiator and tyre nonlinearity is an essential modelling consideration. Optimal control techniques have been used for high sideslip manoeuvring for conventional vehicles but no studies have explored the effects of torque vectoring on agility. In the final chapter, an aggressive turn-around manoeuvre was simulated and it was found that torque vectoring can significantly increase agility and reduce the space taken for an aggressive turn-around manoeuvre. Reducing yaw inertia increased agility, as well as increasing longitudinal slips limits. A critique of agility metrics in this context was given.PhD in Transport System