Robustness Analysis with Respect to Exogenous Perturbations for Flatness-Based Exact Feedforward Linearization

A methodology to analyze robustness with respect to exogenous perturbations for exact feedforward linearization based on differential flatness is presented. The analysis takes into consideration the tracking error equation and makes thereafter use of a stability result by Kelemen coupled with results issued from interval analysis. This turns exact feedforward linearization based on differential flatness into a general control methodology for flat systems

Accurate Tracking of Aggressive Quadrotor Trajectories using Incremental Nonlinear Dynamic Inversion and Differential Flatness

Autonomous unmanned aerial vehicles (UAVs) that can execute aggressive (i.e., high-speed and high-acceleration) maneuvers have attracted significant attention in the past few years. This paper focuses on accurate tracking of aggressive quadcopter trajectories. We propose a novel control law for tracking of position and yaw angle and their derivatives of up to fourth order, specifically, velocity, acceleration, jerk, and snap along with yaw rate and yaw acceleration. Jerk and snap are tracked using feedforward inputs for angular rate and angular acceleration based on the differential flatness of the quadcopter dynamics. Snap tracking requires direct control of body torque, which we achieve using closed-loop motor speed control based on measurements from optical encoders attached to the motors. The controller utilizes incremental nonlinear dynamic inversion (INDI) for robust tracking of linear and angular accelerations despite external disturbances, such as aerodynamic drag forces. Hence, prior modeling of aerodynamic effects is not required. We rigorously analyze the proposed control law through response analysis, and we demonstrate it in experiments. The controller enables a quadcopter UAV to track complex 3D trajectories, reaching speeds up to 12.9 m/s and accelerations up to 2.1g, while keeping the root-mean-square tracking error down to 6.6 cm, in a flight volume that is roughly 18 m by 7 m and 3 m tall. We also demonstrate the robustness of the controller by attaching a drag plate to the UAV in flight tests and by pulling on the UAV with a rope during hover.Comment: To be published in IEEE Transactions on Control Systems Technology. Revision: new set of experiments at increased speed (up to 12.9 m/s), updated controller design using quaternion representation, new video available at https://youtu.be/K15lNBAKDC

A Proof of Stability of Model-Free Control

International audienceCybernetics involves Control Theory and Control Practice. From its roots, Cybernetics has always been intimately to Control. The paper is devoted to the proof of an important theorem for the development of control: the closed loop stability of control laws that are calculated in the framework of model-free control. Everyone knows the importance of control in the field of Cybernetics [1]

Experiment-based Comparative Analysis of Nonlinear Speed Control Methods for Induction Motors

Field-oriented control (FOC) for induction motors is widely used in industrial applications. By using a fast and accurate torque controller based on a stator current controller it is possible to flexibly implement advanced speed control methods to achieve proper performance both in transient and steady-state states. In this study, a deadbeat controller was used for the current loop. The nonlinear methods used for the outer loop controller were backstepping, flatness-based control, and exact feedback linearization with state derivative. The dynamic responses of these three controls were compared through various experimental results. The advantages and disadvantages of the different control structures were analyzed and evaluated in detail. Based on this evaluation, an appropriate scheme can be specified when deployed in practice

Experimental comparison of classical pid and model-free control: position control of a shape memory alloy active spring

WOSInternational audienceShape memory alloys (sma) are more and more integrated in engineering applications. These materials with their shape memory effect permit to simplify mechanisms and to reduce the size of actuators. sma parts can easily be activated by Joule effect but their modelling and consequently their control remains difficult, it is principally due to their hysteretic thermomechanical behaviour. Most of successful control strategy applied to sma actuator are not often suitable for industrial applications: they are particularly heavy and use the Preisach model or neural networks to model the hysteretic behaviour of these material; this kind of models are difficult to identify and to use in real time. That is why this paper deals with an application of the new framework of model-free control (mfc) to a sma spring based actuator. This control strategy is based on new results on fast derivatives estimation of noisy sig- nals, its main advantages are: its simplicity and its robustness. Experimental results and comparisons with pi control are exposed that demonstrate the efficiency of this new control strategy. Key words: Nonlinear control, Model-free control, Shape memory alloy, Derivative estimation, Nonphysical modelling