Reinforcement Learning to Control Lift Coefficient Using Distributed Sensors on a Wind Tunnel Model

Arrays of sensors distributed on the wing of fixed-wing vehicles can provide information not directly available to conventional sensor suites. These arrays of sensors have the potential to improve flight control and overall flight performance of small fixed-wing uninhabited aerial vehicles (UAVs). This work investigated the feasibility of estimating and controlling aerodynamic coefficients using the experimental readings of distributed pressure and strain sensors across a wing. The study was performed on a one degree-of-freedom model about pitch of a fixed-wing platform instrumented with the distributed sensing system. A series of reinforcement learning (RL) agents were trained in simulation for lift coefficient control, then validated in wind tunnel experiments. The performance of RL-based controllers with different sets of inputs in the observation space were compared with each other and with that of a manually tuned PID controller. Results showed that hybrid RL agents that used both distributed sensing data and conventional sensors performed best across the different tests.</p

MIMO nonlinear PID predictive controller

A class of nonlinear generalised predictive controllers (NGPC) is derived for multi-input multi-output (MIMO) nonlinear systems with offset or steady-state response error. The MIMO composite controller consists of an optimal NGPC and a nonlinear disturbance observer. The design of the nonlinear disturbance observer to estimate the offset is particularly simple, as is the associated proof of overall nonlinear closed-loop system stability. Moreover, the transient error response of the disturbance observer can be arbitrarily specified by simple design parameters. Very satisfactory performance of the proposed MIMO nonlinear predictive controller is demonstrated for a three-link nonlinear robotic manipulator example

Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model\u27s parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov\u27s stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously

Tracking Control of Quadrotors

In this thesis, the tracking control problem of a 6 DOF quadrotor is considered, and different control method is proposed considering optimal control, parametric and nonparametric uncertainty, input saturation, and distributed formation control. An optimal control approach is developed for single quadrotor tracking by minimizing the cost function. For uncertainties of the dynamic system, a robust adaptive tracking controller is proposed with the special structure of the dynamics of the system. Considering the uncertainty and input constraints, a robust adaptive saturation controller is proposed with the aid of an auxiliary compensated system. Decentralized formation control method for quadrotors is presented using a leader-follower scheme using proposed optimal control method. Virtual leader is employed to drive the quadrotors to their desired formation and ultimately track the trajectory defined by the virtual leader. Sliding mode estimators have been implemented to estimate the states of the virtual leader. The control method is designed considering switching communication topologies among the quadrotors. Simulation results are provided to show the effectiveness of the proposed approaches

Aggressive maneuver oriented robust actuator fault estimation of a 3-DOF helicopter prototype considering measurement noises

This paper presents a robust actuator fault estimation strategy design for a 3-DOF helicopter prototype which can be adapted to aggressive maneuvers. First, considering large pitch angle condition during flight, nonlinear coupling characteristic of the helicopter system is exploited. As the pitch angle can be measured in real time, a polytopic linear parameter-varying (LPV) model is developed for the helicopter system. Furthermore, considering measurement noises in the actual helicopter system, the dynamical model of helicopter system is modified accordingly. Then, based on the modified polytopic LPV model, a robust unknown input observer (UIO) is developed for the helicopter system to realize actuator fault estimation, in which both measurement noises and large pitch angle are considered. Robust performance of proposed fault estimation approach is guaranteed by using energy-to-energy strategy. And the observer gains are calculated by using linear matrix inequalities. Finally, based on a 3-DOF helicopter prototype, both simulations and experiments are conducted. The effects of measurement noises and large pitch angle on the fault estimation performance are sufficiently demonstrated. And effectiveness as well as advantages of the proposed observer is verified by using comparative analysis

Stability margins and model-free control: A first look

We show that the open-loop transfer functions and the stability margins may be defined within the recent model-free control setting. Several convincing computer experiments are presented including one which studies the robustness with respect to delays.Comment: 13th European Control Conference, Strasbourg : France (2014

A generalized scheme for the global adaptive regulation of robot manipulators with bounded inputs

"In this work, a generalized adaptive control scheme for the global position stabilization of robot manipulators with bounded inputs is proposed. It gives rise to various families of bounded controllers with adaptive gravity compensation. Compared with the adaptive approaches previously developed in a bounded-input context, the proposed scheme guarantees the adaptive regulation objective: globally, avoiding discontinuities in the control expression as well as in the adaptation auxiliary dynamics, preventing the inputs to reach their natural saturation bounds, and imposing no saturation-avoidance restriction on the control gains. Experimental results corroborate the efficiency of the proposed adaptive scheme.