Dynamic nonlinear inverse-model based control of a twin rotor system using adaptive neuro-fuzzy inference system

A dynamic control system design has been a great demand in the control engineering community, with many applications particularly in the field of flight control. This paper presents investigations into the development of a dynamic nonlinear inverse-model based control of a twin rotor multi-input multi-output system (TRMS). The TRMS is an aerodynamic test rig representing the control challenges of modern air vehicle. A model inversion control with the developed adaptive model is applied to the system. An adaptive neuro-fuzzy inference system (ANFIS) is augmented with the control system to improve the control response. To demonstrate the applicability of the methods, a simulated hovering motion of the TRMS, derived from experimental data is considered in order to evaluate the tracking properties and robustness capacities of the inverse- model control technique

Control of the twin-rotor system

The problem of Multi-Input-Multi-Output (MIMO) control has always been an interesting sub-field within the field of control. Among the systems that require MIMO control, the helicopter stands out as one of the prominent examples. This type of aircraft requires two rotors, rotating in perpendicular planes, therefore can not rely on Single-Input-Single-Output controllers to maneuver in the space. Also, un-manned helicopters have not yet been seen in armies worldwide, this fact gives the task of developing MIMO control systems for helicopters a large room to grow. In order to model the helicopter in laboratorial space, a Twin-Rotor Apparatus has been developed by Feedback company. This apparatus is being studied in Universitat Politècnica de Catalunya, Spain, to provide a good model for teaching and research in the field of MIMO control, with the aim to develop more efficient control methods for the real helicopter. The complete mechanical model for this apparatus has been developed using the software MAPLE. Based on this mechanical model, several control schemes are created to control the apparatus using MATLAB-Simulink. These control schemes are designed to make the Twin-Rotor system go to predetermined points and follow periodical input signals. The task of designing the control schemes requires the author to work on state-space configuration, linearization and experimental works. Mathematical approximation is also applied to get the approximated polynomials for variables relationship. The controllers designed work successfully and make ways for the design of similar controllers using for other MIMO syste

Modelling of a Flexible Manoeuvring System Using ANFIS Techniques

The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years. Robust optimal control of flexible structures with active feedback techniques requires accurate models of the base structure, and knowledge of uncertainties of these models. Such information may not be easy to acquire for certain systems. An adaptive Neuro-Fuzzy inference Systems (ANFIS) use the learning ability of neural networks to adjust the membership function parameters in a fuzzy inference system. Hence, modelling using ANFIS is preferred in such applications. This paper discusses modelling of a nonlinear flexible system namely a twin rotor multi-input multi-output system using ANFIS techniques. Pitch and yaw motions are modelled and tested by model validation techniques. The obtained results indicate that ANFIS modelling is powerful to facilitate modelling of complex systems associated with nonlinearity and uncertainty

Multiple-input multiple-output proportional-integral-proportional-derivative type fuzzy logic controller design for a twin rotor system

A new multiple-input multiple-output (MIMO) proportional-integral-proportional-derivative (PIPD) type fuzzy logic controller (FLC) is proposed for pitch and yaw motion control of a twin rotor system in this study. A fuzzy feedforward compensator for gravity effects on pitch motion of the twin rotor is also designed. Fuzzy logic was preferred for controller design since it can be applied to nonlinear systems and do not require the mathematical model of the system. The twin rotor system is a highly nonlinear system that includes coupling effects between pitch and yaw motions and has similar dynamics to that of a helicopter in certain aspects. Experimental results demonstrate that the proposed controller is able to stabilize the system along with good trajectory tracking performance

Reinforcement Learning for UAV Attitude Control

Autopilot systems are typically composed of an "inner loop" providing stability and control, while an "outer loop" is responsible for mission-level objectives, e.g. way-point navigation. Autopilot systems for UAVs are predominately implemented using Proportional, Integral Derivative (PID) control systems, which have demonstrated exceptional performance in stable environments. However more sophisticated control is required to operate in unpredictable, and harsh environments. Intelligent flight control systems is an active area of research addressing limitations of PID control most recently through the use of reinforcement learning (RL) which has had success in other applications such as robotics. However previous work has focused primarily on using RL at the mission-level controller. In this work, we investigate the performance and accuracy of the inner control loop providing attitude control when using intelligent flight control systems trained with the state-of-the-art RL algorithms, Deep Deterministic Gradient Policy (DDGP), Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO). To investigate these unknowns we first developed an open-source high-fidelity simulation environment to train a flight controller attitude control of a quadrotor through RL. We then use our environment to compare their performance to that of a PID controller to identify if using RL is appropriate in high-precision, time-critical flight control.Comment: 13 pages, 9 figure

Modeling and Robust Control of Twin Rotor MIMO System

Recently, unmanned aerial vehicles (UAVs) have witnessed immense popularity in various fields, ranging from surveillance, rescue, and fire fighting to other more sophisticated military and commercial applications. However, due to their highly nonlinear nature and dynamic operational environment, the control of UAVs is still a challenging task. Linear Quadratic-Gaussian Regulator (LQG), is an optimal control technique, which has been very popular for UAVs control. However, for robust performance, an accurate dynamic model of a system is required. In order, to overcome this limitation, the present work couples an integral sliding mode controller with the LQG controller to deal with the modeling inaccuracies. Experimental results of pitch control of the laboratory-based twin rotor MIMO system (TRMS), validate the performance of ISMC-LQG controller

Multi-fuel rotary engine for general aviation aircraft

Design studies of advanced multifuel general aviation and commuter aircraft rotary stratified charge engines are summarized. Conceptual design studies were performed at two levels of technology, on advanced general aviation engines sized to provide 186/250 shaft kW/hp under cruise conditions at 7620 (25000 m/ft) altitude. A follow on study extended the results to larger (2500 hp max.) engine sizes suitable for applications such as commuter transports and helicopters. The study engine designs were derived from relevant engine development background including both prior and recent engine test results using direct injected unthrottled rotary engine technology. Aircraft studies, using these resultant growth engines, define anticipated system effects of the performance and power density improvements for both single engine and twin engine airplanes. The calculated results indicate superior system performance and 27 to 33 percent fuel economy improvement for the rotary engine airplanes as compared to equivalent airframe concept designs with current baseline engines. The research and technology activities required to attain the projected engine performance levels are also discussed

Advanced stratified charge rotary aircraft engine design study

A technology base of new developments which offered potential benefits to a general aviation engine was compiled and ranked. Using design approaches selected from the ranked list, conceptual design studies were performed of an advanced and a highly advanced engine sized to provide 186/250 shaft Kw/HP under cruise conditions at 7620/25,000 m/ft altitude. These are turbocharged, direct-injected stratified charge engines intended for commercial introduction in the early 1990's. The engine descriptive data includes tables, curves, and drawings depicting configuration, performance, weights and sizes, heat rejection, ignition and fuel injection system descriptions, maintenance requirements, and scaling data for varying power. An engine-airframe integration study of the resulting engines in advanced airframes was performed on a comparative basis with current production type engines. The results show airplane performance, costs, noise & installation factors. The rotary-engined airplanes display substantial improvements over the baseline, including 30 to 35% lower fuel usage

Nonlinear Cascade-Based Control for a Twin Rotor MIMO System

This research is focused on the development of a nonlinear cascade-based control algorithm for a laboratory helicopter-denominated Twin Rotor MIMO System (TRMS). The TRMS is an underactuated nonlinear multivariable system, characterised by a coupling effect between the dynamics of the propellers and the body structure, which is caused by the action-reaction principle originated in the acceleration and deceleration of the propeller groups. Firstly, this work introduces an extensive description of the platform’s dynamics, which was carried out by splitting the system into its electrical and mechanical parts. Secondly, we present a design of a nonlinear cascade-based control algorithm that locally guarantees an asymptotically and exponentially stable behaviour of the controlled generalised coordinates of the TRMS. Lastly, a demonstration of the effectiveness of the proposed approach is provided by means of numerical simulations performed under the MATLAB®/Simulink® environment