Design of a Robust Controller Using Sliding Mode for Two Rotor Aero-Dynamic System: Design of a Robust Controller Using Sliding Mode for Two Rotor Aero-Dynamic System

This paper deals with two rotor aero-dynamic system (TRAS) which is a multi-input multi-output highly coupled nonlinear system, for creating a mathematical model based following the Lagrange’s Equations, and creating controllers for Sliding Mode Control and Linear Quadratic Regulator. The Sliding Manifold is designed by employing the reduced order representation. Linear Quadratic Regulator has been created by linearizing the nonlinear system acquired by creating the state space representation following the mathematical model. The signal tracking conditions of PID, SMC, and LQR have been discussed.  Although the proposed control methodology has perfect actuation time, the tracking efficiency was not satisfactory. Therefore, a rework on the parametrization and introduction of filters, i.e. types of Kalman Filters have been proposed as a conclusion

A Study of Advanced Modern Control Techniques Applied to a Twin Rotor MIMO System

The twin rotor MIMO system (TRMS) is a helicopter-like system that is restricted to two degrees of freedom, pitch and yaw. It is a complicated nonlinear, coupled, MIMO system used for the verification of control methods and observers. There have been many methods successfully applied to the system ranging from simple proportional integral derivative (PID) controllers, to machine learning algorithms, nonlinear control methods and other less explored methods like deadbeat control and various optimal methodologies. This thesis details the design procedure for two different control methods. The first is a suboptimal tracking controller using a linear quadratic regulator (LQR) with integral action. The second is the design of several adaptive sliding mode controller to provide robust tracking control of the TRMS. Once the design is complete the controllers are tested in simulation and their performance is compared against a PID controller experimentally. The performance of the controllers are also compared against other controllers in the literature. The ability of the sliding mode controllers (SMC) to suppress chattering is also be explored

Helicopter system modelling and control with matlab

This paper presents the modelling and control of a laboratory helicopter system with MatLab. In this perspective, students are motivated to investigate the dynamics, trajectory planning and control. Based on this experience, further studies on helicopter system, using more sophisticated concepts, are, then, more attractive from the students point of view.N/

Modelling, simulation, and calibration of twin rotor mimo system

Helicopter is an aircraft that plays important role in transporting products, people…in society nowadays. It is complex mechanical equipment that corresponds many fields such as fluid mechanics, mechanics, control…Design it probably easy but fabrication and control it are not simple problem. The aim of research is to obtain a simulation and control model for the setup that has the principle of function like a real helicopter in laboratory in Automatic Control Department in Technical University Catalonia – Barcelona. This setup names Twin Rotor Multi Inputs - Multi Outputs System (TRMS) is manufactured by the Feedback Instruments Limited Company. It serves as a guide for the control tasks and provides useful information about the physical behavior of the system. It is also useful setup for study and practice of students to have a clearer look. On the main originalities of the present master thesis is the use on a control oriented model based on the use of a model that has linear structure but parameters varying with the operating point. This type of model is known as Linear Parameter Varying model (shortly, LPV model). Two procedures to obtain such a model are proposed. One based of rearranging the non-linear equations in such a way that the LPV parameters appear linearly. The second is based on linearizing the non-linear model around different operating points and the interpolation the parameters between them. Finally, the LPV model for the TRMS system obtained using either of the procedures described above can be calibrated using standard parameter estimation algorithms available in the Identification Toolbox in MATLAB

Inverse model based control for a twin rotor system

The use of active control technique has intensified in various control applications, particularly in the field of aircraft systems. A laboratory set-up system which resembles the behaviour of a helicopter, namely twin rotor multi-input multioutput system (TRMS) is used as an experimental rig in this research. This paper presents an investigation using inverse model control for the TRMS. The control techniques embraced in this work are direct inverse-model control, augmented PID with feedforward inverse-model control and augmented PID with feedback inverse-model control. Particle swarm optimization (PSO) method is used to tune the parameter of PID controller. To demonstrate the applicability of the methods, a simulated hovering motion of the TRMS, derived from experimental data is considered. The proposed inverse model based controller is shown to be capable of handling both systems dynamic as well as rigid body motion of the system, providing good overall system performance

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

Hybrid active force control for fixed based rotorcraft

Disturbances are considered major challenges faced in the deployment of rotorcraft unmanned aerial vehicle (UAV) systems. Among different types of rotorcraft systems, the twin-rotor helicopter and quadrotor models are considered the most versatile flying machines nowadays due to their range of applications in the civilian and military sectors. However, these systems are multivariate and highly non-linear, making them difficult to be accurately controlled. Their performance could be further compromised when they are operated in the presence of disturbances or uncertainties. This dissertation presents an innovative hybrid control scheme for rotorcraft systems to improve disturbance rejection capability while maintaining system stability, based on a technique called active force control (AFC) via simulation and experimental works. A detailed dynamic model of each aerial system was derived based on the Euler–Lagrange and Newton-Euler methods, taking into account various assumptions and conditions. As a result of the derived models, a proportional-integral-derivative (PID) controller was designed to achieve the required altitude and attitude motions. Due to the PID's inability to reject applied disturbances, the AFC strategy was incorporated with the designed PID controller, to be known as the PID-AFC scheme. To estimate control parameters automatically, a number of artificial intelligence algorithms were employed in this study, namely the iterative learning algorithm and fuzzy logic. Intelligent rules of these AI algorithms were designed and embedded into the AFC loop, identified as intelligent active force control (IAFC)-based methods. This involved, PID-iterative learning active force control (PID-ILAFC) and PID-fuzzy logic active force control (PID-FLAFC) schemes. To test the performance and robustness of these proposed hybrid control systems, several disturbance models were introduced, namely the sinusoidal wave, pulsating, and Dryden wind gust model disturbances. Integral square error was selected as the index performance to compare between the proposed control schemes. In this study, the effectiveness of the PID-ILAFC strategy in connection with the body jerk performance was investigated in the presence of applied disturbance. In terms of experimental work, hardware-in-the-loop (HIL) experimental tests were conducted for a fixed-base rotorcraft UAV system to investigate how effective are the proposed hybrid PID-ILAFC schemes in disturbance rejection. Simulated results, in time domains, reveal the efficacy of the proposed hybrid IAFC-based control methods in the cancellation of different applied disturbances, while preserving the stability of the rotorcraft system, as compared to the conventional PID controller. In most of the cases, the simulated results show a reduction of more than 55% in settling time. In terms of body jerk performance, it was improved by around 65%, for twin-rotor helicopter system, and by a 45%, for quadrotor system. To achieve the best possible performance, results recommend using the full output signal produced by the AFC strategy according to the sensitivity analysis. The HIL experimental tests results demonstrate that the PID-ILAFC method can improve the disturbance rejection capability when compared to other control systems and show good agreement with the simulated counterpart. However, the selection of the appropriate learning parameters and initial conditions is viewed as a crucial step toward this improved performance

Nonlinear Model Predictive Control (NMPC) for Twin Rotor MIMO System (TRMS)

Twin Rotor MIMO System (TRMS) is a dynamic model with high non-linearity that resembles a helicopter with reduced degree-of-freedom (DOF). Besides, cross-coupling between main rotor and tail rotor contributes to the difficulty in controlling the system. Majority of the previous researches have not focused on continuous actual dynamic disturbance test. The objectives of this project are to model TRMS and control the system against major disturbance (wind effect) and set-point changes. The first phase of the project started with mathematical modelling of direct current (DC) motors, where the relationship between input voltage and angular velocity was captured. The next phase would be the modelling of the whole system and design of controller. During the second phase, the modelling would involve aerodynamics and other Physics laws. Once the complete model was formed, Proportional, Integral and Derivative (PID) and Linear Quadratic Regulator (LQR) controllers were designed to optimize the dynamic system. The system has been tested using wind variation as actual dynamic disturbance to validate the disturbance rejection performance. It was found that the best performance from combination of PID and LQR controllers gave 89% improvement in term of pitch overshoot and 33% improvement in term of yaw overshoot during disturbance rejection compared to PID-only controller

Optimal Controller Design for Twin Rotor MIMO System

Twin Rotor MIMO system (TRMS) is considered as a prototype model of Helicopter. The aim of studying the TRMS model and designing the controller for controlling the response of TRMS is that it provides a platform for controlling the flight of Helicopter. In this work, the non-linear model of Twin Rotor MIMO system has been linearized and expressed in state space form. For controlling action a Linear Quadratic Gaussian (LQG) compensator has been designed for a multi input multi output Twin Rotor system. Two degree of freedom dynamic model involving Pitch and Yaw motion has been considered for controller design. The two stage design process consists of the design of an optimal Linear Quadratic Regulator followed by the design of an observer (Kalman filter) for estimating the non-accessible state variable from noisy output measurement. LQR parameter i.e. Q and R are varied randomly to get the desired response. Later an evolutionary optimization technique i.e. Bacterial Foraging Optimization (BFO) algorithm has been used for optimizing the Q and R parameter of Linear Quadratic Gaussian compensator. Simulation studies reveal the appropriateness of the proposed controller in meeting the desired specifications

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