Twin Rotor MIMO System Research Articles

Robust two-degree of freedom H∞ control design for a twin rotor multi-input multi-output system with external disturbances and model uncertainties

The control of twin rotor multi-input multi-output system is difficult as it is subjected to model uncertainties and external disturbances. Furthermore, there also exists a coupling between pitch and yaw positions, which makes the system more difficult to control them separately. Considering the above difficulties in twin rotor multi-input multi-output system control, [Formula: see text] robust controller is designed to handle the model uncertainties and external disturbances with two-degree-of-freedom. A mixed sensitivity approach is employed to represent the uncertainties and external disturbances arise in the twin rotor multi-input multi-output system. For performance analysis, first the proposed two-degree-of-freedom [Formula: see text] controller is compared with the ‘Linear Quadratic Regulator-Linear Matrix Inequality’–based robust proportional–integral–derivative controller and Internal Model Control–based proportional–integral–derivative controller in MATLAB/Simulation and then in experimentation. From the obtained results, it is confirmed that the proposed controller exhibits enhanced robustness, faster tracking performance and accurate disturbance attenuation, when compared with Linear Quadratic Regulator-Linear Matrix Inequality–based robust proportional–integral–derivative controller and Internal Model Control–based proportional–integral–derivative controller in face of external disturbances and uncertainties.

Intelligent Active Force Control Of A Twin Rotor System

The paper deals with a robust control method applied to a a twin rotor multiple- input-multiple-output system (TRMS). The performance of TRMS employing a hybrid active force control (AFC) and iterative learning (IL) technique is simulated to evaluate the capability of the proposed control method in countering the harmonic excitation with reference to the pitch, yaw, angles of main rotor and tail rotor of the TRMS responses. The AFC with IL scheme was used in conjunction with the Proportional-Integral-Derivative (PID) to analyze the system’s robustness against the introduced disturbance. The mathematical modeling of TRMS was first derived and later the simulation was conducted in MATLAB/Simulink computing platform. The PID controller was used as benchmarking prior to the implementation of AFC and IL in which the tuning of the PID and IL parameters were based on a heuristic method. A comparative study will be conducted for the PID and PIDAFCIL schemes in terms of overshooting, settling time and steady state error. The results show that the PIDAFCIL control method is highly robust, produces low steady state error and exhibits fast convergence compared to its counterpart.

Design of Estimator for Computing Yaw and Pitch for a Twin Rotor MIMO system

Performance of any system is identified through the observation of significant system parameters. Required parameters have to be measured using suitable sensors. But in some scenarios, it is difficult to measure some of the parameters due to issues in the placement of sensors. In such cases, estimators are developed to measure the parameters indirectly. In this paper, an attempt is made to develop an estimator to monitor the value of pitch and yaw of a twin-rotor multi input multi output system. The observer is developed using two methods one using Luenberger’s equations and the other using an Artificial Neural Network (ANN). For training the neural network model, the backpropagation algorithm is used. Tests have been conducted to analyze and compare the behavior of both observers. From the results, it is evident that a Luenberger observer performs better when sufficient system information is available and ANN observer performs better when inadequate system information is available

Learning Stable Robust Adaptive NARMA Controller for UAV and Its Application to Twin Rotor MIMO Systems

This study presents a nonlinear auto-regressive moving average (NARMA) based online learning controller algorithm providing adaptability, robustness and the closed loop system stability. Both the controller and the plant are identified by the proposed NARMA based input–output models of Wiener and Hammerstein types, respectively. In order to design the NARMA controller, not only the plant but also the closed loop system identification data are obtained from the controlled plant during the online supervised learning mode. The overall closed loop model parameters are determined in suitable parameter regions to provide Schur stability. The identification and controller parameters are calculated by minimizing the $$\varepsilon $$ -insensitive error functions. The proposed controller performances are not only tested on two simulated models such as the quadrotor and twin rotor MIMO system (TRMS) models but also applied to the real TRMS with having severe cross-coupling effect between pitch and yaw. The tracking error performances of the proposed controller are observed better compared to the conventional adaptive and proportional–integral–derivative controllers in terms of the mean squared error, integral squared error and integral absolute error. The most noticeable superiority of the developed NARMA controller over its linear counterpart, namely the adaptive auto-regressive moving average (ARMA) controller, is observed on the TRMS such that the NARMA controller shows a good tracking performance not only for the simulated TRMS model but also the real TRMS. On the other hand, it is seen that the adaptive ARMA is incapable of producing feasible control inputs for the real TRMS whereas it works well for the simulated TRMS model.

Pitch and Yaw Angular Motions (Rotations) Control of the 1-DOF and 2-DOF TRMS: A Survey

For several decades, researchers’ attention has been directed to the need for air safety. This has been a trailing concern for the engineering community and in particular the control engineers, who, due to the complex nature of aeronautical systems have to creatively grapple with requirements for aircraft safety and comfortability, flexibility, precision, speed and efficiency based on data obtained from such systems. Motivated by the impact modern control systems and modern technologies have on the present aeronautical/aerospace industry, a survey is carried out. It focuses on the nonlinear underactuated couplings of the decoupled Single-Degree-of Freedom and coupled Two-Degree-of-Freedom motion control of the ubiquitous rotorcraft, Twin Rotor Multi-Input Multi-Output System (TRMS) test bed. As a proven benchmark, it is employed for exploring, testing and validating flight control and optimization schemes. It brings to fore the recent developments of control laws, strategies and methods. They are deployed for physical system modelling, stability behavior (exponential and asymptotic), numerical simulations and real-time implementations in modern aerodynamic plants-(systems and technologies). These technologies include helicopters, airplanes, spacecraft, Unmanned Aerial Surveillance Vehicles, as well as main-stream and broad-ranging Multiple-Input Multiple-Output systems with varying degrees of nonlinearities and complexities. Of utmost importance, the methods are first validated on the TRMS test bed using the real-world online sensors’ (optical shaft encoders) data.

Data-Driven Neuroendocrine-PID Controller Design for Twin Rotor MIMO System

This paper presents the design of a data-driven neuroendocrine-PID controller based on adaptive safe experimentation dynamics (ASED) method for a twin-rotor MIMO system (TRMS). Neuroendocrine-PID is deemed a compatible controller, often due to its biological-inspired mechanism from a human’s endocrine system that promotes control effectiveness and accuracy. In assessing the robustness of the proposed controller, its parameters were optimized through the ASED method, by tracking both error and input control performances. In particular, the ASED method is a game-theoretic method that randomly perturbs several elements of its controller parameters to search for the optimal controller parameters. Comparison was further made alongside performance of a standard PID controller. Following the simulation conducted, findings with regards to total norm error and total norm input have hereby suggested neuroendocrine-PID as a better controller, following a 13.2% improvement in control accuracy to that of a standard PID controller for TRMS system.

English

English

Bond graph modeling and multi-body dynamics of a twin rotor system

The dynamics of a twin-rotor multi-input multi-output system, which is similar to that of a helicopter in many ways, is highly nonlinear in nature. In this article, a detailed dynamical model of twin-rotor multi-input multi-output system is developed and simulated by using bond graph approach. Nonlinear nature of the interface gain, thrust, and drag forces, and the stiffness of cable attached to support column joint are estimated. The rotors are modeled through the Newton–Euler equations. The bond graph model is created by using the generic sub-models and the same set of sub-models can be assembled differently to model many other similar systems such as tricopters and quadcopters. Inertial forces and moments, rotor thrust and drag forces, active and reactive motor torques, and direct current motor dynamics are considered in the model. The responses from the model are compared with the test data for validation.

Robust finite-time sliding mode control of twin rotor MIMO system

In this paper, a robust finite-time sliding mode control (SMC) of the twin rotor MIMO system (TRMS) is discussed. This helicopter laboratory model is highly nonlinear in characteristics and coupling dynamics between main and tail rotors. The main purpose of this paper is to investigate finite-time SMC for pitch and yaw angles of TRMS, either for posture stabilisation or trajectory tracking. Moreover, these angles are used commonly to determine the hovering posture of a helicopter. The paper first briefs the dynamical model of TRMS and then it adopts a finite-time SMC technique to achieve the desired trajectory or posture stabilisation. Numerical simulation results are demonstrated and verify the effectiveness of the control technique.

Modified Backstepping Algorithm with Disturbances Compensation for Nonlinear MIMO Systems

The paper deals with a novel modified backstepping algorithm to ensure the stability of the nonlinear multiple-input multiple-output plant under unknown bounded parametric uncertainties, Lipschitz nonlinear disturbances, and cross-couplings. The modification is based on the auxiliary loop method that permits to estimate undesired dynamics as disturbances and suppress them. High robustness of the closed-loop system without using high-gain components is achieved. The ractical contribution of the results is demonstrated using laboratory platform ”Twin Rotor MIMO System”.

Robust finite-time sliding mode control of twin rotor MIMO system

Robust finite-time sliding mode control of twin rotor MIMO system

Design and real time implementation of nonlinear sliding surface with the application of super-twisting algorithm in nonlinear sliding mode control for twin rotor MIMO system

This paper proposes the design of a nonlinear sliding surface based on the principle of variable damping concept for 2-degree of freedom Twin Rotor Multiple input Multiple output System (2-dof TRMS). The implementation of the designed nonlinear sliding surface in real time is demonstrated. Super-twisting algorithm is applied in nonlinear sliding mode control. The nonlinear sliding surface enables the system trajectory to be highly robust and with the application of super-twisting algorithm in nonlinear sliding mode controller (SMC), the designed controller has minimized the problem of chattering considerably. The system is modeled in such a way that it includes all nonlinearities and coupling effects. A decoupler is designed to nullify the coupling effect. This scheme is capable of reducing both the settling time and peak overshoot simultaneously for 2-dof TRMS. The scheme also reduces the chattering. The proposed method is compared with the design using PID controller. The applicability of the designed nonlinear sliding surface and nonlinear SMC with super-twisting algorithm have been tested both in simulation and in real time. This research paper is mainly dealing with the modeling of Twin rotor MIMO system by including all nonlinearities and coupling effects, the decoupler design for 2-dof TRMS, the design of nonlinear sliding surface for 2-dof TRMS and application of super-twisting algorithm in nonlinear sliding mode control for 2-dof TRMS.

Controller and Observer Techniques for Twin Rotor MIMO System

This paper elaborates the controller and observer system with all mathematical modeling of Twin Rotor MIMO System (TRMS) which is eminently nonlinear system. TRMS is 2 DOF (Degree of Freedom) helicopter model which originated in company called Feedback Instrument Limited for controlling and experimenting of different algorithms. Two DOFs i.e. Yaw and Pitch control need to control by using controller, that imply to track a desired path. Nowadays, the Unmanned Aerial Vehicles (UAV) has been tremendously useful for road traffic by video surveillance and supervisions for public purposes. Because of capacity to hover, helicopters can be used in any environmental conditions. Hence, Scope of TRMS studies has been increasing.

Design and performance comparison of different adaptive control schemes for pitch angle control in a twin – rotor – MIMO – system

The Twin Rotor MIMO System is a higher order non-linear plant and is inherently unstable due to cross coupling between tail and main rotor. In this paper only the control of main rotor is considered which is non-linear and stable by using adaptive schemes. The control problem is to achieve perfect tracking for input reference signals while maintaining robustness and stability. Four adaptive schemes were implemented, two using Model Reference Adaptive Control under which MIT rule and Modified MIT rule are used. The other two using Adaptive Interaction, namely, Adaptive PID and Approximate Adaptive PID. It is observed that adaptive schemes fulfill all the three system performance requirements at the same time. Modified MIT rule was found to give superior performance in comparison to other controllers. Also Approximate Adaptive PID was able to stabilize the main rotor and cancel the effect of cross coupling between tail rotor and main rotor when operating simultaneously without the need for designing decouplers for the system. Thus the main rotor can be made independent from the state of the tail rotor by using Approximate Adaptive PID.

H2 Vs H∞ control of TRMS via output error optimization augmenting sensor and control singularities

Abstract This paper addresses the robust control problem of Twin Rotor Multi input multi output System (TRMS) via H2 and H∞ control techniques. An output error optimization technique is proposed to develop H2 and H∞ controllers for the well posed plant. Computer simulation results are presented for closed loop TRMS in hovering positions which show marked improvements over previous works. The simulated plant exhibits stable responses in hovering position at the desired pitch and yaw angles. Corrections are incorporated in model formulation to compensate control and sensor singularities. The output error optimization technique proposed in the present paper can be essentially adopted in controlling of 2 by 2 plants exhibiting non-minimum phase dynamics.

A practical solution to implement nonlinear output regulation via dynamic mappings

This paper presents a novel error-feedback practical solution for real-time implementation of nonlinear output regulation. Sufficient and necessary conditions for both state- and error-feedback output regulation have been established for linear and nonlinear systems several decades ago. In their most general form, these solutions require solving a set of nonlinear partial differential equations, which may be hard or even impossible to solve analytically. In recent years, a methodology for dynamic calculation of the mappings required for state-feedback regulation has been put forward; following the latter, an error-feedback extension is hereby provided which, when combined with design conditions in the form of linear matrix inequalities, becomes suitable for real-time setups. Real-time results are presented for a nonlinear twin rotor MIMO system. Issues concerning the implementation as well as the solutions adopted, are discussed.

Comparative Analysis of LQG and LQGI Controllers for Twin Rotor MIMO System

Comparative Analysis of LQG and LQGI Controllers for Twin Rotor MIMO System

Online and stable parameter estimation based on normalized brain emotional learning model (NBELM)

SummaryRecently, a computational model of Amygdala based on the brain emotional learning is presented by psychologists. This brain emotional learning model (BELM) that has a neuro‐inspired architecture is utilized to train the weights which are in Amygdala and Orbitofrontal. In this paper, unknown parameters of dynamic systems are estimated by developing the normalized BELM (NBELM). To this end, after proving the stability of the model output, the sufficient condition for weights convergence is extracted while the sensitivity analysis is applied for this model. In order to evaluate the performance of NBELM, in the first example, the matrices of a twin rotor MIMO system are estimated and compared with the equation error method (EEM). In the second example, the nonlinear model of a servomotor is utilized as a case study. In the third example, the performance of the NBELM in experimental systems is validated using a reaction wheel with a DC motor. An important feature of the brain emotional system is its fast response, leading the NBELM to have a high speed performance in estimating the parameters of dynamic systems. A few number of adjustable parameters and low computing complexity also cause the NBELM to be an appropriate method for online estimation of the unknown parameters of dynamic systems.

Modified backstepping algorithm for control of nonlinear systems with cross-couplings

The paper deals with an output control approach for structural uncertain MIMO systems under parametrical uncertainties, cross- reactions and external disturbances. The proposed technique ensures high quality of transients and high robustness in the steady state toward the disturbances without using high-gain components in the controller. A model transformation with one linear filter for control signal is used to obtain a structural determined form of the plant (“straight-feedback form”). The dynamical order of the filer is equal to the relative degree of MIMO plant. The procedure of relative dynamic degree estimation for nonlinear MIMO plant with cross-couplings is considered. The control algorithm combines an auxiliary loop method and backstepping method. The first one is a robust approach to unknown bounded disturbances evaluation and compensation. Backstepping is a well-known iterative procedure of control law synthesis by consecutive analysis of the plant state equations. The considered combination allows estimating undesired dynamics in each state equation and compensates it by creation of virtual control laws with equal magnitude toward disturbances and reverse sign. Experimental verification of the considered control algorithm is given with the use of a laboratory platform called “Twin Rotor MIMO System”. The platform can be controlled in two angle positions and represents the simplified helicopter dynamics.

An adaptive observer for a class of nonlinear systems with a high-gain approach. Application to the twin-rotor system

In this paper, we investigate the problem of adaptive observer design for a class of nonlinear systems subject to unknown parameters and such that the classical observer matching assumption is not satisfied. We adopt the idea of generating auxiliary outputs based on a high-gain observer. The estimated auxiliary outputs are then employed by an adaptive observer to reconstruct both states and unknown parameters. The stability analysis is established based on Lyapunov theory. It is shown that the state estimation error and the adaptation error are uniformly bounded and converge to a compact set that may be reduced by an appropriate choice of the design parameters. In order to improve the robustness of our approach against disturbances, the proposed observer is appropriately modified based on sliding modes theory. Theoretical results are illustrated and validated for the twin-rotor MIMO system with numerical simulations.