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

Iterative learning control experimental results in twin-rotor device

This paper presents the results of applying the Iterative Learning Control algorithms to a Twin-Rotor Multiple-Input Multiple-Output System (TRMS) in order to achieve high performance in repetitive tracking of trajectories. The plant, which is similar to a prototype of helicopter, is characterized by its highly nonlinear and cross-coupled dynamics. In the first phase, the system is modelled using the Lagrangian approach and combining theoretical and experimental results. Thereafter, a hierarchical control architecture which combines a baseline feedback controller with an Iterative Learning Control algorithm is developed. Finally, the responses of the real device and a complete analysis of the learning behaviour are exposed.Postprint (published version

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

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

An Improved Fuzzy Parallel Distributed –Like Controller for Multi-Input Multi-Output Twin Rotor System

Twin Rotor Multi Input Multi Output (MIMO) System (TRMS) is a laboratory set-up design for which it has been used for control experiments, control theories developments, and applications of the autonomous helicopter. Fuzzy Logic Control (FLC) has been widely used with different control schemes to cope with control objectives of TRMS. In this work, Self Tuning Fuzzy PD-like Controller (STFPDC) is proposed to make the response of FLC more robust to the interactions and the non-linearity of the process in terms of less rising time, settling time and overshoot. Adaptive Neuro Fuzzy Inference System (ANFIS) based Fuzzy Subtractive Clustering Method (FSCM) was used to remodel the proposed STFPDC to achieve the control objectives on TRMS with less number of rules. MATLAB/SIMULINK was involved to achieve the simulations in this work. The results showed the proposed controller could simplify the STFPDC to reduce the number of rules from 392 to 73, which is even less than the original FLC that has 196 rules. The conclusion of this work is improving FLC response by using STFPDC and reducing the number of rules used to achieve this improvement by using ANFIS based on FSCM modeling. For future works, it is recommended to develop an optimization algorithm which achieves best selection for the range of influence which gives best response with less number of rules

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

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

A single-step identification strategy for the coupled TITO process using fractional calculus

The reliable performance of a complete control system depends on accurate model information being used to represent each subsystem. The identification and modelling of multivariable systems are complex and challenging due to cross-coupling. Such a system may require multiple steps and decentralized testing to obtain full system models effectively. In this paper, a direct identification strategy is proposed for the coupled two-input two-output (TITO) system with measurable input–output signals. A well-known closed-loop relay test is utilized to generate a set of inputs–outputs data from a single run. Based on the collected data, four individual fractional-order transfer functions, two for main paths and two for cross-paths, are estimated from single-run test signals. The orthogonal series-based algebraic approach is adopted, namely the Haar wavelet operational matrix, to handle the fractional derivatives of the signal in a simple manner. A single-step strategy yields faster identification with accurate estimation. The simulation and experimental studies depict the efficiency and applicability of the proposed identification technique. The demonstrated results on the twin rotor multiple-input multiple- output (MIMO) system (TRMS) clearly reveal that the presented idea works well with the highly coupled system even in the presence of measurement noise

Robust fault detection based on adaptive threshold generation using interval LPV observers

In this paper, robust fault detection based on adaptive threshold generation of a non-linear system described by means of a linear parameter-varying (LPV) model is addressed. Adaptive threshold is generated using an interval LPV observer that generates a band of predicted outputs taking into account the parameter uncertainties bounded using intervals. An algorithm that propagates the uncertainty based on zonotopes is proposed. The design procedure of this interval LPV observer is implemented via pole placement using linear matrix inequalities. Finally, the minimum detectable fault is characterized using fault sensitivity analysis and residual uncertainty bounds. Two examples, one based on a quadruple-tank system and another based on a two-degree of freedom helicopter, are used to assess the validity of the proposed fault detection approach.Postprint (published version

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