A Hybrid H∞ Control Based ILC Design Approach for Trajectory Tracking of a Twin Rotor Aerodynamic System

Saleem, Faisal; Ali, Ahsan; Shaikh, Inam Ul Hasan; Wasim, Muhammad

doi:10.22581/muet1982.2101.16

Cited by 4 publications

(6 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To create a new control input for the current trail, you can try anything. One can use P, PD, PI or merely proportional, integral, and derivative control rules to update the new control input [24][25]. In this work, PD type ILC is used.…”

Section: E Fopid-ekf-dob-pd-ilc Control Approachmentioning

confidence: 99%

See 1 more Smart Citation

Disturbance Observer based Fractional Order Iterative Learning Control of Helicopter Model

2023

1st International Conference on Modern and Advanced Research Icmar 2023

View full text Add to dashboard Cite

The Twin Rotor Aerodynamic System (TRAS) provides a general representation of the aerodynamic characteristics of helicopters as well as other hovering rotor vehicles. Due to the nonlinear nature of the system and the substantial cross-coupling between the inputs and outputs of the main and tail rotors, managing such a system for either stabilization or reference tracking is a challenging challenge. The reference tracking and disturbance rejection problem for a Multi-Input Multi-Output (MIMO) TRAS is investigated in this study using a hybrid architecture based on a Fractional Order Proportional Integral Derivative (FOPID) controller with an Extended Kalman Filter (EKF) as a Disturbance Observer (DOB) and Proportional Derivative Iterative Learning Control (PD-ILC) (FOPID-EKF-DOB-PD-ILC). The system is divided into subsystems for the main and tail rotors. Since TRAS is unstable and ILC is only used for stable systems, FOPID controller is employed to stabilize the plant. Sequential quadratic programming (SQP) is used to calculate the parameters of the FOPID controller. To lessen tracking error and gradually enhance system performance, PD-ILC is applied as a feedforward controller. ILC is employed in this situation as an external controller with no effect on the current control architecture. The FOPID-EKF-DOB controller adjusts the new control input according to the PD-ILC control law. Results from the simulation are used to evaluate the efficiency of the suggested strategy based on performance metrics.

show abstract

Section: E Fopid-ekf-dob-pd-ilc Control Approachmentioning

confidence: 99%

“…Sliding mode control, a method for controlling dynamic systems, is often used in literature. While the input is full, these controllers can still be used [24][25]. [26] claims that the issue of disturbance rejection for TRAS is resolved using a H ∞ based methodology and LQG as the outer loop baseline feedback controller.…”

Section: Introductionmentioning

confidence: 99%

Disturbance Observer based Fractional Order Iterative Learning Control of Helicopter Model

2023

1st International Conference on Modern and Advanced Research Icmar 2023

View full text Add to dashboard Cite

show abstract

“…A Twin Rotor Aerodynamic System (TRAS) as shown in Reference 23 is taken as an example for simulation study to verify the rationality and validity of the algorithm proposed in this paper.…”

Section: Numerical Simulation Case Analysismentioning

confidence: 99%

“…Record steady-state input u * (Γ 0 ) and initial control effort ‖u * (Γ 0 )‖ 2 R . Repeat: Implement the coordinate descent method(23). 2: Set j → j + 1.…”

mentioning

confidence: 99%

Robust point‐to‐point iterative learning control for constrained systems: A minimum energy approach

Zhou

Tao

Chen

et al. 2022

Intl J Robust & Nonlinear

103

View full text Add to dashboard Cite

Iterative learning control (ILC) is a high performance control scenario that is widely applied to systems that repeat a given task or operation defined over a finite duration, and has been introduced to point‐to‐point motion tasks in existing work. However, its design degree of freedom has not been fully utilized to optimize performance beyond tracking accuracy in constrained conditions. The framework of point‐to‐point ILC in this article is extended within discrete linear time‐invariant (LTI) system, so as to take the tracking time instants of desired positions as changing variables. Therefore, it is possible to achieve the objective of minimizing energy while maintaining the required tracking accuracy. The multiobjective optimization problem is divided into two sub‐problems, which are solved with an iterative algorithm composed of norm‐optimal ILC approach as well as the coordinate descend method. Furthermore, the impact of model uncertainty on algorithm performance is also considered, and the iterative algorithm is further extended to capture constrained systems. The algorithm is robust to the model uncertainty and has a certain robustness to output disturbances. Finally, the validity of the proposed algorithm is verified by a twin rotor aerodynamic system (TRAS) model.

show abstract

“…After the linearization and decoupling steps, 2-DOF continuous and discrete-time controllers were designed using H ∞ in [20]. A hybrid architecture using both H ∞ and Iterative Learning Control is described in [21]. A linear quadratic regulator (LQR) for MIMO TRAS problem was designed using particle swarm optimization in [22], while a frequency-based PID controller was combined with a lead compensator designed using root locus in [23].…”

Section: Introductionmentioning

confidence: 99%

μ-Synthesis FO-PID for Twin Rotor Aerodynamic System

2021

View full text Add to dashboard Cite

μ-synthesis is a NP-hard optimization problem based on the generalized Robust Control framework which manages to find a controller which fulfills both robust stability and robust performance. In order to solve such problems, nonsmooth optimization techniques are employed to find nearly-optimal parameters values. However, the free parameters available for tuning must be involved only in classical arithmetic operations, which leads to a problem for the fractional-order operator or for its integer-order approximation, exponential operations being involved. The main goal of the current article consists of presenting a possibility to integrate a fixed-structure multiple-input-multiple-output (MIMO) fractional-order proportional-integral-derivative (FO-PID) controller in the μ-synthesis optimization problem. The solution consists in a possibility to find a set of tunable parameters isomorphic with the fractional-order such that the coefficients involved in the approximation of the fractional element, along with the formulation of a fixed-structure mixed-sensitivity loop shaping μ-synthesis control problem. The proposed design procedure is applied to a twin rotor aerodynamic system (TRAS) using both MATLAB numerical simulation and practical experiments on laboratory scale equipment. Moreover, a comparison with the unstructured μ-synthesis is performed, highlighting the advantages of the proposed solution: simpler form and guaranteed robust stability and performance.

show abstract

A Hybrid H∞ Control Based ILC Design Approach for Trajectory Tracking of a Twin Rotor Aerodynamic System

Cited by 4 publications

References 26 publications

Disturbance Observer based Fractional Order Iterative Learning Control of Helicopter Model

Disturbance Observer based Fractional Order Iterative Learning Control of Helicopter Model

Robust point‐to‐point iterative learning control for constrained systems: A minimum energy approach

μ-Synthesis FO-PID for Twin Rotor Aerodynamic System

Contact Info

Product

Resources

About