Ismaila B. Tijani

Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

The need for a high fidelity model for design, analysis and implementation of an unmanned helicopter system (UHS) in various emerging civil applications cannot be underestimated. However, going by a first principle approach based on physical laws governing the dynamics of the system, this task is noted to be highly challenging due to the complex nonlinear characteristics of the helicopter system. On the other hand, the problem of determining network architecture for optimal/sub-optimal performances has been one of the major challenges in the use of the nonparametric approach based on Nonlinear AutoRegressive with eXogenous inputs Network (NARX-network). The performance of the NARX network in terms of complexity and accuracy is largely dependent on the network architecture. The current approach in the literature has been largely based on trial and error, while most of the reported optimization approaches have limited the domain of the problem to a single objective problem. This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data. The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. The performance of the proposed optimized model is benchmarked with one of the previously reported architectures for a similar system. The optimized model outperformed the previous model architecture with up to 55% performance improvement. Apart from the effectiveness of the optimized model, the proposed design algorithm is expected to facilitate timely development of the nonparametric model of the helicopter system.

H∞ robust controller for autonomous helicopter hovering control

Purpose – The purpose of this paper is to present the synthesis of a robust controller for autonomous small‐scale helicopter hovering control using extended H∞ loop shaping design techniques.Design/methodology/approach – This work presents the development of a robust controller for smooth hovering operation required for many autonomous helicopter operations using H∞ loop shaping technique incorporating the Vinnicombe‐gap (v‐gap) metric for validation of robustness to uncertainties due to parameter variation in the system model. Simulation study was conducted to evaluate the performance of the designed controller for robust stability to uncertainty, disturbance rejection, and time‐domain response in line with ADS‐33E level 1 requirements.Findings – The proposed techniques for a robust controller exhibit an effective performance for both nominal plant and 20 percent variation in the nominal parameters in terms of robustness to uncertainty, disturbance wind gust attenuation up to 95 percent, and transient pe...

Friction compensation for motion control system using multilayer feedforward network

Friction has been shown to be one of the major contributing factors for problem associated with accuracy in motion control systems. Apart from making the system response slow, it causes steady state error or limit cycles near the reference position for the motion control system. In order to alleviate these problems, various control methods have been introduced and proposed for compensating the friction effect. Among the successful method is model-based friction compensation. Many sophisticated friction models have been proposed by researchers. Unfortunately, selecting and developing accurate models for friction compensation for a particular application has been historically challenging and trouble some due to complexity of parametrically modeling of the friction nonlinearities. Motivated by the need for simple and at the same time effective friction compensation in motion control system, AIbased friction model using multilayer feedforward network (MFN) is proposed and developed to estimate and compensate the frictional dynamics of a DC motor driven motion control system. The effectiveness of the developed MFN-based friction model to compensate the friction is evaluated experimentally on a rotary experimental motion system, and compared with mathematical model approach. The experimental results show that the friction compensation using the MFN-based friction model is more effectively to compensate for the effect of the friction than that on mathematical model of friction.

Support vector regression based friction modeling and compensation in motion control system

Friction has been experimentally shown to be one of the major sources of performance degradation in motion control system. Although for model-based friction compensation, several sophisticated friction models have been proposed in the literatures, there exists no universally agreed parametric friction model, which by implication has made selection of an appropriate parametric model difficult. More so, accurate determination of the parameters of these sophisticated parametric friction models has been challenging due to complexity of friction nonlinearities. Motivated by the need for a simple, non-parametric based, and yet effective friction compensation in motion control system, an Artificial Intelligent (AI)-based (non-parametric) friction model using v-Support Vector Regression (v-SVR) is proposed in this work to estimate the non-linear friction in a motion control system. Unlike conventional SVR technique, v-SVR is characterized with fewer parameters for its development, and requires less development time. The effectiveness of the developed model in representing and compensating for the frictional effects is evaluated experimentally on a rotary experimental motion system. The performance is benchmarked with three parametric based (Coulomb, Tustin, and Lorentzian) friction models. The results show the v-SVR as a viable and efficient alternative to the parametric-based techniques in representing and compensating friction effects.

Control of an inverted pendulum using MODE-based optimized LQR controller

This paper presents an evolutionary optimization based LQR controller design for an inverted pendulum system. The objective is to address the challenges of appropriate design parameters selection in LQR controller while providing optimal performance compromise between the system control objectives with respect to pendulum angle and position response. Hence, a Multiobjective differential evolution algorithm is proposed to design an LQR controller with optimal compromise between the conflicting control objectives. The performance of the MODEbased LQR is benchmarked with an existing controller from the system manufacturer (QANSER). The performance shows the effectiveness of the proposed design algorithm, and in addition provides an efficient solution to conventional trial and error design approach.

Hybrid DE-PEM algorithm for identification of UAV helicopter

Purpose – The purpose of this paper is to develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model. Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. Findings – The proposed hybrid algorithm improves the performance of the PEM algorithm in the identification of an autonomous helicopter model. It gives better results when compared with conventional PEM algorithm inside MATLAB toolboxes. Research limitations/implications – This study is applicable to only linearized state-space model. Practical implications – The identification algorithm is expected to facilitate the required model development for model-based control design for autonomous helicopter development. Original...

Optimization of PID controller for flexible link system using a pareto-based multi-objective differential (PMODE) evolution

The conflict between the transient performance of the link position and tip vibration in a flexible link system has made the control of such system a challenging task. The system is required to obtain a fast transient position response together with minimal tip vibration. This can be viewed like many other real-life control problems as a multi-objectives optimization problem in which an optimal compromise between the design objectives is required. PID controller is noted with historical simplicity in terms of design and implementation when compares to other linear time invariant (LTI) control techniques. However, the shortcoming of PID lies in the tuning of the controller gains for a given problem. To overcome this, a Multiobjective Differential Evolution (MODE)-based PID controller is reported in this study for controlling a flexible link system. The gains of the PID controller are tuned using a developed MATLAB-based MODE to obtain pareto-solutions for both link position and tip vibration. The performance of the selected best PID controller from MODE-based design is benchmarked with the LQR controller provided by the manufacturer (QUANSER) of the laboratory scale flexible link plant. Though, the LQR shows better transient performance in the position responses, the developed MODE-PID gave better tip response performances as indicated in both the simulation and experimental responses obtained.

Optimization of an extended H-infinity controller for unmanned helicopter control using Multiobjective Differential Evolution (MODE)

Purpose – The purpose of this paper is to develop a multiobjective differential evolution (MODE)-based extended H-infinity controller for autonomous helicopter control. Design/methodology/approach – Development of a MATLAB-based MODE suitable for controller synthesis. Formulate the H-infinity control scheme as an extended H-infinity loop shaping design procedure (H ∞ -LSDP) with incorporation of v-gap metric for robustness to parametric variation. Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. Findings – The proposed optimized H-infinity control was able to yield set of Pareto-controller candidates with optimal compromise between conflicting stability and time-domain performances required in autonomous helicopter deployment. The result of performance evaluation shows robustness to parameter variation of up to 20 per cent variation in nominal values, and in addition provides satisfactory disturbance rejection to wind distur...

Development of real-time software interface for multicomponent transient signal analysis using Labview and Matlab

This paper presents the development of software interface for real-time implementation of the algorithms for multicomponent transient signal analysis. Though, a Matlab-based algorithm has been developed in the previous study on multicomponent signal analysis, real-time signal analysis is required in many practical applications of such signals. Hence, in this study, a user friendly software interface is developed using an integration of Labview and Matlab packages for real-time implementation of the multicomponent signal analysis. The developed software interface was evaluated with experimental fluorescence data collected from a spectrofluorometer system. The results obtained indicate the effectiveness of the integrated software for practical applications.

Real-time implementation of H ∞ controller for UAV helicopter using MATLAB-based embedded programming approach

The rapid-prototyping and deployment of flight control algorithm on a real-time embedded target has been one of the major challenges in an unmanned helicopter system development. In this paper, a MATLAB-Simulink based embedded target programming approach is presented to address this challenge. The motivation for this approach is that, since most of the computational tasks in the unmanned helicopter system, such as modeling, controller design and simulation are readily and effectively achieved within the MATLAB environment, then, extending the platform to deployment of the resulting flight algorithm onto an embedded target would greatly ease the overall developmental activities. The design and deployment of an H∞ based flight control algorithm onto an embedded target is presented for a small scale unmanned helicopter system. The results of the hardware-in-loop simulation and real-flight tests show effectiveness of the proposed approach. This is expected to facilitate and contribute towards a single-platform integrated development environment for unmanned system development.