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Investigation of flutter instability analysis is an important process during design phase and certification of an aircraft. Without proper analysis, the effect of modification at later stage of design process could come at high cost and risk. The present work examines detailed elevator tab model which could result in a more critical tab flutter speed. The present investigation of aerodynamic hinge moment variation effect on flutter analysis also shows a significant decrease in the flutter speeds. Three configurations involving elevator trim tab and balance tab fixed/free mechanism are investigated. Investigation of flutter sensitivity to tab rotational frequency and tab bending/torsion frequency was performed to determine the minimum tab rotational frequency requirement, so that it can be used as reference in design process. Variation of Mach number (for Configuration 1) and elevator aerodynamic hinge moment (all configurations) are performed. It is found that the aerodynamic variation takes effect when the mode involves both trim and balance tabs and tab elastic modes (e.g., tab torsion). It is found also that the most critical flutter case is for Configuration 3 where the trim and balance tabs are not fixed (independent). The result suggests that control surface tabs need to be modelled from the early design process, so that if any critical flutter appears and needs to be responded by a change in design, it can be implemented earlier and therefore avoid any costly risk.

Due to relatively complex geometry of N219 winglets, CFD simulations have to be conducted to predict the aerodynamic load by the structure in some critical flight conditions. Since the aerodynamic CFD model is not the same as the finite element model of the structure, there is a need to accurately transform the load data between the two models. This paper discusses a simple alternative technique to map pressure distribution from the mesh or face zone of a CFD simulation to an FEM model using a Matlab based in-house code program. The technique focuses on how an FEM shell element has same pressure value with its nearest CFD element. Although the cumulative forces sometimes give different result, the pressure distribution is highly accurate, moreover when the FEM model has smoother elements. Validation has been conducted by comparing with other pressure mapping technique of a commercial software Patran. The results show a good agreement where the present technique provide a more accurate result especially for the critical biggest load among the cumulative forces in the three-dimensional direction. The proposed technique is currently suitable to evaluate loading characteristics of semi monocoque structures. A further treatment of the technique for other types of structure is currently under development.

The fabrication technique applied in this research to grow ZnO crystal is known as ECH method. It is a preferred method due to its low cost, simplicity in operating and low growth temperature. However the condition of ECH method to produce the optimum crystal growth has not been studied further. The objectives of this research are to synthesize ZnO ceramic pellets, to produce ZnO micro/nanostrcutures on ZnO ceramics bar by ECH method, as well as to characterize and analyze structural, morphological, and optical properties of ZnO crystals grown. ZnO pellets were formed by pressed at 3, 4, 5 tons and sintered at 1,100 °C in air for 4 and 72 hours. ZnO ceramic bar was joule heated by direct current of 2 A and 3 A. The result is the grain size of ZnO pellets increased with increasing sintering time and pressing pressure. XRD results indicated mostly crystal prefer to grow along (100) orientation. SEM images showed crystals grown was in a variety of shapes and sizes. PL measurements at room temperature revealed high intensity peak of in visible region in which yellow-level emission was observed from ZnO crystals grown.

There are three objectives to be achieved in this research which include to synthesis high purity ZnO pellets with different sintering time and green body pressure by using powder metallurgy process, the growth of ZnO crystal on ceramic bar by applying different current when conducting electric current heating (ECH) method and the characterization of ZnO crystal growth. In this research, high purity of ZnO powder is grinded and compressed at 3.5 tons, 4.5 tons and 5.5 tons to fabricate ZnO green pellets. Then, the ZnO green pellets are sintered for 3 hours and 5 hours. Next, the pellets are cut into bars and apply ECH method. The amount of current applied for the crystal growth are 2A and 3A. Finally, the crystal grown on the ZnO ceramic bar is characterized using X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Ultraviolet-visible Spectroscopy (UV-Vis) and Photoluminescence Spectroscopy (PL). High purity ceramic pellets are successfully synthesis by powder metallurgy process. By conducting ECH method, crystal are grown on the surface of ceramic bar. Most crystal structure found in ZnO ceramic bar is needle-liked rod structure which is hexagonally formed by many nanorod. The crystal grown in (100) orientation with the crystalline size of from 57.80 nm to 100.31 nm. The band gap energy obtained from UV-Vis were found between 3.2 eV to 3.4 eV which is nearly similar to the theoretical value of 3.37 eV. Lastly, PL emission measurement give the peak that range between 579 nm to 587 nm which indicate that the sample exhibit yellow colour. Among three different pressure applied, 4.5 tons gives the lowest emission energy. It is considered as the critical pressure in the synthesis of ZnO crystal. The intensity of PL is considered inversely proportional to intensity of XRD in [100] direction. Pressing pressure doesn’t show significant effect on the crystal growth of ZnO but current applied during ECH method and sintering time do give effect on UV-Vis absorption spectra and XRD result respectively.

Metal oxide semiconductor gas sensors have been widely utilized in a variety of different roles and industries. They are relatively inexpensive, robust, lightweight, long lasting and benefit from high material and quick response time compared to other sensing technologies. However, there are major challenges need to overcame by developers in order to construct a semiconductor metal oxide gas sensor that is efficient, and durable and most importantly can work at lower temperature. Therefore, in this research, TiO2 dopants was introduced into conventional high purity ZnO gas sensor whereby the samples were prepared in pellet form using powder metallurgy route. The improvement in the mechanical properties as well as the electrical properties of the samples was wished to be observed through this research. The density measurement showed that the adding of TiO2 was efficient to promote the densification of ZnO sample in which 9 wt% TiO2 doped ZnO sample showed the highest density. The XRD results showed that the diffraction pattern was basically attributed to the wurtzite structure of ZnO. This was proven by the plane (1 0 1) had the highest intensity in all the samples except 6 wt% TiO2 and 9 wt% TiO2 doped ZnO sample. SEM showed that the grain size of ZnO decreased with the addition of TiO2. This was caused by the formation of the new phase which was Zn2TiO4. The smaller the grain size, the higher the specific surface area and oxygen adsorption quantity, and therefore the higher the gas sensitivity is. UV-Vis showed that the wavelength of all samples was located around 380 nm. Therefore, the calculated exitonic energy was around 3.20 eV which was nearly matched with the theoretical band gap of ZnO (3.37 eV). The measurement of the resistivity using four point probe showed that the electrical resistivity of the samples decrease up to addition of 9 wt% TiO2. This was attributed to increased carrier concentration. Vickers hardness test showed that the doping of TiO2 had increased the hardness of the sample whereby the 9 wt% TiO2 doped ZnO sample showed the highest value of hardness. The addition of TiO2 into high purity ZnO has influenced the mechanical and electrical properties of ZnO. From observing the microstructural and density measurement to the measurement of the surface resistivity as well as the determination of the Vickers hardness value, it was found that 9 wt% TiO2 doped ZnO was predicted as a candidate for substituting a conventional high purity ZnO as the gas sensor.

This research deals with ambient energy harvesting by using zinc oxide thin film. The objectives of this thesis are to prove the ZnO film as a piezoelectric material can produce electric when vibration is applied and determine its optimal voltage. The thesis describes the sol gel spin coating technique to fabricate zinc oxide thin film. Zinc acetate dehydrate, absolute ethanol and diethanolamine were used in this thesis to act as sol gel precursor. Sol gel was coated on glass slide which wrapped by aluminum foil. The thin film was formed after preheating and annealing. The thin film was characterized by X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Photoluminescence spectroscopy (PL) and Ultraviolet-visible spectroscopy (UV-Vis) as well as analyzed using vibration technique. From XRD results, the films were preferentially diffracted at around 65° which corresponding to (1 1 2) diffraction phase. From FESEM results, it was observed that when the spin speed was increased at same annealing temperature, the thickness was also decreased. When the annealing temperature was increased at same spin speed, both grain size and thickness were increased. From the PL results, there was only film with spin speed of 2000 rpm and annealing temperature of 300 °C had slightly left wavelength which was 380 nm. Annealing temperature would affect only the intensity of PL wavelength. From the results of UV-Vis, it was observed that when the spin speed was increased at same annealing temperature, the band gap was decreased. When the annealing temperature was increased at same spin speed, the band gap was decreased. Piezoelectric test had proven the ZnO film could produce electricity. The maximum voltage (20.7 mV) was produced by the ZnO film with spin speed of 2000 rpm and annealing temperature of 300 °C.

The invention of Unmanned Aerial Vehicle (UAV) in the early 1900 for military purposes and UAV applications in commercial purposes afterwards in the early 2000 accelerate its research in many engineering fields. Multirotor UAV such as quadrotor is usually unstable without a flight controller. Consequently, a proper and accurate model of the UAV dynamics is essential for its system stability. System identification allows the researchers to create an accurate parameter to the mathematical model of a dynamic system based on measured data. This work emphasizes in designing a robust and adaptive filter to develop an accurate mathematical model based on Newton-Euler method which includes aerodynamic drag and moment which are necessary in determining the correct model prediction. The focus of the present work is mainly on Kalman filter development for parameter estimation. While Kalman filter is only efficient in linear problem, an extended version of the filter itself deals with the nonlinear problem in which most real problem is actually nonlinear. This work investigates the performance of the extended version of the Kalman filter relative to parameter estimation. The performance of the filters are evaluated based on their estimation with the actual recorded flight data and presented based on data overlapping using Root Mean Square Error (RMSE). Ardupilot APM is used to acquire the actual flight test data and MATLAB is utilized to carry out the state estimation. To evaluate the performances of the filters, Goodness of Fit (GOF) approach was used. It is found that the GOF index of the present approach is 0.853 which is 25% higher than that of the Robust Extended Kalman Filter approach for the present flight test result.

WiFi indoor localization is regarded as the most promising reliable technology for indoor localization. Its concept is based on building fingerprint and training a ma-chine learning model on it, then using it for predicting the location based on the measured received signal strength RSS. One aspect of its vulnerability is its time vari-ant change due to the dynamical conditions in the environment and the access points APs. This was the most focus of the researchers in the last decades. However, minori-ty of them have considered the limitations of the existing benchmarking fingerprint in terms of lacking of support to realistic navigations runs when they are used for eval-uating indoor localization models. This article proposes a simple yet novel add-on to existing benchmarking fingerprint that assists in converting it from static fingerprint to consecutive training data with supportability to incremental learning and awareness of various characteristics of indoor navigation runs. The model was evaluated based on two benchmarking fingerprint and the generated incremental data were plotted with two levels of granularity one is corresponding to location and the other to place for referring to high resolution level and low resolution level.

An example of sintered inert ceramic is ceramic balls as catalyst support media. The composition of the ceramic is regulated by Universal Oil Products (UOP) standard. The requirement of the chemical composition will therefore determine the range of sintering temperature, number of phases or crystal during sintering, and the weight percent of starting materials. The weight percent of starting materials becomes important in order to fulfil the UOP requirement since all of the materials are stable raw materials and can be found directly from nature. This study is to design how to have the starting material composition and sintering temperature to fulfil the standards. One example of inert ceramic ball design is illustrated at the end of this paper.

Unmanned Aerial Vehicle (UAV) has been the interest in many researchers. It has become increasingly popular over the last decade. Quadrotor UAV is a small helicopter and is highly unstable without any flight controller. Therefore, a proper control on the UAV’s dynamic need to be applied for stabilization. An accurate model of the vehicle dynamics is important to stabilize the UAV. System identification allows the researchers to build mathematical models of a dynamic system based on measured data. In this paper, various system identifications on quadrotor UAV are discussed. This paper only reviews the literature on system identification based on other researches that had been done. Critical review on each method is briefly discussed. This paper also provides the idea of system identification and its characteristics. Concluding remark is given regarding the suitable method for the model chosen.

This paper deals with the investigation on the spring-back of CFRP composite laminate after curing process through autoclave manufacturing process. Two parameters are considered; curvature and stacking lay-up to reflect its application for Aircraft structure. The specimen consists of a 4 plies of UD laminate with a dimension of 500*500mm2 and curvature angle of 30°, 45° and 90°. The analysis of experiments shows that the acute curvature angle until 90° influenced significantly the spring-back deformation with a linear correlation vis-a-vis curvature angle. A FE model is proposed where the laminate is divided into 2 regions; corner for curvature shape and flange for flat area. First attempt to simulate the effect of curvature is reducing the flange modulus of Young due to resin accumulation on flange area and FEA result showed the effect is insignificant. Therefore, the effect comes from the fact that the laminate behaves differently at the corner compared to the flange. The FEA simulation correlates the spring-back of all curved specimen by increasing the thermal expansion of 1st ply, α, of corner linearly with the flange. The proposed method is tested using other published data which were using the specimen with; 8 plies, 280*216mm2 with curvature angle 45° and 90°. As for symmetrical laminate, specimens with a dimension of 300*300mm2, 4 plies, and stacking layup [45/0]s [45/-45]s and [0/45]s are fabricated to investigate the effect of stacking lay-up of the laminate to the spring-back magnitude. The spring-back measurements indicate that the 1st ply fiber direction of laminate which is in contact with mold produces different shape of spring-back after curing. Therefore, the 1st ply of laminate, α, playes a significant role on the spring-back magnitude and shape of symmetrical laminate. FEA confirmed the phenomena by correlating the spring-back obtained from experiments.

Thin film technology is the field of thin film deposition process and it is linked to nanotechnology. Thin film technology has been applied in many fields. Mostly thin film is used in electronic components and electronic displays such as LED displays and lighting, thin film solar cell. Semiconducting material, insulating materials or metal silicide conductors are typically made up of these thin films. Doping is one of the methods to change the properties of thin film. There various types of materials could be used as doping element. Different types of element has different properties which will cause properties of ZnO thin film to be changed. Thin film of ZnO could change from semiconductor to insulator or conductor depends on types doping element. However, doping using Mg mostly will changed the band gap of thin film. , ZnO is chosen as semiconducting material since it is transparent conducting oxide. At room temperature, it has wide direct band gap with value of 3.37eV that in group II-IV semiconductor. Due to luminescence in visible and near UV range of spectrum, it is widely used in sensors, light emitting diodes or solar cells. The doping element being chosen is Mg because the similarity in ionic radius between Mg and Zn. After thin film of ZnO is doped with Mg, several properties of ZnO thin film is changed. The research shows that the surface of undoped ZnO thin film will contain much void and uniform grain size. However, the surface thin film that doped with Mg is dense and uniform while the void will decreases with concentration of Mg. This shows that there is improved in surface morphology. Sol gel techniques had many advantages compared to other method. Sol gel method requires low sintering temperature (200˚C to 600˚C). It is an economical method as it is low cost and it can be carried out using simple and inexpensive equipment. Sol gel method has the ability to change microstructure of film by changing the pH, temperature and viscosity of sol. This thesis discuss about the sol gel spin coating techniques to produce Mg doped ZnO thin films. Zinc acetate dehydrate, absolute ethanol and diethanolamine used as sol gel precursor while magnesium chloride as source of doping element. Sol gel was coated onto glass slides that wrapped with aluminium foil using spin coated instruments. After that, the thin film was annealing at 400˚C for one hour. The thin films with varying concentration of Mg and spin speed is characterized using XRD, FESEM, PL, UV-Vis and four point probes. Thin films that fabricated with 5 wt% Mg and spin speed of 2000 rpm has better result in term of characterization of XRD and FESEM among all Mg doped ZnO thin films since it has more crystal growth of MgO and it has the best surface morphology with uniform nanoparticles structure eventhough it has moderate transparency and energy band gap. Furthermore, the resistivity of this samples is also higher compared to sample with 5 wt% and 3000 rpm but lower than sample with 10 wt% and 2000 rpm. Sample with 10 wt% and 2000 rpm has the best results among all sample in application pf photonic since the intensity peaks of PL is the highest.

Photovoltaic traffic light system is a significant application of renewable energy source. The develop the system use solar energy as an alternative effort of local authority to reduce expenditure for paying fees to power supplier which the power comes from conventional energy source. Since photovoltaic modules still have relatively low conversion efficiency, An alternative control of maximum power point tracking (MPPT) method applied to the traffic light system. MPPT is intended to catch up the maximum power at daytime in order to charge the battery at the maximum rate in which the power from the battery is intended to be used at night time or cloudy day. MPPT is actually a dc-dc converter that can step up or down of voltage in order to achieve the maximum power using Pulse Width Modulation (PWM) control. In this work, we design a MPPT using Microcontroller PIC16F877. Where this microcontroller will compare the voltage and current from PV system, and convert the new voltage and current to get maximum power output. Based on experiment, we obtained the voltage of operation use MPPT is at 16.454 V, this value had error 2.6%, if we compared with Maximum power point voltage of PV module that is 16.9V, based on this result then this MPPT control work successful to deliver the power from PV module to battery maximally.

Achieving a robust obstacle detection system that can provide a safe avoidance path system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, a combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle regions and free space regions. This is done through the principal of object size changes and distance relationship in an image perspective. The proposed method was evaluated by conducting experiments in a real complex environment which consist of a textured and textureless obstacle. In the experiment conducted, we successfully detect and create a safe avoidance path for both situations. The textured situation gives a high success rate while textureless situation produces acceptable success rate until 60cm distance.

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...

This paper introduces a smartphone-based classification system for an indoor environment of a walking person. The system relies only on smartphone inertial data and it can be considered as a smartphone-based aiding system for an indoor navigation. In addition, it does not need pre-installing of wireless network in the environment or heavily tuning process before the navigation run. Therefore, this system can be used as an aiding block where the person wants to localize himself in an indoor environment starting from known navigations point. This system categorizes person navigation in indoor environment into three types of classes: walking straight, turning right, and turning left. There is an ELM (Extreme Learning Machine)-Based neural network for deciding the class of the current navigation action. The evaluation measure shows that the best performance is obtained with the Radial Basis Function (RBF) as the activation function of the neural network. Also, the obtained accuracy rates up to 95%.

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...

Photovoltaic traffic light system is a significant application of renewable energy source. The development of the system is an alternative effort of local authority to reduce expenditure for paying fees to power supplier which the power comes from conventional energy source. Since photovoltaic (PV) modules still have relatively low conversion efficiency, an alternative control of maximum power point tracking (MPPT) method is applied to the traffic light system. MPPT is intended to catch up the maximum power at daytime in order to charge the battery at the maximum rate in which the power from the battery is intended to be used at night time or cloudy day. MPPT is actually a DC-DC converter that can step up or down voltage in order to achieve the maximum power using Pulse Width Modulation (PWM) control. From experiment, we obtained the voltage of operation using MPPT is at 16.454 V, this value has error of 2.6%, if we compared with maximum power point voltage of PV module that is 16.9 V. Based on this result it can be said that this MPPT control works successfully to deliver the power from PV module to battery maximally.

Quadrotor has emerged as a popular testbed for Unmanned Aerial Vehicle (UAV) research due to its simplicity in construction and maintenance, and its vertical take-off, landing and hovering capabilities. It is a flying rotorcraft that has four lift-generating propellers; two of the propellers rotate clockwise and the other two rotate counter-clockwise. This paper presents modeling and system identification for auto-stabilization of a quadrotor system through the implementation of Extended Kalman Filter (EKF). EKF has known to be typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems. In this paper, two main processes are highlighted; dynamic modeling of the quadrotor and the implementation of EKF algorithms. The aim is to obtain a more accurate dynamic modelby identify and estimate the needed parameters for thequadrotor. The obtained results demonstrate the performances of EKF based on the flight test applied to the quadrotor system.

This paper presents parameters estimation techniques for coupled industrial tanks using the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. Meanwhile, liquid tank systems play important role in industrial application such as in food processing, beverage, dairy, filtration, effluent treatment, pharmaceutical industry, water purification system, industrial chemical processing and spray coating. The aim is to model the coupled tank system using mixed UKF and DE method to estimate the parameters of the tank. First, a non-linear mathematical model is developed. Next, its parameters are identified using mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental data. DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. The obtained results demonstrate good performances.

PurposeThe 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/approachThis 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.FindingsThe 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 performance in compliance with ADS‐33E level 1 specifications.Research limitations/implicationsThe controller is limited to hovering and low‐speed flight envelope.Practical implicationsThis is expected to provide efficient hovering/low‐speed autonomous helicopter flight control required in many civilian unmanned aerial vehicles applications. Also, the technique can be used to simplify the number of robust gain‐scheduled linear controllers required for wide‐envelope flight.Social implicationsThe research will facilitate the deployment of low cost, small‐scale autonomous helicopters in various civilian applications.Originality/valueThe research addresses the challenges of parametric variation inherent in helicopter hovering/low‐speed control using an extended H∞ loop shaping technique with v‐gap metric.

Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, therefore only limited sensor can be attached the vehicle. Usually the sensors incorporated in the system is either type vision based (monocular or stereo camera) or Laser based. However, each of the sensor has its own advantage and disadvantage, thus we built the obstacle detection and avoidance system based multi sensor (monocular sensor and LIDAR) integration. On top of that, we also combine SURF algorithm with Harris corner detector to determine the approximate size of the obstacles. In the initial experiment conducted, we successfully detect and determine the size of the obstacles with 3 different obstacles. The differences of length between real obstacles and our algorithm are considered acceptable which is about -0.4 to 3.6.

Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles.

Anti-swing control is a well-known term in gantry crane control. It is designed to move the payload of gantry crane as fast as possible while the payload swing angle should be kept as small as possible at the final position. A number of studies have proposed anti-swing control using the well-known proportional, integral, derivative (PID) control method. However, PID controllers cannot always effectively control systems with changing parameters. Some studies have also proposed intelligent-based control including fuzzy control. However, the designers often have to face the problem of tuning many parameters during the design to obtain optimum performance. Thus, a lot of effort has to be taken in the design stage. In this paper Fuzzy-tuned PID controller design for anti-swing gantry crane control is presented. The objective is to design a practical anti-swing control which is simple in the design and also robust. The proposed Fuzzy-tuned PID utilizes fuzzy system as PID gain tuners to achieve robust performance to parameters’ variations in the gantry crane. A complex dynamic analysis of the system is not needed. PID controller is firstly optimized in MATLAB using a rough model dynamic of the system which is identified by conducting a simple open-loop experiment. Then, the PID gains are used to guide the range of the fuzzy outputs of the Fuzzy-tuned PID controllers. The experimental results show that the proposed anti-swing controller has satisfactory performance. In addition, the proposed method is straightforward in the design.

This paper presents a method of robust control system design for aircraft flight control systems with the existence of uncertainty parameters such as stability and control derivatives resulted by parameter identification process using real flight test data. A nonlinear model of aircraft turn coordination system is considered where the problem is to find the optimal controller by using the H∞ optimal control method combined with a quasi-Newton optimization method. The present method designs the gain of the cross pass channel for the aileron and rudder interconnect, which causes nonlinearity of the system. The robust controller design is qualified as designing the H∞ optimal control under a given value of the 'nonlinear' gain, and sequentially determining the optimal 'nonlinear' gain subject to minimize the error performance of the turn coordination system by using the quasi-Newton method. The perturbations of the uncertainties model have structured uncertainties constructed by the differences between the aerodynamic coefficients derived by parameter identification process and wind tunnel result. The proposed method is applied to the real flight test data of N250 PA-1 aircraft.

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.

Unmanned Aerial Vehicles (UAV) have a great potential to replace manned aircraft in many tasks or missions. However, in order to allow these UAVs to execute their mission appropriately and especially to deploy them in national or civil airspace, UAVs must have a proper and reliable collision avoidance system. This avoidance system is known as a Sense and avoidance (SAA) system. The purpose of the system is to detect any obstacles either in static or moving condition and respond with proper avoidance maneuvers in order to maintain minimum separation distances. Therefore the research project deals with the development of a unique SAA system which is based on multisensory integration. In particular, it focuses on sensors, processing logic and hardware required on the UAVs to acquire situational awareness. Dissimilar kind of sensors which is optical and laser type is proposed to be employed, so that weaknesses from each individual sensor can be tolerated. Proper logics or algorithm related to the fusion of output from each sensor will also be studied.The combination of Extended KalmanFilter (EKF) and Differential Evolution(DE) method is used for the purpose of development of detection and tracking system which considered to be the main challenges in SAA system development. Subsequently, once the algorithms are put together, including maneuvers avoidance technique algorithm, the developed SAA system will be experimentally tested in order to validate and evaluate the overall capability of the system.

This paper presents the application of the moving horizon states estimation (MHSE) method to estimate the states of nonlinear aircraft equation of motion from a dynamic maneuver’s flight test data. To determine the optimum solution of minimizing the performance index, a Quasi-Newton or gradient method is used. The present method also uses the Armijo’s line search gradient to guarantee the solution/estimation to converge faster to the global optimum estimate. The MHSE method is applied to flight test data of N250 PA-1 aircraft for parameter identification and flight path reconstruction. The result of estimation is also used to evaluate the accuracies of the measurement systems.

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.

The three degree of freedom (3DOF) helicopter is a simplified model, which is used to study the behaviours of the helicopters. It is an example of a so-called underactuated mechanical system that has a fewer control inputs than degrees of freedom. Application of multiple-surface sliding mode control to such model looks attractive, because of the ability of this method to stabilize the underatuated systems and to deal with uncertainties, which usually exist in such systems. In this paper, a multiple-surface sliding mode is proposed to control the elevation and travel angles of the 3DOF helicopter.

In this paper, this design was a Nonlinear Energy-based Control Method (NEM) controller for a Three degree-of-freedom (3 DOF) Helicopter developed by Quanser. It is a control design technique that exploits the energy state of a system to achieve stabilization and/or tracking. There are four stages to design NEM controller, which are: energy-based modeling of helicopter dynamics using Euler-Lagrange formalism; design of the NEM controller based on passivity principle and Lyapunov stability idea; tuning the controller gain(s) to satisfy the design criteria and robustness analysis.

This paper describes one of possible parameter identification approach for a quadrotor. The unknown parameter of the quadrotor will be identified using state estimation method with the implementation of Unscented Kalman Filter (UKF). In the identification of state and parameter for nonlinear dynamic system, UKF has grown to be superior techniques. Two main processes highlighted in this paper are dynamic modeling of quadrotor and the implementation of UKF algorithm. The aim is to identify and estimate the needed parameters for an autonomous quadrotor. The obtained results demonstrate the performance of UKF based on the flight test applied to the quadrotor system.

This paper presents a robust feedback controller design for parametric uncertainty systems via constrained optimization. The proposed controller design employs modern optimization tools (Particle Swarm Optimization and Differential Evolution) in a single objective constrained optimization. The objective of the optimization is to search for a set of robust controller gains such that the stability radius of the closed-loop system is maximized. The constraint of the optimization is a closed-loop poles region which is directly related to the desired time-domain control performance. The proposed controller design is applied to control of pendulum-like systems (gantry crane, flexible joint and inverted pendulum). The results show the robust performance of the designed controller.

One of the major problems associated with H-infinity controller design is the challenges of weighting function parameters' tuning. For a given control problem, it is requires to select appropriate weighting function parameters to satisfy both the stability requirement and time domain specifications. The conflicting nature of these objectives has made such design exercise a tedious endeavor. In this study, the optimal-tuning of the H-infinity controller parameters using multi-objective differential evolution (MODE) technique is proposed, and apply for control of a two-mass-spring system which represents a typical benchmark robust control problem. The performance of the resulting robust controller is evaluated both on the nominal plant and perturbed plants with parameter variation. The simulation results indicate a good compromise between the robustness and time domain performance.

In this paper, the state feedback control design problem for tracking control of a flexible link manipulator is considered. The calculation of state feedback control gains is conventionally handled by pole placement method or LQR method via Riccati equation. Unfortunately, they still possess trial and error approach of choosing some parameters. Particularly, choosing elements of Q and R matrices in the state feedback control using LQR method has to be done by trial. Therefore, an intelligent method to resolve this problem is proposed by adopting PSO algorithm. The experimental work is carried out to evaluate the effectiveness of the proposed method.

PID (proportional+integral+derivative) control is known as simple and easy-to-implement controller. However, the robustness performance is often not satisfactory when dealing with parameter variations of the plant. In addition, its design procedure is not straightforward for the system which is non-SISO (Singe Input Single Output) system like a gantry crane. In this paper, a stable robust PID controller for anti-swing control of automatic gantry crane is proposed. The proposed method employs Genetic Algorithm (GA) in min-max optimization to find the stable robust PID. In the optimization, the robustness of the controller is tested using Kharitonov's polynomials robust stability criterion to deal with parametric uncertainty appears in gantry crane model. For practicality, the model is identified by conducting simple open-loop experiment in the beginning. The experimental results show that a satisfactory robust PID control performance can be achieved. The controller is able to effectively move the trolley of the crane in short time while canceling the swing of the payload for different conditions of payload mass and cable length variations.

Robust control has been studied in recent years as an efficient methodology for the design of highly performing controllers of positioning systems. However, it is necessary to provide accurate nominal model and associated uncertainty bounds to design this type of controllers. The aim of this paper is to robustly identify a single axis high precision positioning system with uncertainties. For a given data set a nominal model is identified then model error modeling techniques are used to handle uncertainties in modeling. To examine the quality of the identified nominal and modeling error models H ∞ is designed based on the identified uncertainties. Computer simulation and experimenting with the high precision positioning system verify that the obtained nominal model and modeling error model are reliable and the implemented approach can be used to develop an integrated identification and robust controller.

In this paper, a novel method for tuning PID controller of automatic gantry crane control using particle swarm optimization (PSO) is proposed. PSO is one of the most recent optimization techniques based on evolutionary algorithm. PSO is also known as computationally efficient method. This work presents in detail how to apply PSO method in finding the optimal PID gains of gantry crane system in the fashion of min-max optimization. The simulation results show that with proper tuning a satisfactory PID control performance can be achieved to drive nonlinear plant. The controller is able to effectively move the trolley of the crane in short time while canceling the swing angle of the payload hanging on the trolley at the end position. The robustness of the controller is also tested.

Gantry cranes are widely used in various applications to transfer a payload from one position to desired position. Gantry crane system is an underactuated system where the number of inputs is less than the number of outputs. When the input signal is given to the actuator, the trolley starts to accelerate whilst causing a swing of payload hanging on a flexible cable. Many researchers have proposed anti-swing controls of gantry crane using PID+PD structure where PID controller is used for trolley positioning control and PD controller is used to dampen the swing oscillation. This is because of the simplicity of PID control structure. Some have combined intelligent methods such as fuzzy and neural networks to improve the performance of the proposed PID control structure. This paper discusses GA-based PID+PD controller tuning for automatic gantry crane system. The discussion is emphasized on the selection of the objective function since the objective function is the key to use the GA (genetic algorithm). The optimized PID gains would be mainly due to the appropriate objective/fitness function. The simulation results show that a good anti-swing control performance can be obtained from the proposed objective function.