Showing papers in "Intelligent Control and Automation in 2013"

Attitude Control of a Quadrotor with Optimized PID Controller

Abstract: A new approach to control, stabilization and disturbance rejection of attitude subsystem of quadrotor is presented in this article. Analytical method is used to tune conventional structure of PID controller. SISO approach is implemented for control structure to achieve desired objectives. The performance of the designed control structure is evaluated through time domain factors such as overshoot, settling time and integral error index, and robustness. A comparison is done between designed controller and back-step controller applied to main model of quadrotor. The results of simulation show the effectiveness of designed control scheme.

Modeling and Adaptive Control of an Omni-Mecanum-Wheeled Robot

Abstract: The complete dynamics model of a four-Mecanum-wheeled robot considering mass eccentricity and friction uncertainty is derived using the Lagrange’s equation. Then based on the dynamics model, a nonlinear stable adaptive control law is derived using the backstepping method via Lyapunov stability theory. In order to compensate for the model uncertainty, a nonlinear damping term is included in the control law, and the parameter update law with σ-modification is considered for the uncertainty estimation. Computer simulations are conducted to illustrate the suggested control approach.

Optimal Seat and Suspension Design for a Half-Car with Driver Model Using Genetic Algorithm

Abstract: This paper presents an optimal vehicle and seat suspension design for a half-car vehicle model to reduce human-body vibration (whole-body vibration). A genetic algorithm is applied to search for the optimal parameters of the seat and vehicle suspension. The desired objective is proposed as the minimization of a multi-objective function formed by the combination of seat suspension working space (seat suspension deflection), head acceleration, and seat mass acceleration to achieve the best comfort of the driver. With the aid of Matlab/Simulink software, a simulation model is achieved. In solving this problem, the genetic algorithms have consistently found near-optimal solutions within specified parameters ranges for several independent runs. For validation, the solution obtained by GA was compared to the ones of the passive suspensions through sinusoidal excitation of the seat suspension system for the currently used suspension systems.

Dynamic Friction Behaviors of Pneumatic Cylinders

Abstract: This paper deals with experimental investigation and modeling of dynamic friction behaviors in the sliding regime of pneumatic cylinders. Using three pneumatic cylinders, friction characteristics are investigated and modeled under various conditions of velocity variation and pressures. It is shown that a hysteretic behavior can be seen at low velocities in the friction force-velocity relation and the friction force varies nearly linearly with the velocity at high velocities. The hysteretic loop is expanded to higher velocities when the frequency of the velocity variation is increased, and its size is increased with increasing driving pressure and is decreased with increasing resistance pressure. It is shown that such behaviors can be relatively accurately simulated by the new modified LuGre model in which a few static parameters are varied with the frequency of velocity variation.

Trajectory Tracking of Quadrotor Aerial Robot Using Improved Dynamic Inversion Method

Abstract: This paper presents trajectory tracking control works concerning quadrotor aerial robot with rigid cross structure. The quadrotor consists of four propellers which are two paired clockwise rotate and anticlockwise rotate. A nonlinear dynamic model of the quadrotor is provided, and a controller based on the improved dynamic inverse is synthesized for the purpose of stabilization and trajectory tracking. The proposed control strategy has been tested in simulation that can balance the deviation of model inaccuracy well.

Sensor Fusion with Square-Root Cubature Information Filtering

Abstract: This paper derives a square-root information-type filtering algorithm for nonlinear multi-sensor fusion problems using the cubature Kalman filter theory. The resulting filter is called the square-root cubature Information filter (SCIF). The SCIF propagates the square-root information matrices derived from numerically stable matrix operations and is therefore numerically robust. The SCIF is applied to a highly maneuvering target tracking problem in a distributed sensor network with feedback. The SCIF’s performance is finally compared with the regular cubature information filter and the traditional extended information filter. The results, presented herein, indicate that the SCIF is the most reliable of all three filters and yields a more accurate estimate than the extended information filter.

Wall Follower Autonomous Robot Development Applying Fuzzy Incremental Controller

Abstract: This paper presents the design of an autonomous robot as a basic development of an intelligent wheeled mobile robot for air duct or corridor cleaning. The robot navigation is based on wall following algorithm. The robot is controlled using fuzzy incremental controller (FIC) and embedded in PIC18F4550 microcontroller. FIC guides the robot to move along a wall in a desired direction by maintaining a constant distance to the wall. Two ultrasonic sensors are installed in the left side of the robot to sense the wall distance. The signals from these sensors are fed to FIC that then used to determine the speed control of two DC motors. The robot movement is obtained through differentiating the speed of these two motors. The experimental results show that FIC is successfully controlling the robot to follow the wall as a guidance line and has good performance compare with PID controller.

Stable and Adaptive Control for Wheeled Mobile Platform

Abstract: Most differential drive platforms are equipped with two independent actuators and casters. The positions of the gravity center and the rotation center often do not coincide. This position difference, combined with the effect of unbalanced actuator dynamics on the motion, makes it difficult to properly control the platform. We propose an adaptive nonlinear controller system based on the Lyapunov stability theory that greatly improves the trajectory tracking performance of such platforms. The asymptotically stable kinematic controller takes into account the position difference and the effect of the unbalanced actuator dynamics. The dynamic controller has the desirable property that it requires minimal knowledge of the platform physical parameters. Validation was performed through simulation and several experiments conducted on a rear driven powered wheelchair. Comparative experimental studies suggested that the proposed adaptive control system performs better than a similar method presented in the literature for linear as well as curvilinear trajectory tracking. Furthermore, the control system exhibits good tracking performance on inclined plans and non smooth surfaces.

Particle Swarm Optimization (PSO) Based Turbine Control

Abstract: The steam turbine control system is strongly non-linear in all operating conditions Proportional-Integral-Derivative (PID) controller that is currently used in control systems of many types of equipment is not considered highly precision for turbine speed control system A fine tuning of the PID controller by some optimization technique is a desired objective to maintain the precise speed of the turbine in a wide range of operating conditions This Paper evaluates the feasibility of the use of Particle Swarm Optimization (PSO) method for determining the optimal Proportional-Integral-Derivative (PID) controller parameters for steam turbine control The turbine speed control is modelled in SimulinkTM with PID controller and the PSO algorithm is implemented in MATLAB to optimize the PID function The PSO optimization technique is also compared with Genetic Algorithm (GA) and it is validated that PSO based controller is more efficient in reducing the steady-states error; settling time, rise time, and overshoot limit in speed control of the steam turbine control

Observer for Linear Distributed-Parameter Systems with Application to Isothermal Plug-Flow Reactor

Abstract: This paper presents a conception of an exponential observer for a class of linear distributed-parameter systems (DPSs), in which the dynamics are partially unknown. The given distributed-parameter observer ensures asymptotic state estimator with exponentially decay error, based on the theory of C0-semigroups in a Hilbert space. The theoretical observer developed is applied to a chemical tubular reactor, namely the isothermal Plug-Flow reactor basic dynamical model for which measurements are available at the reactor output only. The process is described by Partial differential equations with unknown initial states. For this application, performance issues are illustrated in a simulation study.

Decoding Arm Movements by Myoelectric Signal and Artificial Neural Networks

Abstract: The scientific researches in the field of rehabilitation engineering are increasingly providing mechanisms in order to help people with disability to perform simple tasks of day-to-day. Several studies have been carried out highlighting the advantages of using muscle signal in order to control rehabilitation devices, such as experimental prostheses. This paper presents a study investigating the use of forearm surface electromyography (sEMG) signals for classification of several movements of the arm using just three pairs of surface electrodes located in strategic places. The classification is done by an artificial neural network to process signal features to recognize performed movements. The average accuracy reached for the classification of six different movements was 68% - 88%.

H 2 and H ∞ Controller Design of Twin Rotor System (TRS)

Abstract: Control engineering had been the core of all engineering fields all the time. As the name depicts, control of different parameters of various industrial or commercial equipment like plants, vehicles, aircrafts and etc is obtained. Robust and optimal control of these equipments plays a vital role. This paper presents a design of H2 and H∞ control for a Twin Rotor System (TRS). TRS is a multi input multi output (MIMO) nonlinear system. The main objective is to control the angular position of the lever bar of TRS. It is having strong coupling between inputs and outputs. The model is first linearized and then controllers are designed to control the positions of lever bar. Simulations are made in MAT- LAB/SIMULINK. Model parameters are also provided in the end.

Slip Suppression of Electric Vehicles Using Sliding Mode Control Method

Abstract: This paper presents a slip suppression controller using sliding mode control method for electric vehicles which aims to improve the control performance and the energy conservation by controlling the slip ratio of wheel. In this method, a robust sliding mode controller against the model uncertainties is designed to obtain the maximum driving force by suppressing the slip ratio. The numerical simulations for one wheel model under variations in mass of vehicle and road condition are performed and demonstrated to show the effectiveness of the proposed method.

General Concave Integral Control

Abstract: In this paper, a class of fire-new general integral control, named general concave integral control, is proposed. It is derived by normalizing the bounded integral control action and concave function gain integrator, introducing the partial derivative of Lyapunov function into the integrator and originating a class of new strategy to transform ordinary control into general integral control. By using Lyapunov method along with LaSalle’s invariance principle, the theorem to ensure regionally as well as semi-globally asymptotic stability is established only by some bounded information. Moreover, the highlight point of this integral control strategy is that the integrator output could tend to infinity but the integral control action is finite. Therefore, a simple and ingenious method to design general integral control is founded. Simulation results showed that under the normal and perturbed cases, the optimum response in the whole domain of interest can all be achieved by a set of the same control gains, even under the case that the payload is changed abruptly.

Robust Adaptive Neural Network Control for XY Table

Abstract: This paper proposed a robust adaptive neural network control for an XY table. The XY table composes of two AC servo drives controlled independently. The neural network with radial basis function is employed for velocity and position tracking control of AC servo drives to improve the system’s dynamic performance and precision. A robust adaptive term is applied to overcome the external disturbances. The stability and the convergence of the system are proved by Lyapunov theory. The proposed controller is implemented in a DSP-based motion board. The validity and robustness of the controller are verified through experimental results.

An Enhanced Genetic Programming Algorithm for Optimal Controller Design

Abstract: This paper proposes a Genetic Programming based algorithm that can be used to design optimal controllers. The proposed algorithm will be named a Multiple Basis Function Genetic Programming (MBFGP). Herein, the main ideas concerning the initial population, the tree structure, genetic operations, and other proposed non-genetic operations are discussed in details. An optimization algorithm called numeric constant mutation is embedded to strengthen the search for the optimal solutions. The results of solving the optimal control for linear as well as nonlinear systems show the feasibility and effectiveness of the proposed MBFGP as compared to the optimal solutions which are based on numerical methods. Furthermore, this algorithm enriches the set of suboptimal state feedback controllers to include controllers that have product time-state terms.

Cluster Analysis Assisted Float-Encoded Genetic Algorithm for a More Automated Characterization of Hydrocarbon Reservoirs *

Abstract: A genetic algorithm-based joint inversion method is presented for evaluating hydrocarbon-bearing geological formations. Conventional inversion procedures routinely used in the oil industry perform the inversion processing of borehole geophysical data locally. As having barely more types of data than unknowns in a depth, a set of marginally over-determined inverse problems has to be solved along a borehole, which is a rather noise sensitive procedure. For the reduction of noise effect, the amount of overdetermination must be increased. To fulfill this requirement, we suggest the use of our interval inversion method, which inverts simultaneously all data from a greater depth interval to estimate petrophysical parameters of reservoirs to the same interval. A series expansion based discretization scheme ensures much more data against unknowns that significantly reduces the estimation error of model parameters. The knowledge of reservoir boundaries is also required for reserve calculation. Well logs contain information about layer-thicknesses, but they cannot be extracted by the local inversion approach. We showed earlier that the depth coordinates of layerboundaries can be determined within the interval inversion procedure. The weakness of method is that the output of inversion is highly influenced by arbitrary assumptions made for layer-thicknesses when creating a starting model (i.e. number of layers, search domain of thicknesses). In this study, we apply an automated procedure for the determination of rock interfaces. We perform multidimensional hierarchical cluster analysis on well-logging data before inversion that separates the measuring points of different layers on a lithological basis. As a result, the vertical distribution of clusters furnishes the coordinates of layer-boundaries, which are then used as initial model parameters for the interval inversion procedure. The improved inversion method gives a fast, automatic and objective estimation to layer-boundaries and petrophysical parameters, which is demonstrated by a hydrocarbon field example.

Domination in Controlled and Observed Distributed Parameter Systems

Abstract: We consider and we study a general concept of domination for controlled and observed distributed systems. We give characterization results and the main properties of this notion for controlled systems, with respect to an output operator. We also examine the case of actuators and sensors. Various other situations are considered and applications are given. Then, we extend this study by comparing observed systems with respect to a control operator. Finally, we study the relationship between the notion of domination and the compensation one, in the exact and weak cases.

Estimation of Sensitivity of the DS/AHP Method While Solving Foresight Problems with Incomplete Data

Abstract: The paper provides mathematical analysis of sensitivity of different combination rules in the DS/AHP method when an alternative is added to the set of decision alternatives while solving foresight problems. Different cases of rank reversals are defined and two sets of conditions for these cases using the method DS/AHP are considered. Rank reversals are illustrated when the DS/AHP method is used to solve practical problem of critical technologies of energy conservation and power efficiency evaluation in Ukraine. It is shown that the DS/AHP method is not sensitive to exclusion (or addition) of an irrelevant decision alternative from (or to) the set of decision alternatives.

Fault Detection and Isolation in Industrial Systems Based on Spectral Analysis Diagnosis

Abstract: The diagnoses in industrial systems represent an important economic objective in process industrial automation area. To guarantee the safety and the continuity in production exploitation and to record the useful events with the feedback experience for the curative maintenance. We propose in this work to examine and illustrate the application ability of the spectral analysis approach, in the area of fault detection and isolation industrial systems. In this work, we use a combined analysis diagram of time-frequency, in order to make this approach exploitable in the proposed supervision strategy with decision making module. The obtained results, show clearly how to guarantee a reliable and sure exploitation in industrial system, thus allowing better performances at the time of its exploitation on the supervision strategy.

Type-2 Fuzzy Logic Controllers Based Genetic Algorithm for the Position Control of DC Motor

Abstract: Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.

Attitude Control of a Flexible Satellite by Using Robust Control Design Methods

Abstract: The increase of satellite’s dimensions has caused flexibility and formation of uncertainty in their model. This is because of space missions being more complex and using light moving structures in satellites. Satellites are also encountered with various circumferential disturbance torques. This uncertainty in model and disturbance torques will cause undesirable performance of satellites’ attitude control system. So, for attitude control of these satellites, those methods should be used which are robust to uncertainty of the plant’s model and can reject the effects of disturbances and the measurement noise. One of these methods is the robust control design method. But, because of pole’s place of these satellite’s dynamics equations, the designing procedure of robust control will face difficulties. In this paper, by using an internal feedback as a novel idea, the satellite’s dynamics equations are changed in such a way that the poles will be placed in proper locations. Then, for these new equations, by regarding the effects of flexibility as uncertainty and considering the uncertainty in inertia matrix of satellite, an H∞ controller has been designed and for better performance, a μ-controller has been improved. Afterwards, these two controllers are analyzed and compared for the original dynamic equations, not for the modified ones. Also, for comparison, a classic controller has been also designed for the original plant and eventually all these three controllers are compared with each other.

Boundary Control for 2 × 2 Elliptic Systems with Conjugation Conditions

Abstract: In this paper, we consider 2 × 2 non-cooperative elliptic system involving Laplace operator defined on bounded, continuous and strictly Lipschitz domain of Rn. First we prove the existence and uniqueness for the state of the system under conjugation conditions; then we discuss the existence of the optimal control of boundary type with Neumann conditions, and we find the set of equations and inequalities that characterize it.

Increase of Indicator Values of Identification Systems Quality on the Recognition of Human Face on the Basis of Photo Portraits

Abstract: In this paper, algorithms of automatic identification of persons on the basis of their photographs are considered. For identification of persons, the comparative analysis of control systems by bases of images created in the different periods is carried out and their applied possibilities are shown.

Group Method of Data Handling for Modeling Magnetorheological Dampers

Abstract: This paper proposes the use of Group Method of Data Handling (GMDH) technique for modeling Magneto-Rheological (MR) dampers in the context of system identification. GMDH is a multilayer network of quadratic neurons that offers an effective solution to modeling non-linear systems. As such, we propose the use of GMDH to approximate the forward and inverse dynamic behaviors of MR dampers. We also introduce two enhanced GMDH-based solutions. Firstly, a two-tier architecture is proposed whereby an enhanced GMD model is generated by the aid of a feedback scheme. Secondly, stepwise regression is used as a feature selection method prior to GMDH modeling. The proposed enhancements to GMDH are found to offer improved prediction results in terms of reducing the root-mean-squared error by around 40%.

ISPO: A New Way to Solve Traveling Salesman Problem

Abstract: This paper first introduces the concepts of mobile operators and mobile sequence, with which it redefines the rate of particle swarm optimization algorithm and the formula of position updating. Combining this discrete PSO algorithm with neighbors, the paper puts forward Hybrd Particle Swarm Optimization Algorithm, whose effectiveness is verified at the end of this paper.

Generating Recommendation Status of Electronic Products from Online Reviews

Abstract: The need for effective and efficient mining of online reviews cannot be overemphasized. This position is as a result of the overwhelmingly large number of reviews available online which makes it cumbersome for customers to read through all of them. Hence, the need for online web review mining system which will help customers as well as manufacturers read through a large number of reviews and provide a quick description and summary of the performance of the product. This will assist the customer make better and quick decision, and also help manufacturers improve their products and services. This paper describes a research work that focuses on mining the opinions expressed on some electronic products, providing ranks or ratings for the features, with the aim of summarizing them and making recommendations to potential customers for better online shopping. A technique is also proposed for scoring segments with infrequent features. The evaluation results using laptops demonstrate the effectiveness of these techniques.

Daylight Savings Calculation Technique for Smart Buildings

Abstract: This publication presents a technique of quantifying energy savings due to daylight. The technique is designated to be used in smart buildings or similar applications where daylight harvesting is welcomed. The technique is divided into three stages. In the first stage an optical sensor is evaluated for its P (power)-E (illumination) response characteristics. In the second stage the calibration of room properties is carried out. In the final stage photometric calculations are performed, and energy savings are calculated. The major advantage of the proposed approach is to determine energy savings during the design stage of a building, not after the building construction or retrofitting. The information obtained from the calculations is useful for investors, future tenants and environmentalists.

Constant Force Feedback Controller Design Using PID-Like Fuzzy Technique for Tapping Mode Atomic Force Microscopes

Abstract: A novel constant force feedback mechanism based on fuzzy logic for tapping mode Atomic Force Microscopes (AFM) is proposed in this paper. A mathematical model for characterizing the cantilever-sample interaction subsystem which is nonlinear and contains large uncertainty is first developed. Then, a PID-like fuzzy controller, combing a PD-like fuzzy controller and a PI controller, is designed to regulate the controller efforts and schedule the applied voltage of the Z-axis of the piezoelectric tube scanner to maintain a constant tip-sample interaction force during sample-scanning. Using the PID-like fuzzy controller allows the cantilever tip to track sample surface rapidly and accurately even though the topography of the surface is arbitrary and not given in advance. This rapid tracking response facilitates us to observe samples with high aspect ratio micro structures accurately and quickly. Besides, the overshoot which will result in tip crash in commercial AFMs with a traditional PID controller could be avoided. Additionally, the controller efforts can be intelligently scheduled by using the fuzzy logic. Thus, continuous manual gain-tuning by trial and error such as those in commercial AFMs is alleviated. In final, computer simulations and experimental verifications are provided to demonstrate the effectiveness and confirm the validity of the proposed controller.

Dynamic Leveling Control of a Wireless Self-Balancing ROV Using Fuzzy Logic Controller

Abstract: A remotely operated vehicle (ROV) is essentially an underwater mobile robot that is controlled and powered by an operator outside of the robot working environment. Like any other marine vehicle, ROV has to be designed to float in the water where its mass is supported by the buoyancy forces due to the displacement of water by its hull. Vertically positioning a mini ROV in centimeters resolution underwater and maintaining that state requires a distinctive technique partly because of the pressure and buoyance force exerted by the water towards the hull and partly because of the random waves produced by the water itself. That being said, the aim of the project is to design and develop a wireless self-balancing buoyancy system of a mini ROV using fuzzy logic controller. A liquid level sensor has been implemented to provide feedback to the controller. A user-friendly graphical user interface (GUI) has been developed for real-time data monitoring as well as controlling the vertical position of the ROV. At the end of the project, the implemented fuzzy control system shows enhanced and better performance when compared with one without a controller, a proportional-derivative (PD) controller, and a proportional-integral-derivative (PID) controller.