Automatic plant pest detection and recognition using k-means clustering algorithm and correspondence filters

Plant pest recognition and detection is vital for food security, quality of life and a stable agricultural economy. This research demonstrates the combination of the k-means clustering algorithm and the correspondence filter to achieve pest detection and recognition. The detection of the dataset is achieved by partitioning the data space into Voronoi cells, which tends to find clusters of comparable spatial extents, thereby separating the objects (pests) from the background (pest habitat). The detection is established by extracting the variant distinctive attributes between the pest and its habitat (leaf, stem) and using the correspondence filter to identify the plant pests to obtain correlation peak values for different datasets. This work further establishes that the recognition probability from the pest image is directly proportional to the height of the output signal and inversely proportional to the viewing angles, which further confirmed that the recognition of plant pests is a function of their position and viewing angle. It is encouraging to note that the correspondence filter can achieve rotational invariance of pests up to angles of 360 degrees, which proves the effectiveness of the algorithm for the detection and recognition of plant pests

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields

Design and development of intelligent actuator control methodologies for morphing wing in wind tunnel

In order to protect our environment by reducing the aviation carbon emissions and making the airline operations more fuel efficient, internationally, various collaborations were established between the academia and aeronautical industries around the world. Following the successful research and development efforts of the CRIAQ 7.1 project, the CRIAQ MDO 505 project was launched with a goal of maximizing the potential of electric aircraft. In the MDO 505, novel morphing wing actuators based on brushless DC motors are used. These actuators are placed chord-wise on two actuation lines. The demonstrator wing, included ribs, spars and a flexible skin, that is composed of glass fiber. The 2D and 3D models of the wing were developed in XFOIL and Fluent. These wing models can be programmed to morph the wing at various flight conditions composed of various Mach numbers, angles of attack and Reynolds number by allowing the computation of various optimized airfoils. The wing was tested in the wind tunnel at the IAR NRC Ottawa. In this thesis actuators are mounted with LVDT sensors to measure the linear displacement. The flexible skin is embedded with the pressure sensors to sense the location of the laminar-to-turbulent transition point. This thesis presents both linear and nonlinear modelling of the novel morphing actuator. Both classical and modern Artificial Intelligence (AI) techniques for the design of the actuator control system are presented. Actuator control design and validation in the wind tunnel is presented through three journal articles; The first article presents the controller design and wind tunnel testing of the novel morphing actuator for the wing tip of a real aircraft wing. The new morphing actuators are made up of BLDC motors coupled with a gear system, which converts the rotational motion into linear motion. Mathematical modelling is carried out in order to obtain a transfer function based on differential equations. In order to control the morphing wing it was concluded that a combined position, speed and current control of the actuator needs to be designed. This controller is designed using the Internal Model Control (IMC) method for the linear model of the actuator. Finally, the bench testing of the actuator is carried out and is further followed by its wind testing. The infra red thermography and kulite sensors data revealed that on average on all flight cases, the laminar to turbulent transition point was delayed close to the trailing edge of the wing. The second journal article presents the application of Particle Swarm Optimization (PSO) to the control design of the novel morphing actuator. Recently PSO algorithm has gained reputation in the family of evolutionary algorithms in solving non-convex problems. Although it does not guarantee convergence, however, by running it several times and by varying the initialization conditions the desired results were obtained. Following the successful computation of controller design, the PSO was validated using successful bench testing. Finally, the wind tunnel testing was performed based on the designed controller, and the Infra red testing and kulite sensor measurements results revealed the expected extension of laminar flows over the morphing wing. The third and final article presents the design of fuzzy logic controller. The BLDC motor is coupled with the gear which converts the rotary motion into linear motion, this phenomenon is used to push and pull the flexible morphing skin. The BLDC motor itself and its interaction with the gear and morphing skin, which is exposed to the aerodynamic loads, makes it a complex nonlinear system. It was therefore decided to design a fuzzy controller, which can control the actuator in an appropriate way. Three fuzzy controllers were designed each of these controllers was designed for current, speed and position control of the morphing actuator. Simulation results revealed that the designed controller can successfully control the actuator. Finally, the designed controller was tested in the wind tunnel; the results obtained through the wind tunnel test were compared, and further validated with the infra red and kulite sensors measurements which revealed improvement in the delay of transition point location over the morphed wing

Computer-based studies on bioprocess engineering : II - Tools for process operation

In this paper we review recent advances on the practice and theory of process control with particular emphasis to the operation of bioreactors. We present in detail a case-study on the modelling, model-based identification and adaptive control of fed-batch baker's yeast fermentation.Junta Nacional de Investigação Científica e Tecnológica (JNICT) - contract numbers BD/224/90-IF, BD/1476/91-RM.Instituto Nacional de Investigação Científica (INIC)

Advances in PID Control

Since the foundation and up to the current state-of-the-art in control engineering, the problems of PID control steadily attract great attention of numerous researchers and remain inexhaustible source of new ideas for process of control system design and industrial applications. PID control effectiveness is usually caused by the nature of dynamical processes, conditioned that the majority of the industrial dynamical processes are well described by simple dynamic model of the first or second order. The efficacy of PID controllers vastly falls in case of complicated dynamics, nonlinearities, and varying parameters of the plant. This gives a pulse to further researches in the field of PID control. Consequently, the problems of advanced PID control system design methodologies, rules of adaptive PID control, self-tuning procedures, and particularly robustness and transient performance for nonlinear systems, still remain as the areas of the lively interests for many scientists and researchers at the present time. The recent research results presented in this book provide new ideas for improved performance of PID control applications