Development of Path Tracking Control Algorithm for a 4 DOF Spatial Manipulator Using PID Controller

The path tracking phenomenon of a robotic manipulator arm plays an important role, when the manipulators are used in continuous path industrial applications, such as welding, machining and painting etc. Nowadays, robotic manipulators are extensively used in performing the said tasks in industry. Therefore, it is essential for the manipulator end effector to track the path designed to perform the task in an effective way. In this chapter, an attempt is made to develop a feedback control method for a 4-DOF spatial manipulator to track a path with the help of a PID controller. In order to design the said controller, the kinematic and dynamic models of the robotic manipulator are derived. Further, the concept of inverse kinematics has been used to track different paths, namely a straight line and parabolic paths continuously. The effectiveness of the developed algorithm is tested on a four degree of freedom manipulator arm in simulations.

Reliability Analysis of Engineering Systems

Nowadays, reliability and reliability-based design in any system has become very important. There are some parts in many systems that designing their test process take too much time and money in order to be analyzed for their reliability. Boilers, as the hearts of plants, contain various components. One of the most important components is Super-heater tubes. Creep failure is the most common failure mode in these tubes which grows faster by increasing the temperature. Accelerated Life Testing (ALT) is used to study the performance of a component under high stress in a short period of time and use of the test result in order to assess the performance of the component under design stress in a desired lifetime. In this chapter, the reliability of Super-heater boiler tubes in plants was examined by applying ALTs. The obtained results indicated that considering the life of components at the beginning of the test, reusing them under the same stress did not exhibit desirable reliability. Furthermore, some recommendations have been suggested to improve the reliability.

Reliability Optimization of Complex Systems Using Cuckoo Search Algorithm

In this chapter, authors briefly discussed about the classification of reliability optimization problems and their nature. Background of reliability and optimization has also been provided separately so that one can clearly understand the basic terminology used in the field of reliability optimization. Classification of various optimization techniques have also been discussed by the authors. Few metaheuristic techniques related to reliability optimization problems like Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been discussed in brief. Thereafter, authors have discussed about Cuckoo Search Algorithm (CSA) which is the main focus of this chapter. Finally, Cuckoo Search Algorithm has been applied for solving reliability optimization problems of two complex systems namely complex bridge system and life support system in space capsule. Simulation results and conclusion have been presented in the last followed by the references.

Effective Optimization of Statistical Decisions for Age Replacement Problems under Parametric Uncertainty

In this chapter, an innovative model for age replacement is proposed. The costs included in the age replacement model are not assumed to be constants. For effective optimization of statistical decisions for age replacement problems under parametric uncertainty, based on a past random sample of lifetimes, the pivotal quantity averaging (PQA) approach is suggested. The PQA approach represents a simple and computationally attractive statistical technique. In this case, the transition from the original problem to the equivalent transformed problem (in terms of pivotal quantities and ancillary factors) is carried out via invariant embedding a sample statistic in the original problem. The approach allows one to eliminate unknown parameters from the problem and to find the better decision rules, which have smaller risk than any of the well-known decision rules. Unlike the Bayesian approach, the proposed approach is independent of the choice of priors. For illustration, numerical examples are given.

Combustion Instability Analysis Using Wavelets in Conventional Diesel Engine

Combustion instability affects the drivability, power, engine performance and efficiency. Elimination of combustion instabilities leads to increase in power for the same fuel economy. Effective controller can reduce combustion instabilities by understanding patterns in the cyclic variations. In this study, cyclic variations of combustion parameters were analyzed in a diesel engine using wavelet analysis. The experiments were conducted at varying loads and compression ratios at 1500 rpm. At steady state condition, cylinder pressure data of 2000 consecutive combustion cycles was measured. Continuous Wavelet Transform was used to capture non-stationary or transient features that might not have been detected using other transforms. Wavelet Power Spectrum (WPS) and Global Wavelet Spectrum were further used to determine the relationship between fluctuations in combustion parameters. Contour Plots were plotted based on WPS for visualizing the intensity and frequency of cyclic Variations. It was found that cyclic variability decreases with increase in engine load and compression ratio.

Journey from Order to Chaos and Returning

In this chapter, different aspects have been described to investigate the ecological system with respect to several factors that may be responsible for emergence of complex behaviors. Some mathematical models incorporate time delay(s) such as delay due to maturation, gestation and other kinds of negative feedback. These nonlinear delay models have led to complexities in the system. The emphasis is to explore the complex dynamical behaviors including chaos in ecological models with respect to different control parameters. Motivation behind synchronization and stabilization of chaos in the system has also been emphasized. Hence, in this chapter attempts have been made to study order and chaos in variety of models applicable to multi-species ecological systems. Such a study is important since the ecological systems have all the necessary ingredients to be able to support chaos. The attempt is made to brief different mechanism that may bring order into chaotic systems or vice versa.

Development of a Material Constitutive Model and Simulation Technique to Predict Nonlinearities in Piezoelectric Materials under Weak Electric Fields

Piezoceramic materials exhibit different types of nonlinearities depending upon the magnitude of the mechanical and electric field strength in the continuum. Some of the nonlinearities observed under weak electric fields are: presence of superharmonics in the response spectra and jump phenomena etc. especially if the system is excited near resonance. It has also been observed by many researchers that, at weak alternating stress fields, the relationship between the piezoelectrically induced charge and applied stress in ferroelectric ceramics, has the same form as the Rayleigh law (for magnetization versus magnetic field) in ferromagnetic materials. Applicability of the Rayleigh law to the piezoelectric effect has been demonstrated for Lead Zirconate Titanate ceramics by many researchers and their experimental results indicate that the dominant mechanism responsible for piezoelectric hysteresis and the dependence of the piezoelectric coefficient on the applied alternating stress is the pinning of non-180° domain walls. In this chapter, the Rayleigh law for ferromagnetic hysteresis has been modified and incorporated in a nonlinear electric enthalpy function and then applied in the analysis of hysteresis behavior of piezoelectric continua. Analytical solutions have been derived for a cantilever beam actuated by two piezo-patches attached to the top and bottom of the beam and excited by opposite electric fields. Analysis has been carried out at different electric field excitations of varying amplitude and frequencies and the results have been compared with the available experimental results from literature.

Welding Process under Fault Coverage Approach for Reliability and MTTF

This chapter deals with the problems occur in the welding under the consideration of many causes of defects such as cracking, distortion, porosity, inclusion and undercutting. Welding is very useful for every industry. It is used as a fabrication and sculptural that joins the two parts of materials, generally metals or thermoplastic, through a restricted amalgamation from a suitable combination of temperature, pressure and metallurgical conditions. In this chapter, authors study that the welding process is how much reliable when many causes of defects taken account into this process and try to find out the reliability and mean time to failure of welding process with the help of Markov modelling and supplementary variable technique. They derived the generalised expression for the probability of each possible transition state, probability of upstate and downstate of welding, and also studied the sensitivity in reliability and MTTF of welding. Fault coverage technique has been developed to enhance the reliability of the welding process for practical utility in the industry.

Monte Carlo Simulation for Reliability-Based Design of Automotive Complex Subsystems

Design and production of high reliable and safer systems with longer life has been a challenge because of high competitive market and recent safety issues of reputable car manufacturers. In this chapter, a methodology is introduced for reliability based design of automotive system. FMEA results are used in the process of failure rate estimation. The basic failure data are adjusted by multiplicative corrective factors to account for the design and environment impacts on system failure characteristics. The system is modeled by reliability block diagram (RBD) method, simulated by an efficient Monte Carlo method. According to the results of FMEA and reliability evaluation, the structure of system is improved by reducing the components failure rates and potential change of system configuration. The components' reliability is improved by increasing the quality of components by utilization of high quality materials and modern manufacturing techniques. The results showed the failure rate improvement for friction lining component in dry friction clutch system.

Design Optimization of a Wind Turbine Using Artificial Intelligence

This chapter examines the capability of Support Vector Machine (SVM), Relevance Vector Machine (RVM) and Genetic Programming (GP) for the optimal design of wind turbine. The excellent design has been influenced by various factors, such as profile of the blade, number of blades, power factor and tip speed ratio. The key to design a wind turbine is to Assessing the optimal tip speed ratio (TSR) is the key for designing the wind turbine. This chapter handles the Artificial Intelligence techniques in predicting the optimal TSR and the power factor based on the parameters engaged for NACA 4415 and LS-1 profile types with 3 and 4 blades. The organized machine learning framework is anticipated to be lucrative than the traditional way in foretelling the TSR and power factor. The machine learning models are then compared with the existing Neural Network model and the pros and cons of the various models are inferred from the results.