Kevin L. Moore

Strange things are afoot in the Buckeye State Across city and country, Ohio echoes with tales of creatures, ghosts, and other unexplained phenomena. A monster that appeared to be half man and half dog and wielding a 2-by-4 terrorized a small Northwest Ohio town during the summer of 1972. Over the years, visitors to a quiet Cincinnati suburb claim to have been accosted by a human-size, leathery frogman lurking near the riverbank. For generations, hikers and hunters have reported seeing Bigfoot throughout forests across Ohio, and some of the most notorious and well-documented UFO encounters on record have taken place here. Authors M. Kristina Smith and Kevin Moore parse urban legends from history as they explore the unnatural side of Ohio's heritage.

The Holy Spirit is not difficult to understand. Unfortunately, what many people believe about the Holy Spirit and miracles isn't in the Bible.I was confused for many years about the Holy Spirit because I sought answers from church leaders, the internet, experiences, and my feelings. They all gave me conflicting answers. Sound familiar? Finally, I did what I should have done from the beginning-open the Bible and study deeply. And what I found surprised me. Perhaps you'll be surprised too In Clouded by Emotion, you'll discover the Bible's answers to your questions about: The identity of the Holy Spirit (who or what?)Baptism with the Holy Spirit (should I ask for this today?)Speaking in tongues (you might be surprised )Being filled with the Holy Spirit (a blessing or a command?)How to listen to the Spirit (it's easier than you think )Miraculous gifts today (which ones are genuine?)And more (so much more )Each of the thirteen chapters ends with discussion questions and access to a short video for Bible classes and personal devotion.Let's study -LanceLance Mosher has a Master's Degree in ministry and has been teaching the Bible privately and publicly in multiple countries since 2009. "Lance moves from student to teacher as he tackles the challenging and beautiful topic of the Holy Spirit's actions in our lives-and does so with grace and an open Bible." -Jeremy Jinkerson, PhDOther books by Lance Mosher: Transformed: A Spiritual Journey (2013), Lance's personal journey of living in the world to learning about the gospel of Jesus Christ.Searching for Brandon Bason (2020), a raw, yet touching coming-of-age novel.

The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem. Additionally, several design methods are given for LTI learning control, incorporating a technique based on parameter estimation and a one-step learning control algorithm for finite-horizon problems. Further chapters focus upon learning control for deterministic nonlinear systems, and a time-varying learning controller is presented which can be applied to a class of nonlinear systems, including the models of typical robotic manipulators. The book concludes with the application of artificial neural networks to the learning control problem. Three specificways to neural nets for this purpose are discussed, including two methods which use backpropagation training and reinforcement learning. The appendices in the book are particularly useful because they serve as a tutorial on artificial neural networks.

This monograph studies the design of robust, monotonically-convergent it- ative learning controllers for discrete-time systems. Iterative learning control (ILC) is well-recognized as an e?cient method that o?ers signi?cant p- formance improvement for systems that operate in an iterative or repetitive fashion (e. g. , robot arms in manufacturing or batch processes in an industrial setting). Though the fundamentals of ILC design have been well-addressed in the literature, two key problems have been the subject of continuing - search activity. First, many ILC design strategies assume nominal knowledge of the system to be controlled. Only recently has a comprehensive approach to robust ILC analysis and design been established to handle the situation where the plant model is uncertain. Second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergencecan be essential. This monograph addresses these two keyproblems by providingauni?ed analysisanddesignframeworkforrobust, monotonically-convergent ILC. The particular approach used throughout is to consider ILC design in the iteration domain, rather than in the time domain. Using a lifting technique, the two-dimensionalILC system, whichhas dynamics in both the time and - erationdomains,istransformedintoaone-dimensionalsystem,withdynamics only in the iteration domain. The so-called super-vector framework resulting from this transformation is used to analyze both robustness and monotonic convergence for typical uncertainty models, including parametric interval - certainties, frequency-like uncertainty in the iteration domain, and iterati- domain stochastic uncertainty.

This monograph studies the design of robust, monotonically-convergent it- ative learning controllers for discrete-time systems. Iterative learning control (ILC) is well-recognized as an e?cient method that o?ers signi?cant p- formance improvement for systems that operate in an iterative or repetitive fashion (e. g. , robot arms in manufacturing or batch processes in an industrial setting). Though the fundamentals of ILC design have been well-addressed in the literature, two key problems have been the subject of continuing - search activity. First, many ILC design strategies assume nominal knowledge of the system to be controlled. Only recently has a comprehensive approach to robust ILC analysis and design been established to handle the situation where the plant model is uncertain. Second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergencecan be essential. This monograph addresses these two keyproblems by providingauni?ed analysisanddesignframeworkforrobust, monotonically-convergent ILC. The particular approach used throughout is to consider ILC design in the iteration domain, rather than in the time domain. Using a lifting technique, the two-dimensionalILC system, whichhas dynamics in both the time and - erationdomains,istransformedintoaone-dimensionalsystem,withdynamics only in the iteration domain. The so-called super-vector framework resulting from this transformation is used to analyze both robustness and monotonic convergence for typical uncertainty models, including parametric interval - certainties, frequency-like uncertainty in the iteration domain, and iterati- domain stochastic uncertainty.