This article introduces recent trends in RHC (Receding Horizon Control), also known as MPC (Model Predictive Control), that has been well recognized in industry and academy as a systematic approach for optimal design and constraint management. Constrained and robust RHCs will be briefly reviewed with milestone results. Among the diverse developments and achievements of RHCs, implementation issues will be focused on, together with the latest applications. In particular, this article introduces results on how to solve a finite horizon open-loop optimal control problem in an efficient way, together with code generation for real-time execution and easy implementation. Instead of traditional applications such as refineries and petrochemical plants, this article highlights some selected emerging applications, such as energy management systems and mechatronics, that have resulted from state-of-the-art high performance computing power and advanced numerical schemes.

Referring to various definitions, we first examine the identity issue of intelligent control and, have tried to explain the nature and attributes of intelligent control in terms of two categories of positions, that is, the Noumenalist's position and the Phenomenologist's position. And then, we give detailed descriptions for (1) FUZZY-based intelligent control and (2) learning control. Finally, as a noticeable new technique of intelligent control for robotic applications, we present (3) Cognitive control.

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

This survey paper reviews robust control problems in both frequency domain and time domain. Robust control is focused on model uncertainties such as modeling error, system parameter variations, and disturbances. Robust control design problems are discussed according to parameter uncertainty, polytopic uncertainty, and norm-bounded uncertainty. Nowadays, robust control theory is combined with various control theory such as model predictive control, adaptive control, intelligent control, and time delay control.

This article reviews various state estimation methods for nonlinear systems, particularly with a perspective of a process control engineer. Nonlinear state estimation methods can be classified into the following two categories: stochastic approaches and deterministic approaches. The current review compares the Bayesian approach, which is mainly a stochastic approach, and the MHE (Moving Horizon Estimation) approach, which is mainly a deterministic approach. Though both methods are reviewed, emphasis is given to the latter as it is particularly well-suited to highly nonlinear systems with slow sampling rates, which are common in chemical process applications. Recent developments in underlying theories and supporting numerical algorithms for MHE are reviewed. Thanks to these developments, applications to large-scale and complex chemical processes are beginning to show up but they are still limited at this point owing to the high numerical complexity of the method.

This article surveys the control theoretic study on time delay systems. Since time delay systems are infinite dimensional, there are not analytic but numerical solutions on almost analysis and synthesis problems, which implies that there are a tremendous number of approximated solutions. To show how to find such solutions, several results are summarized in terms of two different axes: 1) theoretic tools like integral inequality associated with the derivative of delay terms, Jensen inequality, lower bound lemma for reciprocal convexity, and Wirtinger-based inequality and 2) various candidates for Laypunov-Krasovskii functionals.

This paper describes control applications in automobiles. Many aspects of automotive applications of advanced control methods, which include suspension systems, stability control systems, engines, hybrid vehicle control systems, electric vehicle controls systems, advanced driver assistance systems and automated driving control systems, are reviewed. The control methods used in each area are briefly reviewed to help readers understand the applicability and effectiveness of these methods. In addition, some new trends in the research of automotive applications are described.

This paper is to survey and put in perspective the working methods of multi-target tracking in clutter. This paper includes theories and practices for data association and related filter structures and is motivated by increasing interest in the area of target tracking, security, surveillance, and multi-sensor data fusion. It is hoped that it will be useful in view of taking into consideration a full understanding of existing techniques before using them in practice.

Stepper motor is widely used in positioning applications due to its durability and high torque to inertia ratio as well as low cost and ability to be easily controlled with open-loop. Due to increased resolution of position control and improved stability of motion control, microstepping has drawn attention in industry since it was introduced in 1970s. With the increase in computational power and decrease in cost of embedded processors in recent years, drives and control systems for stepper motors have become more sophisticate than ever. Thus, closed-loop control methods have been developed to improve the performance of the stepper motors. In this paper, we review not only basic principles of conventional control methods used for stepper motors but also that of microstepping control. In addition, we surveyed recent development in nonlinear control methods applied to stepper motors. The nonlinear control methods are presented in the view of Lyapunov stability. Nonlinear torque disturbance observer, sliding mode control, and nonlinear phase compensation are also presented.

This is the survey paper on the role of kinematics in robot development. The robot is considered as a form of mechanical systems which includes closed-chain loop system, open-chain loop system and closed and open switching system. To analyze these systems, kinematic notations has been developed in kinematics of mechanical theory since 1955 and has been applied in robotics. Several kinematic notations including Denavit-Hartenberg notations have been reviewed. The status of development of the spherical motor which has a great impact on the future robot advancement has reviewed, and research activity on a spherical motor and its application to 3-D spatial mechanisms at UNIST is introduced. For the open and closed switching mechanical systems, the bipedal robots' walking theories using Zero Moment Point are reviewed. And current status regarding bipedal robots based on newly developed passive dynamic walking theory is reviewed with the research activity at UNIST on this subject.

Since the beginning of the 21st century, emergence of innovative technologies in robotic and telepresence surgery has revolutionized minimally access surgery and continually has advanced them till recent years. One of such surgeries is endoscopic surgery, in which endoscope and endoscopic instruments are inserted into the body through small incision or natural openings, surgical operations being carried out by a laparoscopic procedure. Due to a vast amount of developments in this technology, this review article describes only a technological state-of-the arts and trend of endoscopic robots, being further limited to the aspects of key components, their functional requirements and operational procedure in surgery. In particular, it first describes technological limitations in developments of key components and then focuses on the description of the performance required for their functions, which include position control, tracking, navigation, and manipulation of the flexible endoscope body and its end effector as well, and so on. In spite of these rapid developments in functional components, endoscopic surgical robots should be much smaller, less expensive, easier to operate, and should seamlessly integrate emerging technologies for their intelligent vision and dexterous hands not only from the points of the view of surgical, ergonomic but also from safety. We believe that in these respects a medical robotic technology related to endoscopic surgery continues to be revolutionized in the near future, sufficient enough to replace almost all kinds of current endoscopic surgery. This issue remains to be addressed elsewhere in some other review articles.

This paper covers improvement of the humanoid robot platform HUBO2, known as the HUBO2+. As a necessity of the growth of the humanoid platform, a robust, reliable and user friendly platform is needed. From this standpoint, HUBO2+ is the most improved humanoid robot platform in the HUBO series. The mechanical design has been changed to increase the movable range and to stop joint compulsion. Additionally, all of the electrical parts are re-designed to be un-breakable in an unexpected situation. A smart power controller with robot status check panel is attached on the back. Additionally, a diagnosis tool, the HUBO-i, has been developed. Moreover, each joint motor controller of HUBO2+ has a Protection Function and a PODO system is provided for handling the robot easily.

The purpose of this paper is to review recent developments in lower limb exoskeletons. The exoskeleton system is a human-robot cooperation system that enhances the performance of the wearer in various environments while the human operator is in charge of the position control, contextual perception, and motion signal generation through the robot's artificial intelligence. This system is in the form of a mechanical structure that is combined to the exterior of a human body to improve the muscular power of the wearer. This paper is followed by an overview of the development history of exoskeleton systems and their three main applications in military/industrial field, medical/rehabilitation field and social welfare field. Besides the key technologies in exoskeleton systems, the research is presented from several viewpoints of the exoskeleton mechanism, human-robot interface and human-robot cooperation control.

This paper surveys past and state-of-the-art SLAM technologies. The standard methods for solving the SLAM problem are the Kalman filter, particle filter, graph, and bundle adjustment-based methods. Kalman filters such as EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter) have provided successful results for estimating the state of nonlinear systems and integrating various sensor information. However, traditional EKF-based methods suffer from the increase of computation burden as the number of features increases. To cope with this problem, particle filter-based SLAM approaches such as FastSLAM have been widely used. While particle filter-based methods can deal with a large number of features, the computation time still increases as the map grows. Graph-based SLAM methods have recently received considerable attention, and they can provide successful real-time SLAM results in large urban environments.