The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust $H_\infty$ control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities, due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

The guaranteed cost control problem for a class of linear systems with norm-bounded time-varying parameter uncertainties and input constraints is considered. A sufficient condition for the existence of guaranteed cost state feedback controllers is derived via the linear matrix inequality (LMI) approach, and a design procedure to guaranteed cost controllers is given. Furthermore, a convex optimization problem is formulated to determine the optimal guaranteed cost controller. An example is given to illustrate the effectiveness of the proposed results.

Nowadays, versatile robots are developed around the world. Novel algorithms are needed for controlling such robots. A 2-Layer fuzzy controller can deal with many inputs as well as many outputs, and its overall structure is much simpler than that of a general fuzzy controller. The main problem encountered in fuzzy control is the design of the fuzzy controller. In this paper, the fuzzy controller is designed by the schema co-evolutionary algorithm. This algorithm can quickly and easily find a global solution. Therefore, the schema co-evolutionary algorithm is used to design a 2-layer fuzzy controller in this study. We apply it to a mobile robot and verify the efficacy of the 2-layer fuzzy controller and the schema co-evolutionary algorithm through the experiments.

This paper discusses an output-tracking control design method for Takagi-Sugeno fuzzy systems with parametric uncertainties. We first represent the concerned system as a set of uncertain linear systems. The tracking problem is then converted into a stabilization problem thereby leading to a more feasible control design procedure. A sufficient condition for robust practical output tracking is derived in terms of a set of linear matrix inequalities. A numerical example for a flexible-joint robot-arm model has been demonstrated, to convincingly show effectiveness of the proposed system modeling and control design.

This paper considers eigenstructure assignment in high-order linear systems via proportional plus derivative feedback. It is shown that the problem is closely related with a type of so-called high-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two complete parametric methods for the proposed eigenstructure assignment problem are presented. Both methods give simple complete parametric expressions for the feedback gains and the closed-loop eigenvector matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically very simple and reliable; the second one utilizes the right factorization of the system, and allows the closed-loop eigenvalues to be set undetermined and sought via certain optimization procedures. An example shows the effect of the proposed approaches.

A general construction algorithm of the Grassmann space parameters in linear systems - so-called, the Plucker matrix, 'L' in m-input, p-output, n-th order static output feedback systems and the Plucker matrix, $'L^{aug}'$ in augmented (m+d)-input, (p+d)-output, (n+d)-th order static output feedback systems - is presented for numerical checking of necessary conditions of complete static and complete minimum d-th order dynamic output feedback pole-assignments, respectively, and also for discernment of deterministic computation condition of their pole-assignable real solutions. Through the construction of L, it is shown that certain generically pole-assignable strictly proper mp > n system is actually none pole-assignable over any (real and complex) output feedbacks, by intrinsic rank deficiency of some submatrix of L. And it is also concretely illustrated that this none pole-assignable mp > n system by static output feedback can be arbitrary pole-assignable system via minimum d-th order dynamic output feedback, which is constructed by deterministic computation under full­rank of some submatrix of $L^{aug}$.

A new scheme for a mobile robot to track and capture a moving object using camera images is proposed. The moving object is assumed to be a point-object and is projected onto an image plane to form a geometrical constraint equation that provides the position data of the object based on the kinematics of the active camera. Uncertainties in position estimation caused by the point-object assumption are compensated for using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. In this paper, the experimental results of the tracking and capturing of a target object with the mobile robot are presented.

In this paper, a prototype Cartesian Parallel Manipulator (CPM) is demonstrated, in which a moving platform is connected to a fixed frame by three PRRR limbs. Due to the orthogonal arrangement of the three prismatic joints, it behaves like a conventional X-Y-Z Cartesian robot. However, because all the linear actuators are mounted at the fixed frame, the manipulator may be suitable for applications requiring high speed and accuracy. Using a geometric method and the practical assumption that three revolute joint axes in each limb are parallel to one another, a simple forward kinematics for an actual model is derived, which is expressed in terms of a set of linear equations. Based on the error model, two calibration methods using full position and length measurements are developed. It is shown that for a full position measurement, the solution for the calibration can be obtained analytically. However, since a ball-bar is less expensive and sufficiently accurate for calibration, the kinematic calibration experiment on the prototype machine is performed by using a ball-bar. The effectiveness of the kinematic calibration method with a ball-bar is verified through the well­known circular test.

This paper proposes a wheel-assembly automation system, which assembles a wheel into a hub of a vehicle hung to a moving hanger in a car manufacturing line. A macro-micro manipulator control strategy is introduced to increase the system bandwidth and tracking accuracy to ensure insertion tolerance. A camera is equipped at the newly designed wheel gripper, which is attached at the center of the end-effector of the macro-micro manipulator and is used to measure position error of the hub of the vehicle in real time. The redundancy problem in the macro-micro manipulator is solved without complicated calculation by assigning proper functions to each part so that the macro part tracks the velocity error while the micro part regulates the fine position error. Experimental results indicate that tracking error satisfies the insertion tolerance of assembly $({\pm}1mm)$, and thus it is verified that the proposed system can be applied to the wheel assembly task on a moving hanger in the manufacturing line.

Performance of a force-torque sensor is affected significantly by an error signal that is included in the sensor signal. The error sources may be classified mainly into two categories: one is a structural error due to inaccuracy of sensor body, and the other is a noise signal existing in sensed information. This paper presents a principle of 6-axis force-torque sensor briefly, a double-hole structure to be able to improve a structural error, and then a signal conditioning to reduce the effect of a noise signal. The validity of the proposed method is investigated through experimental study, which shows that SIN ratio is improved significantly in our experimental setup, and the sensor can be implemented cheaply with reasonable performance.

This paper is concerned with the development of a micro tensile testing machine for optically functional materials such as single or poly crystalline silicon and nickel film. This micro tensile tester has been developed for testing various types of materials and dimensions. PZT type actuation is utilized for precise displacement control. The specifications of the PZT actuated micro tensile testers developed are as follows: the volumetric size of the tester is desktop type of 710mm' 200mm' 270mm; the maximum load capacity and the load resolution in this system are IKgf and 0.0152mgf respectively and; the full stroke and the stoke resolution of the PZT actuator are $1000{\mu}m$ and 10nm respectively. Special automatic specimen installing and setting equipment is applied in order to prevent unexpected deformation and misalignment of specimens during handling of specimens for testing. Nonlinearity of the PZT actuator is compensated to linear control input by an inverse compensation method that is proposed in this paper. The strain data is obtained by ISDG method that uses the laser interference phenomenon. To test the reliance of this micro tensile testing machine, a $200{\mu}m$ thickness nickel thin film and SCS (Single Crystalline Silicon) material that is made with the MEMS fabrication process are used.

A practical recursive WLS (weighted least squares) algorithm is proposed to estimate relative range using LOS (line-of-sight) information for ASM (anti-ship missile) application. Apart from the previous approaches based on the EKF (extended Kalman filter), to ensure good convergence properties in long range engagement situations, the proposed scheme utilizes LOS rate measurements instead of conventionally used LOS angle measurements. The estimation error property for the proposed filter is investigated and a simple error compensator is devised to enhance its estimation error performances. Simulation results indicate that the proposed filter produces very accurate range estimates with extremely small computations.

A power plant simulation tool ('PowerSim') has been developed with 10 years experience from the development of a plant simulator for efficient modeling of a power plant. PowerSim is the first developed tool in Korea for plant simulation with various plant component models, instructor station function and the Graphic Model Builder (GMB). PowerSim is composed of a graphic editor using general purpose design software, a netlist converter, component models, the scheduler, Instructor Station and an executive. The graphic editor generates a netlist that shows the connection status of the various plant components from the Simdiagram, which is drawn by Icon Drag method supported by GUI environment of the PowerSim. Netlist Converter normalizes the connection status of the components. Scheduler makes scheduling for the execution of the device models according to the netlist. Therefore, the user makes Simdiagram based on the plant Pipe and Instrument Drawing (P&ID) and inputs the plant data for automatic simulating execution. This paper introduces Graphic Model Builder (GMB), instructor station, executive and the detailed introduction of thermal-hydraulic modeling. This paper will also introduce basic ideas on how the simulation Diagram, based on netlist generated from general purpose design software, is made and how the system is organized. The developed tool has been verified through the simulation of a real power plant.

The dual-mode strategy has been adopted in many constrained MPC (Model Predictive Control) methods. The size of stabilizable regions of states of MPC methods depends on the size of underlying feasible and positively invariant sets and the number of control moves. The results, however, may perhaps be conservative because the definition of positive invariance does not allow temporal departure of states from the set. In this paper, a concept of periodic invariance is introduced in which states are allowed to leave a set temporarily but return into the set in finite time steps. The periodic invariance can be defined with respect to sets of different state feedback gains. These facts make it possible for the periodically invariant sets to be considerably larger than ordinary invariant sets. The periodic invariance can be defined for systems with polyhedral model uncertainties. We derive a MPC method based on these periodically invariant sets. Some numerical examples are given to show that the use of periodic invariance yields considerably larger stabilizable sets than the case of using ordinary invariance.