The concept of feasible & invariant region plays an important role to derive closed loop stability and achie adequate performance of constrained receding horizon predictive control. In this paper, we define a complex polyhedral feasible & invariant set for all stabilizable input-constrained linear systems by using a complex transform and propose a one-norm based receding horizon control scheme using these invariant sets. In order to get a larger stabilizable set, a convex hull of invariant sets which are defined for different state feedback gains is used as a target invariant set of the constrained receding horizon control. The proposed constrained receding horizon control scheme is formulated so that it can be solved via linear programming.

As nonholonomic dynamic systems have constraints imposed on motions that are not integrable, i.e., the constraints cannot be written as time derivatives of some functions of generalized coordinates, advanced techniques are needed for their control. In this paper, a sliding mode tracking control for nonholonomic dynamic systems is proposed. By introducing a general scheme of coordinate transformation, the state of nonholonomic systems is mapped into a bounded space and a robust controller for dynamic models of nonholonomic systems with input disturbances is designed using sliding mode control scheme. Simulation results of tacking control for a nonholonomic mobile robot with two actuated wheels are provided to show the effectiveness of the proposed controller.

A multirate state feedback control (MRSFC) method is proposed for systems sensitive to disturbance and noise based on the multirate estimator design using current estimator. MRSFC updates the controller output slower than the measurement sampling fiequency of system output by a lifting factor $R=T_c/T_s$ The closed-loop MRSFC system is less sensitive to disturbance and noise due to filtering effect than the conventional single-rate control system The multirate estimator gain can be obtained by solving a conventional pole placement problem such that MRSFC has the same spectrum of eigenvalues in the s-plane as the single-rate control. We applied the proposed multirate state feedback controller to a galvanometer servo system Simulation and experimental results show that settling and tracking performances are improved compared with a conventional single-rate pole placement control (PPC).

An objective of Automated Highway Systems (AHS) is to increase the safety and throughput of the existing highway infrastructure by introducing traffic automation. AHS is an example of a large scale, multiagent complex dynamical system and is ideally suited for a hierarchical hybrid controller. We discuss a design issue of efficient hybrid controllers for the platoon maneuvers on AHS. For the modeling of a hybrid system including the merge and split operations, a safety distance policy is introduced for the merge and split operations. After that, the platoon system will be modeled by a hybrid system In addition, a hybrid controller for the proposed merge and split operation models is presented. Finally, the performance of the proposed hybrid control scheme is demonstrated via scenarios for platoon maneuvers.

Since the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different vehicle's operating conditions, high performance control systems of AUVs are needed to have the capacities of teaming and adapting to the variations of the vehicle's dynamics. In this paper, a linearly parameterized neural network (LPNN) is used to approximate the uncertainties of the vehicle dynamics, where the basis function vector of the network is constructed according to the vehicle's physical properties. The network's reconstruction errors and the disturbances in the vehicle dynamics are assumed be bounded although the bound may be unknown. To attenuate this unknown bounded uncertainty, a certain estimation scheme for this unknown bound is introduced combined with a sliding mode scheme. The proposed controller is proven to guarantee that all signals in the closed-loop system are uniformly ultimately bounded (UUB). Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.

The development of the solar and the wind power energy is necessary since the future alternative energies should have no pollution and no limitation. currently power generation system of MW scale has been developed, but it still has a few faults that its operation depends on with the weather condition. In order to solve these existing problems. combined generation system of photovoltaic(400W) and wind power generation system(400W) was suggested. It combines wind power and solar energy to have the supporting effect from each other. However. since the combined generation system cannot always generate stable output with ever-changing weather condition, power compensation device that uses elastic energy of spiral spring was added. In an experiment. when output of system gets lower than 12V(charging voltage), additional power was from the stored rotational energy of spiral spring.

To process data of digital linescan camera, the frame grabber is essential to handle the data in low-level and in high speed more than 30 MHz stably. Traditional approaches to the development of hardware in vision system for the special purpose are mai y based on PC system, and are expensive and gigantic. Therefore, there are many difficulties in applying those in the field. So we investigate, in this paper, the implementation of FPGA for real-time processing of digital linescan camera. The system is not based on PC, but electronic device such as micropncessor. So it is expected that the use of FPGAs for low-level processing represents a fast, stable and inexpensive system. The experiments are carried out on the web guiding system in order to show the efficiency of the new image processor.

It is known that parallel-type mechanisms have many singularities than serial-type mechanisms. In haptic application, these singularities deteriorate the system performance when the haptic system displays the reflecting force. Moreover, different from general manipulators, haptic systems can't avoid the singular point because they are operated by user's random motion command. Although many singularity-free algorithms for serial mechanisms have been proposed and studied. singularity-free algorithms for parallel haptic application have not been deeply discussed. In this paper, various singularity-free algorithms, which are appropriate to parallel haptic system, will be discussedand evaluated.

The problem of generating torch paths for 2D laser cutting of a stock plate nested with a set of free-formed parts is investigated. The objective is to minimize the total length of the torch path starting from a blown depot, then visiting all the given Parts, and retuning back to the depot. A torch Path consists of the depot and Piercing Points each of which is to be specified for cutting a part. The torch path optimization problem is shown to be formulated as an extended version of the standard travelling salesman problem To solve the problem, a hybrid genetic algorithm is proposed. In order to improve the speed of evolution convergence, the algorithm employs a genetic algorithm for global search and a combination of an optimization technique and a genetic algorithm for local optimization. Traditional genetic operators developed for continuous optimization problems are used to effectively deal with the continuous nature of piercing point positions. Computational results are provided to illustrate the validity of the proposed algorithm.

Model-based tuning rules of the PID controller are proposed incorporating with real-coded genetic algorithms. The optimal parameter sets of the PID controller for step set-point tracking are obtained based on the first-order time delay model and a real-coded genetic algorithm as an optimization tool. As for assessing the performance of the controllers, performance indices(ISE, IAE and ITAE) are adopted. Then tuning rules are derived using the tuned parameter sets, potential rule models and another real-coded genetic algorithm A set of simulation works is carried out to verify the effectiveness of the proposed rules.

Sensors need to be implanted to obtain necessary information for LVAS (Left Ventricular Assist System) operations. Size of the sensors can prevent them from being implanted in a patient and reliabilities of the sensors are questionable for a long term use. In this wort we utilize a developed pump model to estimate flow and pressure difference across the pump without implanted sensors and present a method to obtain the physiological variables as aorta pressure and left ventricle pressure from the pump model and pulsatility of flow estimate or pressure difference estimate. These estimated variables can be used for LVAS control as an index or indices.

The system error model for the compensation of the low-cost personal navigation system is derived and the error compensation method using GPS is also proposed. The walking navigation system (WNS) that calculates navigation information through walking detection has small error than INS, but the error also increases with time. In order to improve reliability of the system regardless of time, WNS is integrated with GPS. Since WNS is usually used in urban area, the blockage of CPS signal is frequently occurred. Therefore tightly coupled Kalman filter is used for the integration of WNS and GPS. In this paper, the system model for the design of tightly coupled Kかm filter is designed and measurement is linearized in consideration of moving distance error. It is shown by Monte Carlo simulation that the error is bounded even through the number of visible satellite is less than 4.