In discrete-time controlled system, sampling time is one of the critical parameters for control performance. It is useful to employ different sampling rates into the system considering the feasibility of measuring system or actuating system. The systems with the different sampling rates in their input and output channels are named multirate system. Even though the original continuous-time system is time-invariant, it is realized as time-varying state equation depending on multirate sampling mechanism. By means of the augmentation of the inputs and the outputs over one period, the time-varying system equation can be constructed into the time-invariant equation. The two multirate formulations have some trade-offs in the simplicity to construct the controller, the control performance. It is good issue to determine the suitable formulation in consideration of performance of them. In this paper, the two categories of multirate formulations will be compared in terms of the linear quadratic (LQ) cost function. The results are used to select the multirate formulation and the sampling rates suitable to the desired control performance.

In discrete-time controlled system, sampling time is one of the critical parameters for control performance. It is useful to employ different sampling rates into the system considering the feasibility of measuring system or actuating system. The systems with the different sampling rates in their input and output channels are named multirate system. Even though the original continuous-time system is time-invariant, it is realized as time-varying state equation depending on multirate sampling mechanism. By means of the augmentation of the inputs and the outputs over one Period, the time-varying system equation can be constructed into the time-invariant equation. In this paper, an alternative time-invariant model is proposed, the design method and the stability of the LQG (Linear Quadratic Gaussian) control scheme for the realization are presented. The realization is flexible to construct to the sampling rate variations, the closed-loop system is shown to be asymptotically stable even in the inter-sampling intervals and it has smaller computation in on-line control loop than the previous time-invariant realizations.

The present paper is concerned with the robust decentralized stabilization problem of large-scale systems with time delays in the interconnections using sliding mode control. Based on Lyapunov stability theorem and H$_{\infty}$ theory, an existence condition of the sliding mode and a robust decentralized sliding mode controller are newly derived for large-scale systems under mismatched uncertainties. Finally, a numerical example is given to verify the validity of the results developed in this paper.

A real-time control system, composed of the controlled processor and the controller computer(s), may have a variety of task types, some of which have tight timing-constraints in generating the correct control input. The maximum period of those task failures tolerable by the system is called the hard deadline, which depends on not only fault characteristics but also task characteristics. In the paper, we extend a method deriving the hard deadline in LTI system executing single task. An algorithm to combine the deadlines of all the elementary tasks in the same operation-mode is proposed to derive the hard deadline of the entire system. For the end, we modify the state equation for the task to capture the effects of task failures (delays in producing correct values) and inter-correlation. We also classify the type of executing the tasks according to operation modes associated with relative importance of correlated levels among tasks, into series, parallel, and cascade modes. Some examples are presented to demonstrate the effectiveness of the proposed methods.

In this paper, an integrated nonlinear sliding mode observer and controller has been designed in order to control of an automotive engine idle speed. The primary objective of the engine idle speed control is to maintain the desired engine idle speed despite of various torque disturbances via estimating air mass flow at the location of the injector in intake manifold by using a sliding mode observer. Simulation results show that the case where both throttle angle and ignition time are used as control inputs outperforms the case where just only throttle angle is used as a control input.

비행시험을 통해 획득한 데이터의 해석과정에서 대상 항공기의 크기가 소형인 경우에는 엔진진동이나 외부의 교란에 의한 잡음이나 바이어스 등의 강도가 높기 때문에 데이터의 처리과정에서 많은 문제점을 산출하게 된다. 이와 같은 문제점을 해결하기 위해 상태추정 알고리즘이 사용되며, 본 논문에서는 항공기의 비선형 세로운동 방정식의 경우에 확장형 칼만 필터를 적용하여 항공기 세로운동의 상태변수들을 추정하였으며, 또한 확률근사과정, 이노베이션에 대한 궤환 적응 등 적응형 칼만 필터를 사용하여 수렴속도와 정확도 둥을 향상시킨 알고리즘을 제안하고 그 결과를 나타내었다.

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

In this paper, we propose an optimal algorithm for finding the shortest connection of two kinds of parts to pairs. If total part numbers are of size N, then there are order 2ㆍ(N/2)$^{N}$ possible solutions, of which we want the one that minimizes the energy function. The appropriate dynamic rule and parameters used in network are proposed by a new energy function which is minimized when 3-constraints are satisfied. This dynamic nile has three important parameters, an enhancement variable connected to pairs, a normalized distance term and a time variable. The enhancement variable connected to pairs have to a perfect connection of two kinds of parts to pairs. The normalized distance term get rids of a unstable states caused by the change of total part numbers. And the time variable removes the un-optimal connection in the case of distance constraint and the wrong or not connection of two kinds of parts to pairs. First of all, we review the theoretical basis for Hopfield model and present a new energy function. Then, the connection matrix and the offset bias created by a new energy function and used in dynamic nile are shown. Finally, we show examples through computer simulation with 20, 30 and 40 parts and discuss the stability and feasibility of the resultant solutions for the proposed connection algorithm.m.

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which complex global intelligence form from simple local interactions. Here, we propose an architecture of neural network learning with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigate in a group. As the results of the simulations, the optimum weight is obtained in real time, which not only prevent the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

This paper presents an optimization algorithm for a stable Self Dynamic Neural Network(SDNN) using genetic algorithm. Optimized SDNN is applied to a problem of controlling nonlinear dynamical systems. SDNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real-time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDW has considerably fewer weights than DNN. Since there is no interlink among the hidden layer. The object of proposed algorithm is that the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed optimized SDNN considering stability is demonstrated by case studies.

In this paper, a precise sensitivity measurement system of ultrasonic transducer in the frequency range from 1 MHz to 15 MHz, which can implement the reciprocity principle is constructed. All of the elements of this system such as the ultrasonic preamplifier, ultrasonic absorber, water tank, water degassing system, and four-axes translator and reflector are constructed. For the performance evaluation of the calibration system, a standard hydrophone precisely calibrated from PTB(Physikalisch Technische Bundesanstalt) in Germany are used. And the system parameters which affected the evaluation of the measurement accuracy and the reproducibility in various measuring conditions are considered. The measurement uncertainty of the calibration system is estimated within $\pm$ 2.0㏈.

Springs have been employed in a wide range of mechanical systems. This work deals with the concept of an adaptable spring mechanism which can arbitrarily modulate its spring characteristics. The adaptable spring is desired for enhancing performances of various mechanical systems employing springs. We demonstrate that such adaptable springs can be realized by adapting anthropomorphic musculoskeletal structures of the human upper-extremity, which possesses highly nonlinear kinematic-coupling among redundant muscles existing in its structures. This phenomenon has been explained by several human arm models. Based on the analysis results, we propose multi-degree-of-freedom spring mechanisms resembling the musculoskeletal structure of the human upper-extremity, and verifiy the applicability of these mechanisms through simulation.

The position control accuracy of a robot arm is significantly deteriorated when a long slender arm robot is operated at a high speed. In this case, the robot arm needs to be modeled as a flexible structure, not a rigid one, and its control system needs to be designed with its elastic modes taken into account. In this paper, the vibration control scheme of a one-link flexible manipulator using adaptive input shaper in conjunction with PID controller is presented. The robot consists of a flexible arm manufactured with a thin aluminium plate, an AC servo motor with a harmonic drive for speed reduction, an optical encoder and an accelerometer. On-line identification of the vibration mode is done using the pruned decimation-in-time FFT algorithm to estimate the parameter of the input shaper. Experimental results of the flexible manipulator with a PID controller and input shaper are provided to show the effectiveness of the advocated controllers.

In this paper, we propose visual-based self-localization and obstacle detection algorithms for indoor mobile robots. The algorithms do not require calibration, and can be worked with only single image by using the projective invariant relationship between natural landmarks. We predefine a risk zone without obstacles for a robot, and update the image of the risk zone, which will be used to detect obstacles inside the zone by comparing the averaging image with the current image of a new risk zone. The positions of the robot and the obstacles are determined by relative positioning. The method does not require the prior information for positioning robot. The robustness and feasibility of our algorithms have been demonstrated through experiments in hallway environments.

Flight parameters of a light aircraft in normal category named ChangGong-91 we identified from flight tests. Modified Maximum Likelihood Estimation (MMLE) is used to produce aerodynamic coefficients, stability and control derivatives. A Flight Training Device (FTD) has been developed based on the identified flight parameters. Flat earth, rigid body, and standard atmosphere are assumed in the FTD model. Euler angles are adapted for rotational state variables to reduce computational load. Variations in flight Mach number and Reynolds number are assumed to be negligible. Body, stability and inertial axes allow 6 second-order linear differential equations for translational and rotational motions. The equations of motion are integrated with respect to time, resulting in good agreements with flight tests.