Fieldbus is the lowest level industrial network in the communication hierarchy of factory automation and distributed process control systems. Data generated from field devices are largely divided into three categories : time-critical, periodic and time-available data. Because these data share one fieldbus medium, it needs a method that allocates these data to the bandwidth-limited fieldbus medium. This paper introduces an implementation method of bandwidth allocation scheme on PROFIBUS. In order to implement bandwidth allocation scheme on PROFIBUS, the following functions need to be supplemented on the FDL(Fieldbus Datalink Layer) protocol: (i) separation of medium bandwidth into periodic and non-periodic intervals, (ii) synchronization of node timers over a local link. In order to examine the validity of bandwidth allocation scheme on PROFIBUS, this paper develops an experimental model of a network system. The results obtained from the experimental model show that the bandwidth allocation scheme satisfies the performance requirement of time-critical, periodic and time-available data.

Although large space structures(LSS) such as a space station, a solar power station satellite, etc., are theoretically distributed parameter and infinite-dimensional systems, they have to be modeled into a lumped parameter and large finite-dimensional system for control system design. Besides, there remains the fundamental problem that the modeled large finite-dimensional system must be controled with a much smaller dimensional controller due to the limitation of computing resources. This causes the spillover phenomenon which degrades control performances and reduces the stability margin. Furthermore, it may destabilize the entire feedback control system. In this paper, we propose a novel spillover suppression method in the active vibration control of large flexible structures by using eigenstructure assignment. Its validity and effectiveness are investigated and verified by the numerical experiments using a simply supported flexible beam, which is modeled to have four controlled modes and eight uncontrolled modes.

This paper deals with a sliding mode control with uncertainty adaptation for the robust stabilization of input-delay systems with unknown uncertainties. A sliding surface including a state predictor is employed to compensate for the effect of the input delay. The proposed method does not need a priori knowledge of upper bounds on the norm of uncertainties, but estimates those upper bounds by adaptation laws based on the sliding surface. Then, a robust control law with the uncertainty adaptation is derived to ensure the existence of the sliding mode. A numerical example is given to illustrate the design procedure.

Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.

In this paper, we present a method that has flexibility of exact assignment of eigenstructure with the stochastic robustness for LTI(Linear-Time-Invariant) systems. The stochastic robustness of LTI systems is determined by the probability distributions of closed-loop eigenvalues. The probabilistic stability region is presented stochastically using the Monte Carlo evaluations. The proposed scheme is applied to designing a simple system and a flight control system with stochastic parameter variations to confirm the usefulness of the scheme.

A pulse amplitude modulation(PAM) controller is designed for the 3 axis attitude control of a sounding rocket. a certain number of fixed level of thrust are used for the pulse amplitude modulation and the nonlinearity of the controller is considered to examine the existence of the limit cycles and the stability analysis is carried out with the aid of Nyquist plot.

A Linear Pulse Motor (LPM) is a direct drive motor that has good performance in terms of accuracy, velocity and acceleration compared to the conventional rotating system with toothed belts and ball screws. However, since an LPM needs supporting devices which maintain constant air-gap and has strong nonlinearity caused by leakage magnetic flux, friction and cogging, etc., there are many difficulties in improvement on accuracy with conventional control theory. Moreover, when designing the position controller of LPM, the modeling error and load variations has not been considered. In order to compensate these components, the neural network with conventional feedback controller is introduced. This neural network of feedback error learning type changes the current commands to improve position accuracy. As a result of experiments, we observes that more accurate position control is possible compared to conventional controller.

In this paper, fuzzy logic controllers(FLC) are designed for control of flight. For tuning FLC, we used adaptive evolutionary algorithms(AEA) which uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. We used AEA to search for optimal settings of the membership functions shape and gains of the inputs and outputs of FLC. Finally, the proposed controller is applied to the high-angle-of-attack flight system for a supermaneuverable version of the f-18 aircraft and compares with other methods.

When a robot hand grasp an object, the number of ways to grasp it stably are infinite and thus an optimal grasp planning is needed to find the optimal grasp points for satisfying the objective of the given task. In this paper, we first define some grasp indices to evaluate the quality of each feasible grasp and then a weighted composite grasp index by combining all of the grasp indices is also defined. Next, we propose a method to find the optimal grasp points of the given object by comparing the defined weighted composite grasp index for each feasible grasp points. By simulation results, we show the effectiveness of the proposed optimal grasp planning method and also discuss the trend of each grasp index as the grasp polygon.

This paper suggests fuzzy-PI controllers for a heavy-duty gas turbine. The fuzzy-PI controllers are designed to regulate rotor speed and exhaust temperature of the gas turbine. The controller gains are tuned by genetic algorithm(GA). This paper also proposes a new fitness function of GA using a desired output response. The suggested controller is compared with previous controllers via simulations and it is shown that the rotor speed variation of our controller is smaller than those of previous ones.

We propose a sliding mode controller tracking the states of a time-varying reference model. The reference model generates the desired trajectories of the states, and the sliding mode controller regulates robustly the errors between the desired states and the measured states. We apply this controller to the overhead crane. Its reference model generates the trajectories of the damped-out swing angle and the swing angular velocity to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. Also, this model generates the desired trajectories of the position and velocity of the crane. The crane model is identified from the experimental data using an orthogonal function. Kalman filtering is applied to estimate the crane states. The designed controller is simulated on a computer and is tested through a 2-ton industrial overhead crane using the vector-controlled servo motor system. It is verified that, from the simulated and experimental results, the sliding mode controller tracking a time-varying reference model works well.

The unbalanced heavy-loaded elevation-drive system is composed of a hydraulic cylinder, a driving link-mechanism and an equilibrating-mechanism which compensate the static unbalanced moment of the elevation load. The Compensator for the unbalanced moment is composed of a hydrau-pneumatic accumulator and a hydraulic cylinder which act with the elevation cylinder together. Compensation of the variable static-unbalanced moment for the elevation-drive system is very difficult because these mechanisms imply highly nonlinear properties due to air conditioning characteristics and mechanical rotation of the link-mechanism. In this study, through the analysis of the already designed equilibrating-mechanism, the optimal design parameters of the equilibrating-mechanism is suggested.

In this paper, the error caused by the measurement delay in INS/GPS integrated systems with Kalman filtering is defined and analyzed through the analytical method and the simulation. It is proved that the error of measurement delay causes not only the position error but also the estimate error of the x-axis accelerometer bias when a vehicle turns. And the estimation method of the delay time and the compensation method using an extrapolation method are presented. The performance of the compensation method is shown by the analytic method and the simulation.