Kazuya Ogata

Improvement of de-NOx device control performance using a software sensor

Abstract This paper presents a mathematical estimator, named a ‘software sensor’ for predicting the NO x in the fluegas of power plants. The NO x prediction by the software sensor is used in the control loop of NH 3 gas injection to the de-NO x device to reduce the NO x emission from the stack. By the use of the prediction in place of the actual measurement of NO x by the analyzer, the delay time in the control system is eliminated, and as a result the control performance can be improved, thus resulting in a reduction in operating cost.

Control of manipulator with 2 flexible-links via energy modification method by using modal properties

In this paper, we show an approach to give control performance specifications to controller derived by Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) method. The closed loop system by such controller has mechanical properties. To evaluate the performance, we construct cost function by using the modal vector of the linearized closed loop system around equilibrium point. Simulation results and numerical analysis show the effectiveness of our approach.

A nonlinear adaptive robust control design for robotic systems under time-varying parameter perturbation and external disturbance

Many control strategies have been proposed to compensate for uncertainties of robotic system, where the uncertain parameters are assumed to be constant. However, this assumption may not be satisfied in practice. In this paper, we consider the tracking problem for robot manipulator with unknown and time-varying physical parameters and disturbances. Our proposed state feedback adaptive robust controller consists of a nonlinear compensation based on nominal physical parameters, a linear and a nonlinear state feedback, and an adaptation algorithm for adjustment of the gravitational parameters. The effects of time-varying parameters and disturbances on the tracking performance can be attenuated within a prescribed level. Exact asymptotic tracking can be achieved for set point control with vanishing disturbances and constant parameters. By adding feedback input to penalty variable, high gain feedback can be strategically avoided. The effectiveness of the proposed method is verified by simulation and experiments.

Adaptive Control for Steam Temperature of Thermal Power Plant

Abstract A discrete time adaptive control system was applied to the steam temperature control of a boiler for electric power generation. In the system. the adaptive controllers are applied in parallel with the conventional PID controllers for supcrheated and reheated steam temperatures. The plant dynamics was described with polynomials whose pararneters are adaptively estimated from the data of the plant under routine operation. The adaptive control signals are synthesized on the basis of the estimated parameters so as to achieve the specified control objective. The system was applied to a 375MW plant and found to realize far better control performance than the conventional PID control system.

Modeling and Denox Control System for Fossil-Fuel-Fired Power Plants

Abstract In this paper, a de-NOx system, that complies with the envirorunental regulation and at the same time saves the operation cost, is introduced. The paper consists of two parts, i.e., the modeling of the NOx producing process and the design of the de-NOx control system. At first, a multi-input single-output ARX, model describing the relationship between the NOx content in the flue gas and process input variables relevant to it is identified through the Recursive Least Square Method. The model is used to predict the current NOx gas content which is otherwise unknown because of the remarkable measurement delay. The validi ty of the model is confirmed by comparing the prediction of NOx with its measurement at the actual plant. The controller design is performed on the basis of this model, assuming that the model represents the behavior of the actual plant. A control system consisting of an adaptive feedforward controller and a PID feedback controller is designed. The effectiveness of the controller was examined through simulation studies, which showed the proposed de-NOx system had an excellent performance to achieve the objectives.

Determination of Design Parameters for Control of Manipulator with 2 Flexible-Links via Energy Modification Method

Abstract Energy modification methods have been attracting a lot of attention as a new controller design methods of mechanical systems. However, the relation between design parameters and control performance is not so clear, thus there is no guideline for determination of design parameters. In this paper, IDA-PBC method is applied to manipulator with 2 flexible-links. Utilizing mechanical properties of closed loop system, we cany out numerical evaluation and determine design parameters. Experiments show that the proposed approach is effective.

Robust control of robot manipulators under time-varying parametric uncertainty and disturbance with adaptive gravitational compensation

We consider the tracking problem for robot manipulators with unknown and time-varying physical parameters and disturbances which belong to L/sub 2/. Proposed state feedback adaptive robust controller consists of a nonlinear compensation based on nominal physical parameters, a linear and a nonlinear state feedback, and an adaptation algorithm for adjustment of the gravitational parameters. The effects of time-varying parameters and disturbances on the tracking performance can be attenuated within a prescribed level. Exact asymptotic tracking can be achieved for vanishing disturbances, constant parameters, and set point problem. By adding feedback input to penalty variable, high gain feedback can be strategically avoided.

Nonlinear Control for Manipulator with Flexible Link Based on a Backstepping Approach

Abstract A systematic approach to construct a lyapunov function for closed loop system of flexible manipulator is considered. Backstepping approach andc nature of the mechanical system are used for the design of the control system. Howeverit is found that the controller becomes complicated.

A Consideration of the Upper Bound of Parameter Identification Error with Unstructured Modelling Uncertainty and Disturbance

Abstract When a control system is designed, it is important to make a model which can explain the input-output relation precisely. To identify the model’s parameter as precisely as possible, it is important to make the experimental signal less affected by the disturbance or the unstructured model uncertainty and sufficiently informative. In this report, the upper bound of the estimated parameter error is proposed when the unstructured model uncertainty exists. This upper bound can be used to decide the optimal identification input.

Adaptive Tracking Control of Rigid Robot Manipulators by Using Only Joint Position Measurements

Abstract In this paper, a new high-gain observer for rigid robot manipulators is proposed. By combining this observer with several adaptive controllers for rigid robot manipulators, we extend the state feedback(joint position and joint velocity) based adaptive controllers to output(joint position only) feedback based ones. We show that the output feedback based adaptive control system consisting of the observer and adaptive controller(Slotine and Li, 1988) is semiglobally asymptotically stable. Moreover, we show that the adaptive control system consisting of the observer and composite adaptive controller(Slotine and Li, 1989) is semi-globally exponentially stable if the regressor vector is P.E.(persistently exciting). The simulation results have shown the effectiveness of the developed observer and adaptive controller.