Model-based Control System Design Research Articles

Sliding Mode Control with Frequency-shaped Hyperplane for a Ball Screw Driving Stage

In a CNC Video Measuring System, both very-low-speed motion and high-speed motion are required. Very-low-speed motion is highly influenced by friction. Currently, PID control with look-up-table gains is used to handle with this problem. However, the process of developing this table tends to be a trial-and-error scheme. In the present paper, we investigate a model-based control system design. System identification techniques are used for constructing a model for a control system design and a sliding mode controller with a frequency-shaped hyperplane is designed using that model. Both strong attenuation of disturbances at low frequencies and stability at high frequencies are achieved in a real machine.

A simplified mathematical dynamic model of the HTR-10 high temperature gas-cooled reactor with control system design purposes

A simplified mathematical dynamic model of the HTR-10 high temperature gas-cooled reactor is developed based upon the fundamental conservation of fluid mass, energy and momentum. The model is formulated for coupling reactor neutron kinetics with reactivity feedback and reactor thermal-hydraulics. The reactor is nodalized to employ the lumped parameter modeling methodology, which is mathematically described by differential algebraic equations (DAEs). The developed model is implemented on a personal computer using the MATLAB/Simulink tool. A lot of numerical simulation experiments are investigated and discussed. The transient results show that the model can properly predict the reactor dynamics and can serve as the basis for the model-based control system design.

Robust system identification of an irrigation main canal

In this paper, a mathematical model of irrigation main canals is derived from on-line system identification experiments. This model is obtained experimentally by using a robust system identification procedure. The entire process followed to obtain this model is described in this paper: from the design of the experiments to the model validation. The model takes into account prior physical information. A recursive least-squares parameters estimation algorithm with normalization for robust system identification of main irrigation canals is developed. The validation results show the robustness of the parameters estimation algorithm and justify its use in robust model-based control system design. The results also show accurate water levels prediction in open irrigation main canals with time-varying parameters. The reported results show that robust system identification has an important role to play in management and efficient use of water resources.

Model-based optimal attitude and positioning control of small-scale unmanned helicopter

In this paper, we propose a model-based control system design for autonomous flight and guidance control of a small-scale unmanned helicopter. Small-scale unmanned helicopters have been studied by way of fuzzy and neural network theory, but control that is not based on a model fails to yield good stabilization performance. For this reason, we design a mathematical model and a model-based controller for a small-scale unmanned helicopter system. In order to realize a fully autonomous small-scale unmanned helicopter, we have designed a MIMO attitude controller and a trajectory controller equipped with a Kalman filter-based LQI for a small-scale unmanned helicopter. The design of the trajectory controller takes into consideration the characteristics of attitude closed-loop dynamics. Simulations and experiments have shown that the proposed scheme for attitude control and position control is very useful.

Modeling the internal dynamics of energy and mass transfer in an imperfectly mixed ventilated airspace.

The present paper outlines a modeling approach, which has been developed to model the internal dynamics of heat and moisture transfer in an imperfectly mixed ventilated airspace. The modeling approach, which combines the classical heat and moisture balance differential equations with the use of experimental time-series data, provides a physically meaningful description of the process and is very useful for model-based control purposes. The paper illustrates how the modeling approach has been applied to a ventilated laboratory test room with internal heat and moisture production. The results are evaluated and some valuable suggestions for future research are forwarded. The modeling approach outlined in this study provides an ideal form for advanced model-based control system design. The relatively low number of parameters makes it well suited for model-based control purposes, as a limited number of identification experiments is sufficient to determine these parameters. The model concept provides information about the air quality and airflow pattern in an arbitrary building. By using this model as a simulation tool, the indoor air quality and airflow pattern can be optimized.

Model Based Optimal Attitude and Positioning Control of Small-Scale Unmanned Helicopter

In this paper, we propose the model based control system design for autonomous flight and guidance control of a small-scale unmanned helicopter. A small-scale unmanned helicopter has been studied with fuzzy and neural network theory, but it is not so good performance for unmodel based control to stabilize it. For this reason, we design a mathmetical model (Mettler's model) and a model based controller for a small-scale unmanned helicopter system. In order to realize a full autonomous small-scale unmanned helicopter, we have designed the attitude controller and trajectory controller with kalman filter based LQI for a small-scale unmanned helicopter. The characteristic of the attitude closed loop dynamics is taken into consideration to design a trajectory controller. By way of the simulations and experiments, it has been clarified that the proposed scheme for attitude control and guidance control is very useful.

Proportional‐Integral‐Plus Control of an Intelligent Excavator

Abstract: This article considers the application of Proportional‐Integral‐Plus (PIP) control to the Lancaster University Computerised Intelligent Excavator (LUCIE), which is being developed to dig foundation trenches on a building site. Previous work using LUCIE was based on the ubiquitous PI/PID control algorithm, tuned on‐line, and implemented in a rather ad hoc manner. By contrast, the present research utilizes new hardware and advanced model‐based control system design methods to improve the joint control and so provide smoother, more accurate movement of the excavator arm. In this article, a novel nonlinear simulation model of the system is developed for MATLAB/SIMULINK©, allowing for straightforward refinement of the control algorithm and initial evaluation. The PIP controller is compared with a conventionally tuned PID algorithm, with the final designs implemented on‐line for the control of dipper angle. The simulated responses and preliminary implementation results demonstrate the feasibility of the approach.

121 Model-based Attitude and Hovering Control of Small Unmanned Helicopter

In this paper, we propose the model based control system design for autonomous flight and guidance control of a small unmanned helicopter. A small unmanned helicopter has been studied with fuzzy and neural network theory, but it is very difficult for unmodel based control to stabilize it. For this reason, we design a mathmetical model(Mettler's model) and a model based controller for a small unmanned helicopter system. In order to realize a full automatic controlled small unmanned helicopter, we have designed the attitude controller and trajectory controller with kalman filter based LQI for a small unmanned helicopter. The characteristic of the attitude closed loop dynamics is taken into consideration to design a trajectory controller . By way of the simulations and experiments, it has been clarified that the proposed scheme for attitude control and guidence control is very useful.

Attitude Control and Hovering Control of Radio-Controlled Helicopter.

This paper proposes the model based control system design for autonomous flight and guidance control of Radio-Controlled Helicopter. RC Helicoper has been studied with fuzzy and neural network approach, but it is so difficult for unmodel based control to stabilize it. The system identification techniques and model tuning approach are applied for RC helicopter system to obtain the mathmetical model. In order to realize the full automatic controlled RC helicopter, we have designed the attitude controller and altitude controller with LQG based Kalman filter and trajectory controller with SMC (Sliding Mode Control) for RC helicopter. It has been clarified that the proposed scheme for attitude control, altitude control and hovering control are very useful by way of the simulations and experiments.

344 ラジコンヘリコプターの姿勢安定化・誘導制御(アドバンスト制御理論応用IV)(OS アドバンスト制御理論応用)

In this paper, we propose the model based control system design for autonomous flight and guidance control of Radio-Controlled Helicopter. RC Helicoper has been studied with fuzzy and neural network theory, but it is so difficult for unmodel based control to stabilize it. So we apply system identification and model tuning approach for RChelicopter system to obtain the mathmetical model. In order to realize the full automatic controlled RC helicopter, we have designed the attitude controller with LQG based Kalman filter and trajectory controller with SMC(Sliding Mode Control) for RC helicopter. It has been clarified that the proposed scheme for attitude control and guidence control is very useful by way of the simulations and experiments.