This paper describes the development of the 2-dimensional high-precision length measurement principle for accurate evaluation of a disk and the angle measurement technology for an angle sensor in an angle standard system. The 2-dimensional length was measured for an area of 150mm square with a high-precision accuracy of 0.1μm. A high-precision measuring instrument which evaluates the angle accuracy of an angle sensor and a disk was developed. The resolution of the angle calibration system is 0.001 seconds, and its reproducibility is 0.004 seconds. Measurement evaluation of an angle sensor and the disk accuracy was achieved.

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This paper proposes an adaptive model predictive control (MPG) algorithm for a class of constrained, linear, time-invariant, discrete-time systems, which updates the estimation of system parameters on-line and produces the control input subject to the given input/state constraints. This method is based on a robust MPC algorithm using comparison models which enable us to estimate the prediction error bound of uncertain systems and an adaptive mechanism. First, a new parameter update method based on the moving horizon estimation is proposed, which allows us to predict the worst-case estimation error bound over the prediction horizon. Second, we propose an adaptive MPC algorithm by combining the on-line parameter estimation with MPC method based on the modified comparison model. This method guarantees the stability of the closed-loop systems in the presence of system constraints. Finally, a numerical example is given to demonstrate its effectiveness.

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This paper is concerned with affine constraints on a configuration manifold. We first define affine constraints and some concepts. We then explain their geometric representation and show some properties of geometric representation. We next derive necessary and sufficient conditions for affine constraints in the cases of complete integrability, partial nonintegrability and complete nonintegrability. Finally, foliation structures of the configuration manifold are investigated in the respective cases.

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This paper deals with accessibility of kinematic asymmetric affine control systems with affine constraints (KAACS). We first show that the KAACS can be uniquely derived from affine constraints and control inputs. We next investigate relations between accessible sets of the KAACS and foliation structures in the cases of complete integrability, partial nonintegrability and complete nonintegrability. Then, necessary and sufficient conditions for local accessibility and strong local accessibility of the KAACS are derived. Finally, we show some examples in physical and engineering systems and apply our results to them.

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Unknown input observer (UIO) has been used to estimate the states of dynamic systems in the presence of unknown inputs. The UIO can also be applied to the systems with disturbance inputs or unknown varying parameters. It is well known that there exists the UIO for linear time invariant systems (A, B, C) if and only if (i) rankCB=rankB and (ii) all invariant zeros are stable. However, in many cases, these may be very strict conditions. In this paper, a new synthesis method of the UIO is studied in order to estimate system states influenced by unknown inputs. The proposed method can be applied in the case when the above condition (ii) is not satisfied. The basic idea is to assign poles of uncontrollable subspace and controllable subspace for observer systems to desired locations via eigenstructure assignment methods. The dynamic behavior of the states which belong to the controllable subspace depends on the pole locations and so these poles are assigned so that the estimation error caused by unknown inputs and/or disturbance inputs is reduced as small as possible. In order to indicate the effectiveness of our proposed method, a numerical example of the control system with disturbance inputs is given.

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The paper presents two necessary and sufficient existence conditions of a common quadratic Lyapunov function for a set of second-order continuous-time linear time-invariant systems. The first condition reduces Lyapunov matrix inequalities to simpler algebraic inequalities containing two quantified variables. Based on the convex property of solution sets of a common diagonal matrix of second-order Lyapunov inequalities and Helly's theorem, the existence condition for a pair of second-order systems is extended to a set of second-order systems. The problem is reduced to algebraic inequalities with a single variable. The obtained results make the problem amenable to QE (Quantifier Elimination) approach. Several examples are given to illustrate the applications of the obtained results.

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In this paper, a practical and general adaptive robust nonlinear controller is proposed for positioning control of a nonlinear mechanical system. To overcome the main obstacles that prevent the adaptive control techniques from coming into wide use in the industrial side, our attention is focused on the guaranteed transient performance and theoretical transparency of the control system. The controller is designed in a backstepping manner. At the first step, a PI controller is designed to stabilize the position error. Then at the second step, an adaptive robust nonlinear controller is designed to stabilize the velocity error, where the input-to-state stability (ISS) property which guarantees the transient performance is achieved by the nonlinear damping terms. And the adaptive laws are added to achieve a small ultimate error. It is commented that the complicated looking adaptive robust nonlinear controller can be explained as hierarchical modifications of the coventional PI positioning controller with minor-loop. Therefore it is believed that the proposed controller may gain wide acceptance of the engineers. Finally, numerical and experimental examples are included to verify the theoretical results.

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In this paper, we introduce a reinforcement learning architecture method for autonomous robots to obtain generalized behavioral concepts. Reinforcement learning is a well formulated method for autonomous robots to obtain a new behavioral concept by themselves. However, these behavioral concepts cannot be applied to other environments that are different from the place where the robots have learned the concepts. On the contrary, we, human beings, can apply our behavioral concepts to some different environments, objects, and/or situations. We think this ability owes to some memory structure like Schema System that was originally proposed by J. Piaget. We previously proposed a modular-learning method called Dual-Schemata model. In this paper we add a reinforcement learning mechanism to this model. By being provided with this structure, autonomous robots become able to obtain new generalized behavioral concepts by themselves.

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This paper is concerned with tracking control including automatic detection of the moving target object, as well as vibration damping control of the tracking object with vibration elements. In the system, in order that the tracking robot tracks the moving target object, 2-DOF control is constructed to the tracking object. Then, in order to damp the vibration of the tracking object, the position feedback controllers without using direct feedback of vibration element are designed by Hybrid Shape Approach. In the case that the position of moving target object is previously unknown, the moving target object is detected by the laser sensor fitted to the tracking object, and the algorithm of Reference Generator proposed in this paper generates the reference for tracking to moving target object. Moreover, Reference Generator outputs the reference which satisfies the limitations of the velocity and acceleration in the used device. The effectiveness of the proposed control system is shown through experiments using an automatic pouring robot.

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In this paper, we deal with a hybrid controller of learning control and adaptive control for robot manipulators. Some hybrid controllers of adaptive and learning control are proposed by now. The hybrid controller proposed by Dawson et. al. are made in combination with the repetitive learning control and the model-based adaptive control. However, the stability condition of Dawson's controller consists from many equations and the condition for stability is sever. To relax the condition for stability and to make easy to use a hybrid contoroller, we make the new hybrid controller based on Dawson's controller. We give a proof of stability of new controller by using Lyapunov method and show experimental results with computer simulation of 2 link manipulator to verify the effectiveness of the proposed controller.

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Genetic Network Programming (GNP) has been proposed as a new method of evolutionary computations and its basic characteristics are studied. Recently, GNP is also applied to Elevator Group Supervisory Control System (EGSCS) which is a benchmark for real world problems and its applicability and effectiveness are clarified. The elevator system is probabilistic and has some uncertain factors because of the different building specification, traffic volume, traffic flow and so on. Therefore, it is difficult to control the elevator system effectively due to such factors. EGSCS using GNP in the previous studies can control the elevator system using the conventional node functions. However, it does not have enough flexibility in various conditions of the elevator system because of its structure. In this paper, several new frameworks of GNP for EGSCS are proposed in order to overcome the above problem considering ranking calculations with regard to various evaluation items and node function optimization based on Real-coded GA. These frameworks can contribute to generate a flexible and effective structure of GNP for various conditions. From the simulation results, it is clarified that the proposed method can obtain better performances than conventional methods.

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We have developed a pneumatic servo table system, which is a precise positioning system using air power. This system has many advantages such as a high mass power ratio, a low heat generation and a low magnetic field generation. In this paper, the energy consumption of the pneumatic servo table system is investigated from simulations and experiments. To clarify the energy consumption, the air consumption must be examined. The air consumption of the system was analyzed theoretically and it became clear that the air consumption could be separated to the consumption for the movement of the table and that for the acceleration. The certainty of the analysis is confirmed with experimental results using a quick response laminar flow meter.

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An ultrasonic flowmeter is considered to replace flow nozzle and orifice meter as a main feedwater flowmeter in nuclear power station. This paper describes the first examination about the influence of the upstream condition using a cramp-on type ultrasonic flowmeter.

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