Tadashi Ishihara

Dynamics of the Head-Neck Complex in Response to the Trunk Horizontal Vibration: Modeling and Identification

Although many studies exist concerning the influence of seat vibration on the head in the seated human body, the dynamic response of the head-neck complex (HNC) to the trunk vibration has not been well investigated. Little quantitative knowledge exists about viscoelastic parameters of the neck. In this study, the dynamics of the HNC is identified when it is exposed to the trunk horizontal (fore-and-aft) vibration. The frequency response functions between the HNC angular velocity and the trunk horizontal acceleration, corresponding to four volunteers, are obtained in the frequency range of 0.5 Hz to 10 Hz. A fourth-order mathematical model, derived by considering a double-inverted-pendulum model for the HNC, is designed to simulate the dynamic response of the HNC to the trunk horizontal vibration. The frequency domain identification method is used to determine the coefficients of the mathematical model of the HNC. Good agreement has been obtained between experimental and simulation results. This indicates that the system, similar to the designed fourth-order model, has mainly two resonance frequencies. The viscoelastic parameters of the neck, including the spring and damping coefficients, are then obtained by use of the optimization method.

Integral controller design based on disturbance cancellation: Partial LTR approach for non-minimum phase plants

For non-minimum phase plants, the loop transfer recovery (LTR) design of integral controllers based on the disturbance cancellation is considered. Since the design requires an unstabilizable extended plant, the standard LTR method cannot be applied. A new partial LTR method is proposed to overcome the difficulty. The target of the proposed design is a fictitious controller including a disturbance estimator based on the measurement of the minimum phase state. It is shown that the Riccati equation including the gain matrix of the disturbance estimator in the target can be used to recover the target feedback property in the output feedback controller. A simple design example is presented to show the effectiveness of the proposed method.

LTR Design of Integral Controllers for Time-Delay Plants Using Disturbance Cancellation

A design of integral controllers based on disturbance cancellation for time-delay plants is discussed. Since the extended plant used in the design is not stabilizable, the standard loop transfer recovery (LTR) method can not be applied. The new LTR method proposed by the authors to design disturbance cancellation controllers for lumped plants is extended to time-delay plants. It is shown that the new LTR technique provides a transparent two-step design.

LTR design of disturbance cancellation integral controllers for time-delay plants

For time-delay plants, the loop transfer recovery (LTR) technique for the integral controller design based on disturbance cancellation is discussed. Since the design requires an unstabilizable extended plant, the standard LTR method cannot be applied. The new LTR method proposed by the authors for lumped plants is extended to time-delay plants by introducing appropriate predictors. A simple design example is presented to illustrate the proposed design method.

Design of optimal output disturbance cancellation controllers via loop transfer recovery

The authors have introduced optimal disturbance cancellation controllers as a class of controllers minimizing a non-standard quadratic performance index explicitly including disturbances. This paper discusses the application of the classical loop transfer recovery (LTR) technique to the optimal disturbance cancellation controller for step disturbances entering the plant output. The estimation error dynamics of the Kalman filter jointly estimating the plant states and the disturbances is chosen as a target of the LTR design. The weighting coefficient of the performance index is used to recover the target which has guaranteed stability margins as in the standard LTR design. It is shown by a numerical example that the proposed design provides flexible tuning of the disturbance rejection capability with sufficient stability margins.

Multi-objective Genetic Algorithms for the Method of Inequalities

Global search capability of genetic algorithms (GAs) provides an attractive method for solving inequalities. For multi-objective optimisation, various multi-objective genetic algorithms (MGAs) have been proposed. However, due to the fundamental difference between the method of inequalities and conventional multi-objective optimisation, it is not immediately apparent how MGAs should be used for solving inequalities. In this chapter, the use of MGAs in the method of inequalities is discussed. For the effective use of MGAs, an auxiliary vector performance index, related to the set of inequalities, is introduced. A simple MGA with Pareto ranking is proposed in conjunction with the auxiliary vector index. The performance of the proposed MGA is tested on a special set of test problems and control design benchmark problems.

Experience-Based Iterative Learning Controllers for Robotic Systems

An experience based iterative learning controller is proposed for a general class of robotic systems. Experience of the iterative learning controller is stored in the memory in terms of input output data and later used for the prediction of the initial control input for a new desired trajectory. It is proved in this paper that using this approach we can reduce the number of iterations to achieve a certain user defined tracking accuracy. This approach is very general and applicable to all kinds of existing iterative learning control schemes. Numerical illustrations showed the effectiveness of the proposed method.

Partial LTR Design of Optimal Output Disturbance Cancellation Controllers for Non-Minimum Phase Plants

Abstract For non-minimum phase plants, a partial LTR design of optimal output disturbance cancellation controllers is discussed. A target recoverable by the partial LTR procedure is identified as an output injection with a frequency-shaped gain matrix. The partial LTR result is used to clarify system-theoretic meaning of enforcing the minimum phase LTR procedure. It is shown that the partial LTR procedure provides more design freedom in shaping target feedback property than the enforced minimum phase LTR procedure.

Feedback control of braking deceleration on railway vehicle

An increase of the deceleration in high-speed and high-density train operations degrades riding comfort and frequently causes wheel skids. This requires an introduction of the control technology to upgrade the control performance of brake systems on railway vehicles. We are now studying control methods for a mechanical brake that uses friction and pneumatic pressure, including nonlinear elements as the basis of a brake force. Furthermore, the system itself has certain dead time, which is not negligible and makes control difficult. One of our targets is to develop a brake control device that can control the deceleration in accordance with a decelerating pattern that optimizes the riding comfort of trains and prevents wheel skids. In this paper, a design method of the controller for the deceleration tracking control and the system compensating the dead time are proposed. Finally, the effects of them are confirmed through computer simulations and experimental results on a dynamo test stand.

A Learning Control for a Class of Linear Time Varying Systems Using Double Differential of Error

In this paper, a new iterative learning control based on the double differential of the error is proposed for the linear time varying system having relative degree greater than one. The convergence criterion of the proposed method is proved. Furthermore, it is shown by simulations that convergence of error can be increased considerably by using our proposed controller as compared to the iterative learning controller using error or single differential of the error for the modification of the control input without increasing the learning gain.