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Velocity field control (VFC) is an alternative approach for motion control of robotic systems. It has advantages over the trajectory tacking problem when the timing in the desired task is of less importance in the application of interest. Recently, this control strategy has been emerged as a promising control method in robot-aided rehabilitation. Therefore, this paper addresses the problem of VFC for robotic exoskeletons with dynamic uncertainties. Most existing VFC methods require some knowledge of the dynamic model of the robot, which is usually difficult in practice to precisely identify. Consequently, this paper design an adaptive neural network VFC method to compensate for the dynamic uncertainties. The controller gives a priori bounded control command in order to take into account the saturation of actuators. The controller performance is validated through simulation and experimental studies on a two-degree-of-freedom lower-limb robotic exoskeleton.

This paper addresses the assist-as-needed (AAN) control problem for robotic orthoses. The objective is to design a stable AAN controller with an adjustable assistance level. The controller aims to follow a desired trajectory while allowing an adjustable tracking error with low control effort to provide a freedom zone for the user. By ensuring the stability of the system and providing the freedom zone, the controller combines the advantages of both model-based and non-model-based AAN controllers existing in the literature. Furthermore, the controller provides a priori bounded control command, and includes an adaptive neural network term to compensate for the uncertainties of dynamic model of the system, mainly when a precise tracking is of interest. The stability of the closed-loop system is well analysed based on the Lyapunov method. The effectiveness of the proposed control scheme is validated through experiments using a lower extremity robotic exoskeleton.

This paper proposes a distributed control approach for optimal power dispatch towards environment-friendly power grids. To do so, an optimization problem called environmental economic dispatch, which is subjected to physical constraints of the considered power system, is solved. Consequently, we propose an approach based on the Alternating Direction Method of Multipliers (ADMM) to obtain the globally optimal solution of that optimization problem in a distributed manner under a fast convergence. As a result, each generation unit can derive by itself an optimal generated power that minimizes with compromising both fuel and emission costs while satisfying both global and local physical constraints caused by the whole system and by its own. The most distinguished feature of this approach is that the power balance constraint is always guaranteed during the execution of the algorithm. Finally, the performance of our proposed approach is illustrated through the simulation to a realistic power system and the comparison with another method.

This paper aims at proposing a distributed control approach for optimal power dispatch towards environment-friendly power grids. In order to do so, both electric generation and pollutant emission costs are properly incorporated into a unique objective function of an optimization problem subjected to physical constraints of the considered power system. Consequently, we propose an approach based on the Alternating Direction Method of Multipliers (ADMM) to obtain the globally optimal solution of that optimization problem in a distributed manner under a fast convergence. As a result, each generation unit in a power system can derive by itself an optimal generated power that minimizes with compromising both fuel and emission costs while satisfying both global and local physical constraints caused by the whole system and by its own. The most distinguished feature of this approach is that the power balance constraint is always guaranteed during the execution of the algorithm. Finally, the performance of our proposed approach is illustrated through the simulation to a realistic power system and the comparison with another method.

Due to ill-defined and poorly understood dynamics of flapping wing flying robots, acquiring high-fidelity aero dynamical and control models for such aerial robots are challenging and often infeasible. In this work, we propose using a non-linear, model-free approach that eliminates errors arising from the mis-modeling or under-modeling of flapping dynamics. These procedures require no prior knowledge or model of any of the dynamical aspects of the flying robot and assume zero statistical knowledge about noise affecting sensor measurements. Intelligent PID (iPID) controllers are used to provide an abstracted treatment of all unknowns and uncertainties in the robot by encapsulating them together into a single term. The problem then devolves into the estimation of this term by either direct or indirect means which is more practical than obtaining high-fidelity models. For indirect estimation, numerical differentiation is required and we propose using a Haar-wavelet differentiator that is capable of smoothing and differentiating signals irrespective of the multivariate noise corrupting the signal. The direct estimation method uses an algebraic and non-asymptotic method. Pitch control and altitude control experiments are successfully performed on a real, bird-like flapping wing flying robot using all different approaches; results obtained reveal that indirect estimation using the Haar-wavelet differentiator provides slightly better performance.

Rigid planar space robot is represented as Caplygin system and its base attitude can be stabilized by means of geometric phase. However, in cases when flexible arms are used for control of base attitude, inherent resonance modes are excited and instability is resulted. In this study we propose a stabilized controller is synthesized as adaptive tracking control system convined with sliding mode control to track to the arm trajectories derived from the geometric phase of the Caplygin system. Usefulness of the proposed controller is demonstrated by numerical simulations and laboratory experiments.

In this paper a new control methodology for underactuated mechanical systems is proposed. The basic idea of this method is to combine passive velocity field control with decoupling vector field. In order that the underactuated mechanical systems can be stabilized at the desired position after settling on the desired velocity vector field, novel control strategies are proposed. Proposed control strategies are applied to the underactuated planar three-link manipulator and underactuated planar body. Simulations demonstrate the usefulness and effectiveness of the proposed control methodology.

In this brief, a new adaptive control framework to compensate for uncertain nonlinear parameters in robot manipulators is developed. The designed adaptive controllers possess a linear parameter structure, guarantee global boundedness of the closed-loop system as well as tracking of a given trajectory within any prescribed accuracy. Our design approach takes advantage of a Lipschitzian property with respect to the plant nonlinear parameters. The outcome is that a very broad class of nonlinearly parameterized adaptive control problems for robot manipulators can be solved using this technique. Another feature of the proposed method is the design of low-dimensional estimator, even 1-D if desired, independently of the unknown parameter vector dimension. Simulations and experiments in friction compensation task for low-velocity tracking of a 2 degree-of-freedom planar robot demonstrate the viability of the technique and emphasize its advantages relatively to more classical approaches.

In this paper, we realize parallel parking task based on two-stage modeling method, where parking task model and vehicle dynamical model are developed respectively and incorporated into a entire model in a seamless manner. The vehicle dynamics is highly constrained by non-holonomic constraint with nonlinear tire characteristics. In order to describe vehicle dynamics, we use a new data mining based affine system modeling method. The entire parking task model is combined with several sub-parking task models, which consist of some conditions in state-input space of the system and their transitions to another. The incorporation of the both parking task model and vehicle dynamical model is realized using finite state machine. The proposed model is very general that regardless of the initial position of the vehicle, it is successfully controlled to move into the parking space. In the later part of this paper, we present a mathematical programming based optimal control scheme where the optimal inputs are selected among the permissible set of the input variable, considering all the limitations specified by linear inequalities. In order to confirm the usefulness of the proposed method, some simulation results are shown.

In this paper, a synthesis method of new disturbance observer, which can cope with frequency variation, is proposed. The main idea is to synthesize the disturbance observer as a gain-scheduled controller. The proposed disturbance observer gives the same low sensitivity property for disturbances with frequency variation as the conventional disturbance observer does. As an application, we consider vibration suppression control system for a flexible beam with multiple vibration modes. By numerical simulations and experiments, the proposed control scheme is shown superior to the conventional disturbance observer with respect to vibration suppression as compared.

A well-known control system that can reduce the adverse effects of disturbances is the disturbance observer. Whenever we apply a disturbance observer, the disturbance frequency should be known and constant. However, since in many cases of industrial systems the disturbance frequency is varied in some frequency spectrum, it may be difficult to reduce the adverse effect of such disturbances by use of the traditional disturbance observer. Therefore, we have proposed a disturbance observer which can handle frequency variation (DOFV). However, in order to apply DOFV we must measure the disturbance frequency in real time. Therefore, a frequency estimation scheme is required in order to apply DOFV. In this paper, a method for the design of a disturbance attenuation system that can handle frequency variation is proposed. The main idea of this design method is to combine DOFV with a frequency estimator that can estimate the disturbance frequency in real time. Even though the proposed disturbance attenuation system is a low-degree and low-gain controller, it has excellent steady-state disturbance attenuation performance. Numerical simulations and experiments show the usefulness of the proposed disturbance attenuation system. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 175(2): 46–53, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21073

This paper presents a motion control system of an unmanned vehicle, where parallel parking task is realizedbased on a self-organizing affine system modeling and a quadratic programming based robust controller. Because of non-linearity of the vehicle system and complexity of the task to realize, control objective is not always realized with a single algorithm or control mode. This paper presents a hybrid model for parallel parking task in which seven modes for describing sub-tasks constitute an entire model.

Electric Vehicle (EV) which has a large amount of storage battery can contribute to make Energy Management System (EMS) more effective. While an EV is parking at home or at company, the battery of an EV can be used as an energy storage for smart grids. In this paper, we propose a model predictive control of EV storage battery in Home Energy Management System (HEMS) based on an auto-regressive model and Particle Swarm Optimization (PSO). We also study the effectiveness of Photovoltaics (PV) equipped with EVs. The proposed method controls the states of EV storage battery to minimize the electricity cost of HEMS and evaluates the electric company's profit.

This paper proposes a novel approach to design distributed optimal controllers for the power coordination problem in Wind Power Plants (WPPs). Based on LQR method, we present a systematic procedure to design a fully distributed optimal stabilizing controller for the linearized model of Wind Turbines (WTs) in a WPP. Next, the reduced-order distributed optimal controller is derived by elaborating more on the selection of weighting matrices in the LQR performance cost. Furthermore, the effect of disturbances to the system performance is evaluated through the H ∞ norm computation. Finally, the simulation results for a linearized model of WPP are shown to illustrate the effectiveness of the proposed approach.

In this paper we consider the problem of plant parameter estimation for a flapping wing flying robot. These parameters are the coefficients of polynomials appearing in transfer functions that govern some robot dynamics e.g pitching, and their values are completely unknown and even susceptible to variation over time. First, we analyse the pitching dynamics of the SlowHawk2 flapping wing flying robot under study and derive the linearized state-space model. Our analysis shows that in addition to the elevator deflection inducing pitching motion on the flying robot, extraneous pitching is also caused by the flapping wings. Thus, our derivations yield a multiple-input single-output (MISO) system consisting of two uncoupled transfer functions where both the elevator deflection and the wing-flapping action are the inputs that determine the pitching. Subsequently, an online parameter estimator is designed for the MISO system in order to estimate values of coefficients in the transfer functions. We use the recursive least squares method with the so-called forgetting factor. How the parameter estimator is designed using only the known input signals and measured output signals is described in detail. Using real sensor data obtained from real test flights, the designed estimator shows that the values of the unknown parameters can be accurately and robustly determined.

Recognizing the human gait is an edge research in robotics and rehabilitation. It has been popular to recognize the human gait from kinematic data. However, the recognition from muscle activities, the input of the movement, has not been widely approached. In this paper, we propose a framework to recognize the human walking and running movements by investigating muscle activities through electromyography (EMG). The framework is a Hidden Markov Model (HMM) topology utilizing Locally Linear Embedding (LLE) technique to extract feature vectors. We show that: (1) the high-dimensional EMG data can be embedded into a lower-dimensional space by using a manifold learning algorithm (LLE), primitive components which give meaningful representation of the EMG can be extracted, and (2) our proposed HMM topology whose input are the extracted vectors from EMG can recognize the gait movement at an accuracy rate of over 80%.

This paper presents a new framework for traffic flow control based on an integrated model description by means of a Hybrid Dynamical System (HDS). The geometrical information on the traffic network is characterized by a Hybrid Petri Net (HPN). Then, the algebraic behavior of traffic flow is transformed into a Mixed Logical Dynamical System (MLDS) form in order to introduce an optimization technique. These expressions involve both continuous evolution of traffic flow and event driven behavior of traffic light. HPN allows us to formulate the problem easily for complicated and large-scale traffic network due to its graphical understanding. MLDS enables us to optimize the control policy for traffic light by means of its algebraic manipulability and use of model predictive control framework. Since the behavior represented by HPN can be directly transformed into corresponding MLDS form, the seamless incorporation of two different modeling schemes provide a systematic design scenario for traffic flow control.

In this paper, the behavior of wire vibration in machining process is studied by using a system modeled on the basis of experimental results. For the purpose of examining the behavior of wire vibration, dynamical changes in the material removal process must be taken into account. Therefore, a machining system set up is modeled where the interference between the vibration system of the wire electrode and the material removal system are considered. In this system, the material removal rate and the external force output from the material removal system are the input of the vibration system, whereas, the gap distance output from the vibration system is the input source of the material removal system. In order to analyze the modeled system, some simulations of the machining process are carried out. In the analysis of these simulations, a statistical method is applied to the wire displacement. Furthermore, the mean value and the magnitude of a simulated wire displacement are quantitatively compared with the measured results. Using the modeled system, the relation between wire vibration and state variables in the system are clarified.

Nonstationary optimal regulator (NOR) is one of the effective methods for positioning control of vibration systems. NOR corresponds to an LQ regulator utilizing time-varying weighting functions and produces positioning trajectories taking the vibration characteristic of a controlled object into account. Generally, many positioning or tracking mechanisms such as information equipments, machine tools and robots adopt dual-stage actuator systems (DSASs). DSASs consist of coarse and fine actuators and realize efficient and high performance responses. However, the control method for DSASs with mechanical flexibility has not been fully addressed. This study utilizes the NOR technique for positioning control of DSASs taking spring and damping elements of controlled objects into account. We use a proper combination of time-varying weights for this problem. The effectiveness of this method is verified by numerical calculations and experiments.

Servo control is one of the most important control techniques for motion control of mechanical structures. Generally, the servo control consists of reference trajectories and a feedback controller. Many recent studies in the control engineering field have treated recent design methods of feedback controllers taking account of several control specifications. However, generally, the ability of an actual feedback controller is strictly limited due to its cost or difficulties of realization. Different from the above approaches, this study proposes a novel framework for the motion control of mechanical structures. It means a combination of a high performance reference generation and a simple feedback controller. References are generated by an offline simulator taking several specifications into account. As an example, we discuss a positioning control of a vibration system and utilize a nonstationary optimal control simulator and a sliding mode feedback controller. The effectiveness of the method is verified by numerical calculations and experiments.

A well-known control system which can reduce the adverse effects of disturbances is a disturbance observer. However, in many cases of mechanical systems, system disturbances which do not satisfy the matching condition may be imposed. Therefore, it may be difficult to reduce the adverse effects of the disturbances by the traditional disturbance observer. In this paper, a method of control system synthesis for disturbance rejection using a dual observer is proposed. This method is based on the zeroing induced by the disturbance localization problem. This problem may be solved by dividing the state space into observable subspace and unobservable subspace. As compared with an H∞ controller based on perfect observation, the usefulness of the proposed control system for disturbance rejection is demonstrated by numerical simulations for a two-mass spring system. © 2002 Scripta Technica, Electr Eng Jpn, 138(4): 50–60, 2002; DOI 10.1002/eej.1138

This study discusses the positioning and vibration control of time-varying vibration systems whose parameters are time-varying. We assume that the time-varying parameter of a vibration system is detected by an on-line measurement or Wavelet analysis. This paper treats two control methods using nonstationary optimal regulators (NOR) for this problem. The first method is a gainscheduling of NORs. An actual controller is obtained by the interpolation of plural NORs designed a priori. The other one is an NOR design based on Wavelet analysis of the vibration system. In the second case, single NOR derived from the analysis result is applied. This study shows the effectiveness of these methods by numerical calculations and experiments. From the comparison of these methods, this paper suggests suitable applications of NOR according to the characteristics of each control problem.

This paper proposes a control strategy for descriptor non-polynomial systems using parallel asynchronous particle swarm optimization (PAPSO). Basic idea of our approach is to extend the existing approaches for estimating the domain of attraction (DOA) of the non-polynomial systems to synthesis of stabilizing control. To do this we derive the stability conditions for estimating the DOA with input magnitude constraints. From these conditions stabilizing controller is obtained by PAPSO. The proposed strategy can be easily exploited to search for both the stabilizing controller and optimal estimates of DOA. Usefulness and validity are demonstrated by numerical simulations.

An understanding of muscle activities can reveal the mechanism of producing locomotion, helping to improve the performance of assistive robots in supporting the users' movement. This paper proposes a framework to recognize the human walking movement by investigating electromyography (EMG), which has not been widely approached yet. The framework is a combination of a Hidden Markov Model (HMM) and Locally Linear Embedding (LLE) technique. First, we show that using LLE algorithm we could reduce the dimensionality of the high-dimensional EMG dataset. The extracted primitive components gave a meaningful representation of the EMG. Second, we demonstrate that the HMMs trained by these components could recognize the movement intention at a high rate of accuracy.

A trajectory specification method for a flapping-wing flying robot exhibiting a novel dynamical model than other types of micro aerial vehicles such as quadrotors and airplanes is presented. The desired trajectory is first defined as a vector-valued, differentiable parametric curve of the form f : RR → RR. The velocity vector at any point of the trajectory is the same as the unit tangent vector obtained using parametric differentiation. The acquired unit tangent vector is subsequently expressed in quaternion form and nominal values for the pitch and yaw angles at every point of the trajectory are determined. Finally, the feed-forward trajectory is specified as a function of the input control variables (δr, δe) of the flapping wing flying robot. At the same time, the feasibility of a specified trajectory is verified so that there are no violations of intrinsic constraints. Both two and three dimensional flight trajectories are simulated for exemplification. Simulation results are compared to real sensor data, thus verifying the procedure.

This paper aims to describe a framework implementing Multi-Class Support Vector Machine (MCSVM)-based motion intention recognition. To this end, we primarily constructed a wearable exoskeleton robot of lower body (TTI-Exo) which is employed as the experimentation platform to test the proposed method of motion intention recognition based on MCSVM and the assist effectiveness as well. Experiments of stand-to-sit and sit-to-stand movements were carried out to test the MCSVM method and TTI-Exo's motion assist. Having disclosed prototype development, experimental results are presented. We verified that our proposed method based on MCSVM obtained a better recognition accuracy than a conventional method based on threshold values. Muscle activities when subjects wearing TTI-Exo were much smaller than when subjects not wearing the exoskeleton, thus implying the assist efficacy of our power assist system.

In this paper, we develop a dynamics-based adaptive control scheme to achieve the stability for teleoperation system and its transparency in the sense of motion/force tracking. The proposed scheme does not require accurate dynamic parameters of manipulators, human and environment models as well as the information of manipulators' acceleration. The validity and advantages on control characteristics of proposed scheme towards conventional impedance matching control are confirmed by numerical simulations and experiments.

A well known control system which can reduce the adverse effect of a periodic disturbance with single frequency is the disturbance obsever. However, in many cases of industrial systems disturbance frequency is varied for some frequency range. Therefore, it may be difficult to reduce the adverse effect of the disturbance by the use of the traditional disturbance observer.In this paper, a design method of new disturbance observer which can cope with the frequency variation is proposed. The main idea of this design method is to synthesize the disturbance observer as a gain-scheduled controller. The proposed disturbance observer is constructed as low degree and low gain controller with superior steadystate characteristic. As compared with the traditional disturbance observer and the H∞ controller, the usefulness of the proposed disturbance observer was shown by numerical simulations.

In this paper, the free-flying space robot, comprising a satellite base body and articulated manipulator arms, is considered. We clarify the reduced effective inertia of this sophisticated mechanism is smaller or equal to the effective inertia associated with the articulated manipulator arm which is fixed on the earth. Furthermore, we develop the control system which decouples motions of satellite base body with the end-effector movements with application to control system for capturing a turget by a space robot. Finally numerical simulations demonstrate the usefulness of the proposed control system.

This paper is authored to describe a control framework that is designated for realizing cyclic, actively-compliant and dynamically-balanced jumping and trotting quadruped locomotion over rough terrain. In order to succeed in exhibiting such locomotion abilities, two controllers are synthesized: i) Active Compliance Control via force feedback, ii) Angular Momentum Control via gyro sensing. The first controller computes the joint displacements that are associated with ground reaction force errors, using Jacobian transpose and admittance blocks. Together with position constraints, these joint displacements are simultaneously fed-back to local servo controllers; allowing the robot to perform the given locomotion task in an actively-compliant manner. The second controller, in the meantime, evaluates gyro sensor information to calculate the required compensation torque about center of mass, which is necessary to regulate upper torso rotational motion. Afterwards, it updates the orientation input in accordance with this compensation torque. Using the proposed framework, the overall control performance is tested via cyclic jumping and trotting motion experiments, conducted over rough terrain with a stiff-by-nature quadruped robot. Results turn out to be positive; the robot demonstrates successful jumping and trotting cycles in a repetitive, actively-compliant and dynamically-balanced fashion.

This paper is written to report our research group's recent activities that are concerning quadruped locomotion control. To this end, we primarily constructed an electrically-actuated quadruped robot which is employed as an experimentation platform to test the locomotion control algorithm. An overall motion control scheme is introduced to reveal the main principles for achieving fast and agile locomotion scenarios. Having disclosed prototype development and real-time control procedures, trot-running locomotion experimental results are presented. In these experiments, the robot exhibited successful trot-running cycles in a repetitive, dynamically-equilibrated, agile, and compliant manner; demonstrating that the control algorithm has potentials to be utilized in fast locomotion tasks.

In this study we give a feedback control method for steering support system. In this method we consider the stability of the path tracking control system under the limitation of steering angle, so that drivers can drive more safety and comfortable. In order to do this, we have derived linearized system from the nonholonomic kinematic system by the flatness consideration and linear control law which stabilizes the path tracking control system. Furthermore, feedback gains are tuned to satisfy the closed loop stability and limitation of the steering angle. Usefulness of the proposed control method has been demonstrated by experiments using 1/10 scaled robot car.

This paper is aimed at presenting a framework that consists of a pattern generator and a controller, which are combined together to realize continuous and dynamically equilibrated running motion on a 4-link 3-DoF one-legged robot with no passively compliant elements. Initially, we make use of a pattern generator to synthesize dynamically-consistent running trajectories in which the rotational inertia and the associated angular momentum term are characterized. As for the controller, ground reaction force constraints are imposed to the system indirectly. For this purpose, joint torque values that are corresponding to horizontal and vertical force errors are computed. Subsequently, they are inserted to an admittance filter block to obtain the associated joint displacements. These joint displacements are then fed-back to local servo controllers to implement indirect force feedback control in an actively compliant manner. Additionally, friction compensation and foot orientation controller blocks are added to enhance the system performance. In order to validate the method, running experiments are conducted on the actual one-legged robot. As the result, we satisfactorily obtained continuous, dynamically equilibrated and repetitive running cycles.

This work presents a new theoretical approach to hybrid position/force control. It develops a method for the design of controllers of constrained manipulators. In this work also the robustness considerations are given. It can be shown that the proposed control system has robustness properties for a class of dynamic uncertainties. In order to improve the robustness property integral controller is applied to the force control loop. The usefulness of this hybrid control system is demonstrated through simulations of a constrained two degrees of freedom robot manipulator.

Recently an industrial multi-link robot is expected to be applied to precision machining. However, the multi-link robot manipulators are highly coupled non-linear systems and their equations of motions are hardly identified. Therefore it has been thought that precision machining using a multi-link robot is impossible. In this paper, a new type of precision machining robot in proposed. This robot consists of a multi-link robot and the machining unit for micro-positioning. The control system of this robot is modelled as the singular perturbed system and is applied to the position control and electric discharge machining (EDM) control.

Various types of linear motor have been developed. However, most of them are only applied to positioning control. High compliance property of the linear motor has not been used effectively. Then there are few types of linear motor which can be applied to manufacturing unit.In this study, we developed a differential linear motor which has some advantages suitable for manufacturing unit. The new type of the linear motor has been expected to be applied not only to positioning unit but also to active compliance unit of robot manipulators. Therefore, we applied pseudo diagonalization method to the position and compliance control of the developed differential linear motor. In the position control part dither signal was used after diagonalization. Amplitude of the dither signal was modified by error signals. In the compliance control part PID controller was used. The effectiveness of the proposed control system was shown through experiments.

Pneumatic actuators are less expensive and have higher power/weight ratio than other types of actuators. On the other hand, it is very difficult to control the pneumatic actuators because of uncertainties caused by the nonlinear pneumatic circuit and large friction caused by mechanical contact between piston-ring and cylinder. Then the pneumatic actuator has hardly applied to precise positioning and smooth drive control.In this paper we applied optimal control theory and model feedback control scheme to control of the pneumatic cylinder in order to realize both the precise positioning and the smooth driving. The effectiveness of the proposed control system is shown through experiments. Results of these experiments are compared with the results which were carried out by fuzzy control logic.

This work presents a new robust control methodology for hybrid position/force control. The control input of this methodology consists of a nonlinear and a linear part. The nonlinear control part gives a new coordinate system. Using this coordinate system. robot dynamics is decoupled and input spaces are divided into two orthogonal spaces of position and force control. The linear control part improves robustness properties of the nonlinear hybrid control scheme. A model feedback control scheme is applied to the linear part or position control and integral control is used in the linear part of force control. The robustness properties of the nonlinear robust hybrid control algorithm are demonstrated through simulation of a constrained two degrees of freedom robot manipulator.

Precise control of manipulators in contact with constrains in their environments is a prerequisite to feasible application of robot manipulators to complex handling and assembly problems in industry and space. An important step toward achieving such control is to control simultaneously position and force trajectory. Through recent advances in robotics technology many control design methodologies have been proposed for the control of robot manipulators. The hybrid technique is well known technique in these methodologies. In this technique coordinate system on the constrains plays an important role. But decision scheme of the coordinate system has not been proposed clearly.This paper analyzes the hybrid technique based on the constrained control system and proposes a new conceptually simple approach to the hybrid technique. The new approach is able to control simultaneously manipulator impedance and position trajectories on the constrains. The coordinate system is appropriately selected and divided into two coordinate systems. These two coordinate systems represent two independent input spaces where the hybrid technique is realized.Finally we also present the results of experiments that explore application of the hybrid technique to a control of a two degrees of freedom manipulator.

In parallel mechanisms with redundant actuators, actuator forces are underspecified because of redundancy. In this paper, the method to minimize a maximum actuator force was proposed. At first, parallel mechanism with two redundant actuators and Stewart platform model using the linear shaft motor were developed. This redundant parallel mechanism was consists of Stewart platform and additional 2 redundant actuators. Inverse dynamics of each mechanisms were formulated. Secondly, effectiveness of dynamic control of Stewart platform was experimentally confirmed. Finally, the method to minimize a maximum actuator force using Linear Matrix Inequality (LMI) was proposed. And the effectiveness of the proposed method was confirmed by simulation.

This study discusses the positioning and vibration control of time-varying vibration systems whose parameters are time-varying. We assume that the time-varying parameter of a vibration system is detected by an on-line measurement or Wavelet analysis. This paper treats two control methods based on nonstationary optimal regulators (NORs) for this problem. The first method is a gain-scheduling of NORs. An actual controller is obtained by the interpolation of plural NORs designed a priori. The other one is an NOR design based on Wavelet analysis of the vibration system. In the second case, single NOR derived from the analysis result is applied. This study shows the effectiveness of these methods by numerical calculations and experiments. From the comparison of these methods, this paper suggests suitable applications of NOR according to the characteristics of each control problem.Copyright © 2003 by ASME

In this paper, a simple control methodology for macro/micro manipulator system is proposed. The macro/micro manipulator system consists of a multi-link rigid body manipulator as a macro manipulator and a machining unit mounted on the end-effector of the macro manipulator as a micro manipulator. It is shown that the state equations of the proposed macro/micro manipulator system are identical with the singular perturbed system. A simple method of control system design of this system can be derived from the singular perturbation theory. Simulation results show that the proposed control scheme perfectly compensates the tracking errors. An experimental verification of the proposed control algorithm is shown by applications to electrodischarge machining. >

Since system uncertainties are unavoidable in the modeling, control systems are generally required to be insensitive to these uncertainties. In this paper, the problem of control system design which is insensitive to these uncertainties is studied, and a structure of system uncertainties which do not affect the control performance is clarified.

グラインディングロボットにおいて, マニピュレータに取りつけられたグラインダは, マニピュレータの剛性が低いために, 振動姓じやすく, そして時には, 不安定にさえなる.その振動は研削面を荒くしまた, 鞍定状態はマニピュレータを破損に至らしめることがある.本論文は, 研削時のグラインダの安定性について議論している.加工物の平面部が研削されるとき, 加工面の接線方向に対するグラインダの運動は線形微分方程式で記述される.この式から, グラインダの安定性は, マニピュレータの剛性マトリックス, 被削面の傾斜角, 加工物とグラインダの摩擦係数に依存することが示される.一方, 曲面上の研削の場合, 微分方程式は非線形になる.その場合, 研削の安定限界は, 被削面の曲率の影響を強く受ける.グラインディングロボットの曲面研削においては, グラインダを安定に支持するために, マニピュレータのリストが曲面に応じて制御されなければならないことが示されている.

When an industrial robot grinds a curved surface of a workpiece, an operator must teach the robot the contour of the surface accurately. This instruction, however, is a very troublesome job because of the large number of teaching points. This paper proposes a grinding robot that requires no teaching. The robot system consists of a manipulator mounted on a cylindrical grinding wheel on the end effector, instruments to measure the three different forces and a computer equipped with an A/D converter. The force information consists of the grinding torque and the two components of the grinding force which is applied to the grinding wheel from the workpiece. The coordinates of the points where the wheel contacts the workpiece are calculated from the force information by the computer. Therefore, the robot is able to recognize the contour of the workpiece and to grind it without teaching. Experiments using an articulated robot arm with five degrees of freedom show that the proposed robot system is applicable to t...