Michihiro Kawanishi

A framework for sensorless torque estimation and control in wearable exoskeletons

This paper is aimed at describing a framework to implement sensorless torque estimation and control in wearable exoskeletons, for the purpose of handling power augmentation tasks. The proposed method relies on accurately identifying and compensating the joint-level disturbance torques caused by stiction, viscous friction, and gravitational loads. Utilizing off-the-shelf techniques, the characteristics of these disturbances are primarily identified. Subsequently, additional torque inputs are superimposed to the system via feedforward loops in a way to counteract to these disturbances. Having compensated frictional and gravitational loads acting on the actuation module; we are able to estimate the external torque exerted at each joint by using disturbance observers. In this manner, torque control is enabled without any requirement of built-in torque sensing units. In order to validate the proposed framework, we conducted weight lifting and upholding experiments on able-bodied human subjects with and without wearing the upper extremity of exoskeleton suit. Comparison of EMG and IEMG signals acquired in two cases indicates that the exoskeleton system provides sufficient power augmentation reliably. In conclusion, the proposed method is validated to be efficient and it can be potentially used for rehabilitation, training and power augmentation tasks.

BMI global optimization based on branch and bound method taking account of the property of local minima

This paper deals with the global optimization of the BMI (bilinear matrix inequalities) eigenvalue problem. At first, we clarify some geometric properties of local minima of the BMI optimization problem. Then, based on these results, we give a modified branch and bound method for the BMI global optimization which improves the numerical efficiency, and demonstrate its optimization process by a simple numerical example.

Parameter estimation for the pitching dynamics of a flapping-wing flying robot

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.

Continuous and dynamically equilibrated one-legged running experiments: Motion generation and indirect force feedback control

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.

Design of /spl mu/ suboptimal controllers based on S-procedure and generalized strong positive real lemma

This paper is concerned with a design method for a /spl mu/ suboptimal controller. Based on the S-procedure and a generalized strong positive real lemma, we derive a new less conservative LMI condition for uncertain systems to achieve /spl mu/</spl gamma/ for all frequencies. With our condition, we can design /spl mu/ suboptimal controllers by means of BMI optimization.

Controller design of two-mass-spring system based on BMI optimization

This paper gives a design example of multipurpose controllers for two-mass-spring systems based on BMI optimization technique. The obtained controller achieves (a) tracking with zero steady-state error, (b) pole placement in a prescribed region, and (c) optimal H/sub /spl infin// performance, simultaneously in the presence of physical parameter uncertainties. In addition, its effectiveness is demonstrated via simulations and experiments.

Robust position control of Delta Parallel mechanisms using dynamic model and QFT

This paper presents a solution to the residual vibration of 3-DOF Delta parallel robots. As the parallel mechanism is highly nonlinear, inverse dynamics analysis in explicit form by using Lagrangian formulation is proposed to linearize the system. To apply the Lagrangian method to the parallel mechanism, the structure is divided to sub-chains by imaginary open tree method. After deriving inverse dynamics in analytical form, system is linearized. To control the linearized system, Quantitative Feedback Theory is applied and vibration suppression during the high-speed motion is achieved. Usefulness of the linearization and QFT method to control the high-speed parallel mechanism is shown through experiments.

Stabilization of Polynomial Systems with Bounded Actuators using Convex Optimization

Abstract State-feedback stabilization of polynomial systems with bounded input magnitudes is addressed in this paper. Stabilizing controllers are constructed using polynomial or rational Lyapunov functions. The stabilizing conditions with respect to both the classes of Lyapunov functions can be formulated as parameter-dependent linear matrix inequalities (PDLMIs), which can be efficiently solved by the sum-of-squares (SOS) technique. In order to reduce the conservatism of the previous design, a post-design approach is proposed by introduction of polynomial annihilators. A numerical example is provided to illustrate the proposed approach.

Application of Sigmoidal Gompertz Curves in Reverse Parallel Parking for Autonomous Vehicles

A new method for the planning and autonomous execution of a single-trajectory, velocity-independent, parallel parking manoeuvre for autonomous vehicles is presented. The procedure commences with the identification and pre-selection of a smooth sigmoidal trajectory known as the Gompertz curve in parametric format. Trajectory parameters are determined in real-time during the path-planning phase using an optimization scheme in order to generate a candidate path. The optimization scheme takes into account the maximum steering angles that can be physically realized and checks the generated candidate trajectory for collisions. Thereafter, the trajectory is reparametrized to arc-length format using the cubic interpolation method and the vehicle orientation at every point of the trajectory is deduced. Following that, values of the steering angle(s) are determined. In the final step, the vehicle uses dead-reckoning to follows the arc-length parametrized path in reverse in order to park itself in a single-manoeuvre. The proposed method is substantiated through both extensive simulations and real sensor data.

Prototype development and real-time trot-running implementation of a quadruped robot: RoboCat-1

This paper is written to report our research groups 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.