Movement selection and control is a very difficult inverse dynamics problem for robotic control that humans and animals accomplish easily. For the past 10 years there has been a popular theory that biological movement is made up of sub-routine type blocks, or ‘motor primitives’, with a central controller timing the activation of these blocks, creating synergies of muscle activation. Using machi...

In contrast to most scientific disciplines, sports science research has been characterized by comparatively little effort investment in the development of relevant phenomenological models. Scarcer yet is the application of said models in practice. We present a framework which allows resistance training practitioners to employ a recently proposed neuromuscular model in actual training program de...

in this study, stability control of a three-wheeled vehicle with two wheels on the front axle, a three-wheeled vehicle with two wheels on the rear axle, and a standard four-wheeled vehicle are compared. for vehicle dynamics control systems, the direct yaw moment control is considered as a suitable way of controlling the lateral motion of a vehicle during a severe driving maneuver. in accordance...

This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM) algorithm so that an approximation of the inverse system ...

The Feedback Error Learning (FEL) for Functional Electrical Stimulation (FES) controller was examined through computer simulation using a musculoskeletal model. Feedforward controller of the FEL controller consisted of the inverse dynamics model (IDM) and the inverse statics model (ISM) in order to achieve successful learning. The new controller showed better performance in learning of the feed...

This paper presents a combined strategy for tracking a non-holonomic mobile robot which works under certain operating conditions for system parameters and disturbances. The strategy includes kinematic steering and velocity dynamics learning of mobile robot system simultaneously. In the learning controller (neural network based controller) the velocity dynamics learning control takes part in tra...

This paper is a review of different approaches and models underlying the voluntary control of human hand-arm movement. These models, dedicated to artificial movement simulation with application to motor control, robotics and computer animation, are categorized along at least three axis: Direct vs. Inverse models, Dynamics vs. Kinematics models, Global vs. Local models. We focus on sensory-motor...

A new dynamics-driven control law was developed for a robot arm, based on the feedback control law which uses the linear transformation directly from work space to joint space. This was validated using a simulation of a two-joint planar robot arm and an optimisation algorithm was used to find the optimum matrix to generate straight trajectories of the end-effector in the work space. We found th...

This paper is a review of different approaches and models underlying the voluntary control of human hand-arm movement. These models, dedicated to artificial movement simulation with application to motor control, robotics and computer animation, are categorized along at least three axis: Direct vs. Inverse models, Dynamics vs. Kinematics models, Global vs. Local models. We focus on sensory-motor...

The problem of variational data assimilation (DA) for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition, boundary conditions and/or model parameters. The input data contain observation and background errors, hence there is an error in the optimal solution. For mildly nonlinear dynamics, the covariance matrix of the optimal solution error can b...