Mehrdad Boroushaki

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A six-degree-of-freedom musculoskeletal model of the lumbar spine was developed to predict the activity of trunk muscles during light, moderate and heavy lifting tasks in standing posture. The model was formulated into a multi-objective optimization problem, minimizing the sum of the cubed muscle stresses and maximizing the spinal stability index. Two(More)
In this paper, the agent velocity in robotic swarm was determined by using particle swarm optimization (PSO) to maximize the robotic swarm coordination velocity. A swarm as supposed here is homogenous and includes at least two members. Motion and behavior of swarm members are mostly result of two different phenomena: interactive mutual forces and influence(More)
In this paper, the path planning problem of special hyper-redundant manipulator with lockable joints is solved using particle swarm optimization. There is a locking mechanism in each link of this tendon-actuated manipulator. At any time, all links of the manipulator must be locked except one. Then by pulling the cables, the configuration of the(More)
Purpose: Force control of robotic instruments is a difficult task due to the uncertainties caused by changes in the instrument's geometrical and mechanical characteristics during surgery as well as the nonlinear dynamics of the instrument. A new approach based on an intelligent controller is developed to control the force interactions of a robotic surgical(More)
Great effect of three way catalytic convertor (TWC) performance on oxygen sensor output voltage has made the sensor (located after catalyst) as the main signal in almost all today's TWC monitoring algorithms. In this paper output voltage of nonlinear oxygen sensor is estimated using a nonlinear autoregressive with exogenous inputs (NARX) model. The(More)
Despite development of accurate musculoskeletal models for human lumbar spine, the methods for prediction of muscle activity patterns in movements lack proper association with corresponding sensorimotor integrations. This paper uses the directional information of the Jacobian of the musculoskeletal system to orchestrate adaptive critic-based fuzzy neural(More)
In this paper, a robust control design strategy is introduced to synchronize two different chaotic systems. The controller is based on particle swarm optimization (PSO). Particle swarm optimization is a well-known evolutionary optimization algorithm inspired by organism behavior of birds flocking and fish schooling. Our control approach is based on defining(More)
Most of the strategies yet implemented to optimize fuel loading pattern design in the nuclear power reactors, are based on maximizing the core effective multiplication factor (Keff) in order to extract maximum energy and to reduce the local power peaking factor (Pq) from a set value. However, a new optimization criterion would be of interest in order to(More)
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