Sharif Digital Repository

The central pattern generators have been considered as a method to simplify the control of the complex rhythmic motions, e.g., walking, by the central nervous system. In this study, a control structure was designed to control the soleus and tibialis anterior muscles in a complete gait cycle. The activation patterns of the muscles were measured experimentally and used as the reference signals of a tracking problem. The hip angle and ground reaction force were also used as a feedforward. The feedback from the Golgi tendon acted as a regulator of muscle activity. The controller was applied to two gait trials. The results indicated that the designed controller was capable of tracking the... 

The canonical problems in control of the biped robots arise from underactuation, impulsive nature of the impact with the environment and existence of the many degrees of freedom in their mechanism. Since biped walkers have fewer actuators than degrees of freedom, they are underactuated mechanical systems. In this paper according to the humans and animals locomotion algorithms, the stability of an underactuated biped walker with point feet is done by Central Pattern Generator (CPG) and feedback networks. For tuning the parameters of the CPG network, the control problem is defined as an optimization problem. This optimization problem is solved by using of Genetic algorithm. Also a new feedback... 

The role of motor control in development of low back pain is subject of many researches both in theoretical and experimental fields. In this work flexion-extension movement of lumbar spine have been controlled by three different methods, including feedback linearization (FBL), PD control and their combinations. The model involves 7 links: 1 link for pelvis, 5 links for lumbar vertebrae and 1 link for trunk. Torque actuators have been used on each joint to make them follow desired trajectory. In linear control method, equations of motion have been linearized with respect to upright position and then control signals have been applied in the direction of eigenvectors. Robustness of each method... 

According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors... 

The central pattern generators (CPG) in the spinal cord are thought to be responsible for producing the rhythmic motor patterns during rhythmic activities. For locomotor tasks, this involves much complexity, due to a redundant system of muscle actuators with a large number of highly nonlinear muscles. This study proposes a reduced neural control strategy for the CPG, based on modular organization of the co-active muscles, i.e., muscle synergies. Four synergies were extracted from the EMG data of the major leg muscles of two subjects, during two gait trials each, using non-negative matrix factorization algorithm. A Matsuoka׳s four-neuron CPG model with mutual inhibition, was utilized to... 

According to the fact that humans and animals show marvelous capacities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground, the problem of controlling the biped robots is difficult. In other words, the biped walkers have fewer actuators than the degrees of freedom. So they are underactuated mechanical systems. In this paper according to the humans and animals locomotion algorithms, the stability of an underactuated biped walker having point feet is investigated by central pattern generators. For tuning the parameters of the CPG, an effective energy based... 

The complexity associated with musculoskeletal modeling, simulation, and neural control of the human spine is a challenging problem in the field of biomechanics. This paper presents a novel method for simulation of a 3D trunk model under control of 48 muscle actuators. Central pattern generators (CPG) and artificial neural network (ANN) are used simultaneously to generate muscles activation patterns. The parameters of the ANN are updated based on a novel learning method used to address the kinetic redundancy due to presence of 48 muscles driving the trunk. We demonstrated the feasibility of the proposed method with numerical simulation of experiments involving rhythmic motion between upright... 

The canonical problems in control of the biped robots arise from underactuation, impulsive nature of the impact with the environment and existence of the many degrees of freedom in their mechanism. Since biped walkers have fewer actuators than degrees of freedom, they are underactuated mechanical systems. In this paper according to the humans and animals locomotion algorithms, the stability of an underactuated biped walker with point feet is done by central pattern generator and feedback networks. For tuning the parameters of the CPG network, the control problem is defined as an optimization problem. This optimization problem is solved by using of Genetic algorithm. Also a new feedback... 

According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors...