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 article proposes an approach to generate high-level test patterns from the arithmetic model of a register-transfer-level (RTL) circuit using a hybrid canonical data structure based on a decision diagram. High-level simplified and fast symbolic path activation strategy as well as input justification is combined with test pattern generation for circuits under consideration. For simplification of a test procedure, some ATPG approaches have been introduced based on binary decision diagram (BDD) tools. Since these methods require the design to be flattened into the bit level, they cannot be used to deal with large industrial benchmarks efficiently, either in terms of memory or runtime.... 

This paper proposes a high-level test generation method which considers the control part as well as data path of a register transfer level circuit as a set of polynomial functions to generate behavioral test patterns from faulty behavior instead of comparing the faulty and fault-free circuits based on a hybrid Boolean-word canonical representation called Horner expansion diagram. Since this set of polynomial functions express primary outputs and next states with respect to primary inputs and present states, it is not necessary to perform justification/propagation phase which leads to a minimum number of backtracks. It improves fault coverage and reduces test generation time over logic-level... 

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... 

This paper presents a simulation-based study of the stuck-open fault testing in CMOS logic circuits. A novel built-in self-test (BIST) technique is presented for detecting stuck-open faults in these logic families. This scheme does not need test-pattern generation, and thus can be used for robust on-line testing. Simulation results for area, delay, and power overheads are presented. © 2007 IEEE  

Cerebellum has been assumed as an array of adjustable pattern generators (APGs). In recent years, electrophysiological researches have suggested the existence of modular structures in spinal cord called motor primitives. In our proposed model, each "adjustable primitive pattern generator" (APPG) module in the cerebellum is consisted of a large number of parallel APGs, the output of each module being the weighted sum of the outputs of these APGs. Each spinal field is tuned by a coefficient, representing a descending supraspinal command, which is modulated by ith APPG correspondingly. According to this model, motor control can be interpreted in terms of the modification of these coefficients.... 

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... 

In this study, a gait optimization routine is developed to generate walking patterns which demand the lowest friction forces for implementation. The aim of this research is to fully address the question “which walking pattern demands the lowest coefficient of friction amongst all feasible patterns?”. To this end, first, the kinematic structure of the considered 31 DOF (Degrees of Freedom) humanoid robot is investigated and a closed-form dynamics model for its lower-body is developed. Then, the medium through which the walking pattern generation is conducted is presented. In this medium, after designing trajectories for the feet and the pelvis, the joint space variables are obtained, using... 

Context: Generating test cases based on software input interface is a black-box testing technique that can be made more effective by using structured input models such as input grammars. Automatically generating grammar-based test inputs may lead to structurally valid but semantically invalid inputs that may be rejected in early semantic error checking phases of a system under test. Objective: This paper aims to introduce a method for specifying a grammar-based input model with the model's semantic constraints to be used in the generation of positive test inputs. It is also important that the method can generate effective test suites based on appropriate grammar-based coverage criteria....