In this paper, the design and implementation of a novel passive safe joint is reported. This safe joint is designed for applications, such as an air hockey playing robot playing against a human, in which the force app...
详细信息
In this paper, the design and implementation of a novel passive safe joint is reported. This safe joint is designed for applications, such as an air hockey playing robot playing against a human, in which the force applied by the linkage should be kept below a certain threshold. The proposed mechanism benefits from the compliance of two ramps controlled by the nonlinear behavior of a spring. The passivity of the design, the small footprint, the low cost of production, and the ability to rotate 360 degrees are the main advantages of this design. The mechanism has been designed, evaluated, implemented and tested showing its effectiveness. Finally it has been incorporated in an air hockey robot showing its capability in action.
In this study, a developed automatic sleep stage classification system with a portable EEG recording device, (Mindo-4s) is implemented by JAVA-based sleep graphical user interface (GUI) in android platform. First, the...
详细信息
Many systems repeat the same operation over and over again on a finite duration. Repetitive processes have this characteristic where repeated sweeps, termed passes, are made over the finite pass length and when each i...
Many systems repeat the same operation over and over again on a finite duration. Repetitive processes have this characteristic where repeated sweeps, termed passes, are made over the finite pass length and when each is complete the process resets to the starting location and the next pass begins. The distinguishing feature of these processes is that the output, or pass profile, produced on each pass explicitly contributes to the dynamics of the next one and can result in oscillations that increase in amplitude from pass-to-pass. For applications, it is necessary to have a stability theory on which to base control law design for stabilization and performance. This paper gives a reflective overview of the stability theory for linear repetitive processes with particular attention to the forms of stability possible, their characterizations, and suitability for control law design. A particular feature is that the strongest form of stability for these processes can, especially for applications, lead to difficulties in control law design for stability and performance. One alternative in such cases is also considered.
Identifying the structure and arrangement of the teeth is one of the dentists' requirements for performing various procedures such as diagnosing abnormalities, dental implant and orthodontic planning. In this rega...
详细信息
Identifying the structure and arrangement of the teeth is one of the dentists' requirements for performing various procedures such as diagnosing abnormalities, dental implant and orthodontic planning. In this regard, robust segmentation of dental computerized Tomography (CT) images is required. However, dental CT images present some major challenges for the segmentation that make it difficult process. In this research, we propose a multi-step approach for automatic segmentation of the teeth in dental CT images. The main steps of this method are presented as follows: 1-Primary segmentation to classify bony tissues from nonbony tissues. 2-Separating the general region of the teeth structure from the other bony structures and arc curve fitting in the region. 3-Individual tooth region detection. 4-Final segmentation using mean shift algorithm by defining a new feature space. The proposed algorithm has been applied to several Cone Beam Computed Tomography (CBCT) data sets and quality assessment metrics are used to evaluate the performance of the algorithm. The evaluation indicates that the accuracy of proposed method is more than 97 percent. Moreover, we compared the proposed method with thresholding, watershed, level set and active contour methods and our method shows an improvement in compare with other techniques.
As life science progress and its consequences provide human life necessities, controlling these kinds of processes has recently become very important. Unfortunately because of including delay and nonlinear behavior of...
详细信息
ISBN:
(纸本)9781467355339
As life science progress and its consequences provide human life necessities, controlling these kinds of processes has recently become very important. Unfortunately because of including delay and nonlinear behavior of micro-organisms these processes have nonlinear time varying model and so controlling them is too complicated. These nonlinear dynamics are too slow and so it is possible to linearize the model step by step and apply control signal to the local linearized models. In this paper we design a model predictive controller for each linearized model at time unit and as a result a nonlinear time varying system has been controlled properly. As these localized models are open loop unstable, we have to use close loop paradigm also due to its numerically robustness. Finally result has validated with experimental values and reliability of this approach has been exposed.
We study in this paper the consensus problem for multi-agent systems with agents characterized by high-order linear systems with time delays in both the communication network and inputs. Provided that the open-loop dy...
详细信息
ISBN:
(纸本)9781479900305
We study in this paper the consensus problem for multi-agent systems with agents characterized by high-order linear systems with time delays in both the communication network and inputs. Provided that the open-loop dynamics of the agents is not exponentially unstable, but may be polynomially unstable, and the communication topology contains a directed spanning tree, a truncated predictor feedback approach is established to solve the consensus problem. It is shown that, if the delays are constant and exactly known, the consensus problems can be solved by observer based output feedback protocols for arbitrarily large yet bounded delays. If it is further assumed that the open-loop dynamics of the agents only contains zero eigenvalues, the delays are allowed to be time-varying and unknown.
Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of ...
详细信息
ISBN:
(纸本)9781467355339
Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of micro-organisms. Model predictive control is one of the most popular advanced controlling strategies in this industry, however its dependence on accurate model for predicting future input and output values is limitating. If there is a way that could predict the future values of the process properly, it is possible to overcome to the existing challenges. In this paper we design a model free predictive controller by using a trained recurrent neural network as a predictor for prediction stage at MPC and using GA for solving the associated optimization problem that result the optimal control signal sequence.
Actor-critic reinforcement learning algorithms have shown to be a successful tool in learning the optimal control for a range of (repetitive) tasks on systems with (partially) unknown dynamics, which may or may not be...
详细信息
Actor-critic reinforcement learning algorithms have shown to be a successful tool in learning the optimal control for a range of (repetitive) tasks on systems with (partially) unknown dynamics, which may or may not be nonlinear. Most of the reinforcement learning literature published up to this point only deals with modeling the task at hand as a Markov decision process with an infinite horizon cost function. In practice, however, it is sometimes desired to have a solution for the case where the cost function is defined over a finite horizon, which means that the optimal control problem will be time-varying and thus harder to solve. This paper adapts two previously introduced actor-critic algorithms from the infinite horizon setting to the finite horizon setting and applies them to learning a task on a nonlinear system, without needing any assumptions or knowledge about the system dynamics, using radial basis function networks. Simulations on a typical nonlinear motion control problem are carried out, showing that actor-critic algorithms are capable of solving the difficult problem of time-varying optimal control. Moreover, the benefit of using a model learning technique is shown.
Recently, several control systems for closed-loop anesthesia have been demonstrated both in simulation and clinical studies. A set of performance measures, proposed by Varvel et al., have constituted the standard mean...
详细信息
ISBN:
(纸本)9781479909964
Recently, several control systems for closed-loop anesthesia have been demonstrated both in simulation and clinical studies. A set of performance measures, proposed by Varvel et al., have constituted the standard means of comparing such systems. This paper debates the adequacy of the Varvel measures, as applied to closed-loop anesthesia, and proposes an alternative set of measures. Key features of the proposed measures are: wide acceptance within the control community;reflection of clinical feasibility;separate measures for induction and maintenance of anesthesia;separation of outlier detection and performance evaluation. The proposed measures are descriptive, few, and easy to compute.
暂无评论