This paper studies the decentralized control of a large platoon of identical vehicles which are moving on a plane, where each vehicle is assumed to have steering dynamics;each vehicle in this case is assumed to be des...
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Many interesting design problems encountered in signal processing and control turn out to depend on a set of decision variables that can only take a finite number of values, i.e., they are quantized. For example, in p...
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A multi-level model, that provides a hierarchically structured description of a complex, multi-scale limb system is proposed in this paper for predicting and analyzing movement patters generated by various activation ...
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in this paper, the design of a fault detection filter for nonlinear systems is presented. The nonlinear system is represented as a sequence of linear time- varying approximations and at each linear approximation the d...
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We present a receding horizon control algorithm for compensation of backlash at the input of a stable linear system under control rate constraints. The problem is first posed as a receding horizon optimal control prob...
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The full-bridge converter with current-doubter synchronous rectifier (FB-CDSR) is a promising topology to implement low-voltage high-current power supplies. This paper proposes a novel control for this converter, whic...
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The current work presents an API based on the Real-Time Specification for Java (RTSJ) that optimizes real-time embedded systems development. Using this API it is possible to state non-functional specifications, like t...
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The current work presents an API based on the Real-Time Specification for Java (RTSJ) that optimizes real-time embedded systems development. Using this API it is possible to state non-functional specifications, like time constraints, and guarantee its implementation in the selected platform. Moreover, it discusses how real-time requirements derived from the RT-UML standard can be mapped to the elements from the proposed API. An integrated toolset is used to support the intermediate steps of this mapping process. The paper illustrates the mapping mechanism by means of a case study that implements the control system of an automated wheelchair.
This research is aimed at the development of a dynamic control to enhance the performance of the existing dynamic controllers for mobile robots. System dynamics of the car-like robot with non-holonomic constraints wer...
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In the model predictive control (MPC) framework a controller is computed using a finite horizon optimal control cost. When linear constraints are imposed on the system with a quadratic cost function, then the MPC prob...
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In the model predictive control (MPC) framework a controller is computed using a finite horizon optimal control cost. When linear constraints are imposed on the system with a quadratic cost function, then the MPC problem can be reformulated as a constrained quadratic programming (QP) problem. In this paper active set methods are used in order to solve the QP problem associated with MPC, and it is shown that it is possible to use information from the previous sample interval in order to provide improved initial conditions for the QP problem which is applied to the subsequent sample interval. Simulations show that when real-time considerations force the used of suboptimal intermediate control values, then improved initial conditions can allow for control values which are closer to the true optimal solution than obtained when using standard initial conditions. These ideas can allow for the implementation of MPC schemes on a greater number of real industrial applications, where standard MPC control cannot be applied due to the excessive CPU time requirements
It is well known that the nonblocking supervisory control problem is NP-hard, subject in particular to combinatorial state explosion that is exponential in the number of system components. To manage this complexity we...
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It is well known that the nonblocking supervisory control problem is NP-hard, subject in particular to combinatorial state explosion that is exponential in the number of system components. To manage this complexity we introduce state tree structures (STS), an adaptation of statecharts to the supervisory control theory. The systems to be controlled are modeled as STS hierarchies encoded by binary decision diagrams. This approach is capable of dealing with discrete-event systems of industrial size; furthermore the controllers are highly structured and comprehensible to non-specialists
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