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In this paper, a formation problem of a satellite with a leader in an eccentric orbit is considered, where the transition to a periodic relative orbit is required, and the control input is restricted to a subinterval of the period of the leader's orbit. As preliminaries, the same problem in the special case of the circular orbit is considered, and feedback controls based on a differential Riccati...
In this paper, we present a robust recursive filtering algorithm for discrete time-varying systems with sensor failures and uncertain parameters in their state space models. The exiting results are generalized to the case where each sensor may fail at any sample time independently of the others. For robust performance, stochastic parameter uncertainties are included in the system matrix. The design...
This paper proposes a new control method for a weigh feeder. A weigh feeder has been widely employed in industry because it can dispense powder at a specified rate or amount. The proposed controller is mainly divided into a feed-forward and a feedback compensators. In order to obtain a simple controller, the former gives a steady-state control input designed using a nominal plant gain, and the latter...
This paper presents a decentralized method to the problem of multiple unmanned aerial vehicles (UAVs) cooperative search of an unknown area. Firstly, based on search map model, the multiple UAVs cooperative search problem is posed as a receding horizon (RH) optimization decision problem, and a RH based UAV search decision process is proposed. Then, this centralized online optimization problem is partitioned...
This paper studies the tracking performance of linear time-invariant (LTI) single-input single-output (SISO) discrete-time networked feedback systems. We take the system's reference input as a step signal, and assume that the controller output is first quantized and next transmitted over a communication network to the plant, whereas the quantization error is modeled as a white noise. We are interested...
In most batch processes, quality control measurements cannot be completed before the next batch operation. Thus, the corrective step is often delayed by one batch or more. The uncertain duration of delay with stochastic characteristics can be treated as a random variable of unknown distribution. Coupled with inaccurate process models, the delay may lead to significant process output variations even...
The problem of robust Hinfin guaranteed control for the descriptor systems with time-delay and parameter uncertainty is considered. A sufficient condition for the existence of non-fragile Hinfin controller is presented in terms of linear matrix inequality such that the resulting closed-loop system is robustly stable and guarantees Hinfin performance index. It is proved that the condition also satisfies...
Networked control system (NCS) is a newly emerging topic within control theory community. In this paper we pay particular attention to the problem concerning data rate constraint. Motivated by many successful results in related research, we study the lowest data rate needed to stabilize an LTI system when the controller structure is limited to be a static state feedback and the channel is modeled...
In this paper, a controller for the singularly perturbed system is designed in detail to satisfy frequency-domain loop-shaping specifications which are given in terms of Hinfin norm, moreover, the controller has the similar structure with the full system. It is further shown that this controller is obtained through designing its fast and slow parts. The main contribution of this paper is that the...
This paper presents the design of a neural network-based feedback linearisation (NARMA-L2) slip controller for an anti-lock braking system (ABS). The dynamics of the electro-mechanical based braking system are incorporated in the ABS model and thus a slip controller is developed to minimise the braking distance. The proposed controller is compared with an optimally-tuned PID controller. Simulation...
Computationally efficient robust model predictive control algorithm applicable for linear systems with polytopic model uncertainty as well as bounded additive disturbances is explored. A form of control scheme consisting of a static state feedback and a dynamically evolving perturbation is used in such a way that the cost function can be minimized in a receding horizon fashion over a pre-determined...
Parametric optimization techniques is an established practice for designing controllers. It was used, for example, to obtain the parameters of PI and PID controllers in several works. An important criticism to this technique is the dependence of the design from a parametric model of the plant, which have to be very accurate. In the current work, the problem of designing a continuous-time PID controller...
A novel integration of design and controllability method is proposed for the process design under uncertainty. The key idea is to integrate the robust eigenvalue assignment with the robust optimal design to achieve the desirable design performance and dynamic performance. The robust optimal design is to have a trade-off between robustness and optimization for the steady-state economic design, and...
This paper examines a time optimal control problem for a dielectrophoretic system. The system consists of a neutrally buoyant and neutrally charged particle in a chamber filled with a fluid flowing with low Reynolds number. At the bottom of this chamber is a series of parallel electrodes with a controlled voltage. The voltage on the electrodes creates a time-varying nonuniform electric field inducing...
In this paper, a novel class of robust state-space realizations, called normal realizations, is derived for reducing roundoff noise and self-sustained oscillations which ultimately can not be avoided in real-time applications. It is shown that these realizations are free of limit cycles. Another interesting property of the normal realizations is that they yield a minimal error propagation gain. This...
Living organisms learn by acting on their environment, observing the resulting reward stimulus, and adjusting their actions accordingly to improve the reward. This action-based or Reinforcement Learning can capture notions of optimal behavior occurring in natural systems. We describe mathematical formulations for Reinforcement Learning and a practical implementation method known as Adaptive Dynamic...
Complete coverage path planning is a key problem for autonomous mobile robot, which concerns both efficiency and completeness of coverage. This paper proposed a novel strategy of combined coverage path planning method, which combines the template-based and the heuristic coverage path planning. The template-based mode allows the robot to run under some predefined motion templates which can realize...
A novel method for planning point-to-point robot trajectories will be introduced in this paper. With the new method, the requirement of an optimal path and the need of a slim motion due to the lack of free space can be compromised. The generated slim motion is suitable for applications where human-robot cooperation takes place and the workspace is considered to be constrained. This new method is based...
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