Nonparametric approach for uncertainty-based multidisciplinary design optimization considering limited data

Uncertainty-based multidisciplinary design optimization (UMDO) has been widely acknowledged as an advanced methodology to address competing objectives and reliable constraints of complex systems by coupling relationship of disciplines involved in the system. UMDO process consists of three parts. Two parts are to define the system with uncertainty and to formulate the design optimization problem. The third part is to quantitatively analyze the uncertainty of the system output considering the uncertainty propagation in the multidiscipline analysis. One of the major issues in the UMDO research is that the uncertainty propagation makes uncertainty analysis difficult in the complex system. The conventional methods are based on the parametric approach could possibly cause the error when the parametric approach has ill-estimated distribution because data is often insufficient or limited. Therefore, it is required to develop a nonparametric approach to directly use data. In this work, the nonparametric approach for uncertainty-based multidisciplinary design optimization considering limited data is proposed. To handle limited data, three processes are also adopted. To verify the performance of the proposed method, mathematical and engineering examples are illustrated.     

Effective pedestrian detection using deformable part model based on human model

Recently, pedestrian detection systems have become an important technology in the development of the advanced driver assistance system (ADAS) for the autonomous car. The histogram of oriented gradients (HOG) is currently the most basic algorithm for detecting pedestrians, but it treats the entire body of the pedestrian as one single feature. In other words, if the entire body of the pedestrian is not visible, the detection rate under HOG decreases markedly. To solve this problem, we propose a detection system using a deformable part model (DPM) that divides the pedestrian data into two parts using a latent support vector machine (SVM)-based machine-learning technique. Experimental results show that our approach achieves better performance in a detection system than the existing method. In practice, there are many occlusions in the environment in front of the vehicle. For example, the surrounding transport facilities, such as a car or another obstacle, can occlude a pedestrian. These occlusions can increase the false detection rate and cause difficulties during the detection process. Our proposed method uses a different approach and can easily be applied in real-world scenarios, regardless of occlusions.

     

A disturbance observer based practical coordinated tracking controller for uncertain heterogeneous multi‐agent systems

This paper presents a coordinated tracking controller for multi‐agent systems. We assume that agents are uncertain, nonidentical, and affected by external disturbances. The information available to the tracking controller is a weighted sum of relative measurements. A coordinated tracking controller based on the disturbance observer, which is known as a robust output feedback controller, is designed so that the disturbances acting on agents are attenuated and at the same time the weighted sum of relative measurements approximately satisfies a differential equation defined by the leader's dynamics, which results in practical coordinated tracking. Systematic design procedures of the controller as well as numerical simulations are provided. Copyright © 2014 John Wiley & Sons, Ltd.     

Formation stabilization and resizing based on the control of inter‐agent distances

We propose a control strategy that could steer the group of mobile agents in the plane to achieve a specified formation. The control law could be implemented in a fully decentralized manner so that each agent moves on their own local reference frame. Under the acyclic minimally persistent graph topology, each agent measures the relative displacements of neighboring agents and then adjusts the distances between them to achieve the desired formation. As well as achieving a fixed formation, we could resize the formation only by changing the leader edge, which connects the leader with the first‐follower in acyclic minimally persistent graph, without changing the structures of the control law. Copyright © 2014 John Wiley & Sons, Ltd.     

Stochastic stability and stabilization of discrete‐time singular Markovian jump systems with partially unknown transition probabilities

This paper considers the stochastic stability and stabilization of discrete‐time singular Markovian jump systems with partially unknown transition probabilities. Firstly, a set of necessary and sufficient conditions for the stochastic stability is proposed in terms of LMIs, then a set of sufficient conditions is proposed for the design of a state feedback controller to guarantee that the corresponding closed‐loop systems are regular, causal, and stochastically stable by employing the LMI technique. Finally, some examples are provided to demonstrate the effectiveness of the proposed approaches. Copyright © 2014 John Wiley & Sons, Ltd.     

Some results on disturbance attenuation for Hamiltonian systems via direct discrete‐time design

The disturbance attenuation and robust disturbance attenuation problems for Hamiltonian systems in the discrete‐time setting are considered and some new results are presented. The new results are derived utilizing the recently presented dissipativity equality obtained by adding the dissipation rate function to the classical dissipativity inequality. A selection of the dissipation rate function yields new results. These results include a condition on the dissipation structure of the system to achieve the desired disturbance attenuation level and gives direct construction of optimal control laws for any desired disturbance attenuation level. The results remove the need to solve Hamilton–Jacobi–Isaacs inequalities. Copyright © 2014 John Wiley & Sons, Ltd.     

Observer based repetitive learning control for a class of nonlinear systems with non‐parametric uncertainties

In this paper, a repetitive learning control (RLC) scheme is developed for a class of nonlinear systems to handle an output tracking problem, where two state observers are introduced concurrently to estimate the unavailable control system and reference states information. The estimation of reference state information is because of the lack of reference internal model in the RLC design. By virtue of the periodicity of reference signals and the associated learning capability in control mechanism, the involved unstructured nonlinear uncertainties can be handled. The Lyapunov‐like energy function method is adopted to facilitate the learning control design as well as property analysis thus achieve the asymptotical convergence of errors in state observation and output tracking simultaneously. Moreover, owing to the robustification of the learning controller that is addressed by incorporating projection, the proposed control scheme would be applicable in practice. In the end, an illustrative example is simulated to demonstrate the efficacy of the proposed RLC law. Copyright © 2014 John Wiley & Sons, Ltd.     

A limit set stabilization by means of the Port Hamiltonian system approach

A solution to the stabilization problem of a compact set by means of the Interconnection and Damping Assignment Passivity‐Based Control methodology, for an affine nonlinear system, was introduced. To this end, we expressed the closed‐loop system as a Port Hamiltonian system, having the property of almost all their trajectories asymptotically converge to a convenient limit set, except for a set of measure zero. It was carried out by solving a partial differential equation (PDE) or single matching condition, which allows the desired energy level or limit set E to be shaped explicitly. The control strategy was tested using the magnetic beam balance system and the pendulum actuated by a direct current motor (DC‐motor), having obtained satisfactory results. Copyright © 2014 John Wiley & Sons, Ltd.     

Less conservative stability criteria for linear systems with interval time‐varying delays

The problem of the stability of a linear system with an interval time‐varying delay is investigated. A new Lyapunov–Krasovskii functional that fully uses information about the lower bound of the time‐varying delay is constructed to derive new stability criteria. It is proved that the proposed Lyapunov–Krasovskii functional can lead to less conservative results than some existing ones. Based on the proposed Lyapunov–Krasovskii functional, two stability conditions are developed using two different methods to estimate Lyapunov–Krasovskii functional's derivative. Two numerical examples are given to illustrate that the two stability conditions are complementary and yield a larger maximum upper bound of the time‐varying delay than some existing results. Copyright © 2013 John Wiley & Sons, Ltd.