مجله کنترل
سال هشتم شماره 3 (پاییز 1393)

Interval knowledge is introduced in this paper. Interval knowledge is new paradigm for representation of human’s partial-implicit knowledge which applies granular information-based computational methods، e. g.، fuzzy sets and rough sets. Interval-based intelligent systems and controllers are ones used interval knowledge and granular computing approaches. These systems and controllers are able to deal with types of vagueness and uncertainties. During past two decades، several researches have proved interval-based intelligent system are more capable than ones use traditional approaches in order to processes of data، especially in noisy situations. In this paper، rough sets theory، rough set neural networks، and theory of fuzzy type2 as most important interval knowledge approaches are presented، and also some their applications are summarized.

In this paper، after reviewing a history of early literature and enumerating the benefits of quadruped robots، the latest world-wide research works on these robots are discussed. Then، various gate mechanisms، path movement methods، and static and dynamic stability margins of these robots are investigated. The modeling and kinematic and dynamic analyses of a typical quadruped robot with twelve degrees of freedom are also provided. Finally، a general path planning algorithms of such robots and the methods of deriving their stability conditions are explained.

Model Predictive Controllers (MPC) are effective control strategies widely used in the industry. The desirable MPC performance requires appropriate tuning of the controller parameters. However، the MPC tuning parameters are related to the closed loop characteristics in a complex and nonlinear manner، so the tuning procedure is an intricate problem، which has received much attention in recent decades. In this paper، the effects of each tuning parameter on the closed loop behavior are studied. Then، the issue of MPC tuning problem is considered and a review of the available tuning methods are provided. Modern tuning strategies are also considered. The emphasis of this paper is on theoretical tuning strategies which lead to closed form tuning equations that can be used in closed loop analysis. Finally، a simulation study is employed to have a comparative study on some closed form tuning equations and the advantages and disadvantages of each method is clarified.

Cable-driven robots are a class of parallel robots in which the rigid links are replaced by cables. Using cables instead of rigid links in parallel robots makes them a suitable choice to remedy some of the traditional shortcoming of the conventional robots. However، this introduces new challenges in the study of cable-driven robots. This paper presents a survey of cable-driven robots and addresses numerous challenging open problems in this field. The paper consists of an overview of both applications and theoretical issues of cable-driven robots such as workspace، dynamics and control، and furthermore some open challenging issues in this field of research.

In this paper، a survey on applications of estimation theory، identification and stochastic control in industrial systems is presented. Identification، parameter and state estimation of a dynamical system and stochastic control are three important and applicable fields in industry. Several fields are discussed in this paper containing، leak detection in fluid pipelines، maneuvering target tracking، Active Queue Management (AQM) in communication networks، applications of stochastic modeling and control in medical and health issues، disease infection and control، dosage regimen design، and disease modeling and treatment. In addition، covariance assignment of dynamical systems’ states، quantum systems، localization، identification and stochastic control of robots، and also applications of estimation theory in navigation systems are reviewed. Furthermore، estimation، identification and stochastic control of electrical motors، and traffic control in Intelligent Transportation Systems (ITS) are investigated. Finally، chaotic systems control، synchronization، estimation، and identification are studied.