Mohammad Biglarbegian

On the Stability of Interval Type-2 TSK Fuzzy Logic Control Systems

Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainties. This paper proposes a novel inference mechanism for an interval type-2 Takagi-Sugeno-Kang fuzzy logic control system (IT2 TSK FLCS) when antecedents are type-2 fuzzy sets and consequents are crisp numbers (A2-C0). The proposed inference mechanism has a closed form which makes it more feasible to analyze the stability of this FLCS. This paper focuses on control applications for the following cases: 1) Both plant and controller use A2-C0 TSK models, and 2) the plant uses type-1 Takagi-Sugeno (TS) and the controller uses IT2 TS models. In both cases, sufficient stability conditions for the stability of the closed-loop system are derived. Furthermore, novel linear-matrix-inequality-based algorithms are developed for satisfying the stability conditions. Numerical analyses are included which validate the effectiveness of the new inference methods. Case studies reveal that an IT2 TS FLCS using the proposed inference engine clearly outperforms its type-1 TSK counterpart. Moreover, due to the simple nature of the proposed inference engine, it is easy to implement in real-time control systems. The methods presented in this paper lay the mathematical foundations for analyzing the stability and facilitating the design of stabilizing controllers of IT2 TSK FLCSs and IT2 TS FLCSs with significantly improved performance over type-1 approaches.

Design of Novel Interval Type-2 Fuzzy Controllers for Modular and Reconfigurable Robots: Theory and Experiments

Recently, there has been a growing interest in using modular and reconfigurable robots (MRRs) in flexible automation to reduce labor and increase throughput. Moreover, the significant facilitation of repair and maintenance of MRRs has attracted manufacturers to respond to the increasing desire for new products and methods of production in todays competitive market. As a result, design and control of such systems have become major topics for investigation in recent years. This paper presents a novel design methodology of interval type-2 Takagi-Sugeno-Kang fuzzy logic controllers (IT2 TSK FLCs) for MRR manipulators with uncertain dynamic parameters. We develop a mathematical framework for the design of IT2 TSK FLCs for tracking purposes that can be effectively used in real-time applications. To verify the effectiveness of the proposed controller, experiments are performed on an MRR with two degrees of freedom, which exhibits dynamic coupling behavior. Results show that the developed controller can outperform some well-known linear and nonlinear controllers for different configurations. Therefore, the proposed structure can be adopted for the position control of MRRs with unknown dynamic parameters in trajectory-tracking applications.

On the robustness of Type-1 and Interval Type-2 fuzzy logic systems in modeling

Research on the robustness of fuzzy logic systems (FLSs), an imperative factor in the design process, is very limited in the literature. Specifically, when a system is subjected to small deviations of the sampling points (operating points), it is of great interest to find the maximum tolerance of the system, which we refer to as the systems robustness. In this paper, we present a methodology for the robustness analysis of interval type-2 FLSs (IT2 FLSs) that also holds for T1 FLSs, hence, making it more general. A procedure for the design of robust IT2 FLSs with a guaranteed performance better than or equal to their T1 counterparts is then proposed. Several examples are performed to demonstrate the effectiveness of the proposed methodologies. It was concluded that both T1 and IT2 FLSs can be designed to achieve robust behavior in various applications, and preference one or the other, in general, is application-dependant. IT2 FLSs, having a more flexible structure than T1 FLSs, exhibited relatively small approximation errors in the several examples investigated. The methodologies presented in this paper lay the foundation for the design of FLSs with robust properties that will be very useful in many practical modeling and control applications.

A novel neuro-fuzzy controller to enhance the performance of vehicle semi-active suspension systems

This paper proposes a neuro-fuzzy (NF) strategy to implement semi-active suspension in passenger vehicles. The proposed method is composed of two parts: a NF controller (NFC), to establish an efficient controller strategy to improve ride comfort and road handling (RCH), and an inverse mapping to estimate the semi-active suspension current. To effectively estimate the current needed to control the semi-active damper, an inverse mapping based on neural network, modified back-propagation (MBP) is presented. The inverse mapping is incorporated into the FC to enhance RCH. Given the relative velocity between the mass and the base and also the absolute acceleration of the mass, the FC computes the optimum damping coefficient. The fuzzy logic rules are extracted based on expert knowledge encapsulated in skyhook and groundhook. A quarter-car model was adopted for the purpose of simulating and experimenting with the proposed NFC. To verify the performance of the FC, two sets of results are reported. First, an experimental analysis was performed to demonstrate the effectiveness of the FC in comparison with the benchmark skyhook and Rakheja–Sankar controllers. Furthermore, a random input was considered to examine the robustness of the NFC in comparison with the other adopted controllers. It was shown that the developed NFC control enhances the performance of the quarter-car system significantly, in terms of both ride comfort and handling characteristics. Second, four FCs with the same control strategies were implemented on a full-vehicle model to demonstrate the effectiveness of the proposed control strategy in reducing the propensity to rollover. It was concluded that the developed FC enhances the RHC and also has the potential to increase the stability of vehicles.

Intelligent Control of Vehicle Semi-Active Suspension Systems for improved Ride Comfort and Road Handling

In this paper we propose a neuro-fuzzy (NF) control strategy to enhance desired suspension performance. The proposed method consists of two parts: a fuzzy control strategy to establish an efficient controller to improve ride comfort and road handling (RCH) and an inverse mapping model to estimate the current needed for a semi-active damper. The fuzzy logic rules are extracted based on Skyhook and Groundhook. The inverse mapping model is based on an artificial neural network and incorporated into the fuzzy controller to enhance RCH. To validate the effectiveness of the proposed NF controller, a quarter car model is adopted and numerical analysis is presented. To verify the performance of the NF controller (NFC), comparisons with existing semiactive techniques are made and two sets of results are reported. First, a sinusoidal road input is considered and time domain results are presented. Second, for the same sinusoidal input, frequency response of the developed controllers is obtained. It is shown that the developed NFC enhances RCH considerably and outperforms other existing controllers in terms of both ride comfort and handling

A neural network based fuzzy control approach to improve ride comfort and road handling of heavy vehicles using semi-active dampers

The use of semi-active dampers in suspension systems is increasing rapidly in the automotive industry. This is attributed to the fact that damping can be adjusted to improve ride comfort and road handling. However, accomplishing ride comfort and better road handling concurrently is challenging. In this paper, we propose an intelligent system to optimise the suspension performance in terms of concurrently achieving the above-mentioned objectives. A neural network-based fuzzy logic controller is designed to control the system that embodies this damper. The proposed controller can enhance the vehicle handling and ride comfort concurrently while consuming less energy than existing control methodologies.

Review of Recent Type-2 Fuzzy Controller Applications

Type-2 fuzzy logic controllers (T2 FLC) can be viewed as an emerging class of intelligent controllers because of their abilities in handling uncertainties; in many cases, they have been shown to outperform their Type-1 counterparts. This paper presents a literature review on recent applications of T2 FLCs. To follow the developments in this field, we first review general T2 FLCs and the most well-known interval T2 FLS algorithms that have been used for control design. Certain applications of these controllers include robotic control, bandwidth control, industrial systems control, electrical control and aircraft control. The most promising applications are found in the robotics and automotive areas, where T2 FLCs have been demonstrated and proven to perform better than traditional controllers. With the development of enhanced algorithms, along with the advancement in both hardware and software, we shall witness increasing applications of these frontier controllers.

Tractor–semitrailer model for vehicles carrying liquids

This article presents a model for solving solid–fluid interactions in vehicles carrying liquids. A tractor–semitrailer model is developed by incorporating suspension systems and tire dynamics. Owing to the solid–fluid interaction, equations of motion for the vehicle system are coupled. To simplify the complicated solution procedure, the coupled equations are solved separately using two different codes. Each code is analyzed separately; but as the parameters of the two codes depend on each other, the codes must be connected at the end of each time step. To determine the dynamic behavior of the system, different braking moments are applied. As the braking moments increase, braking time decreases. However, it turns out that increasing the braking moment to more than a certain level produces no significant results. It is also shown that vehicles carrying fluids need a greater amount of braking moments in comparison to vehicles carrying solids during braking. In addition, as the level of the fluid inside the tanker increases, from one-third to two-third of the tanker’s volume, the sloshing forces applied to the tanker’s walls increase. It was also concluded that the strategy used in this article to solve for the solid–fluid interaction by incorporating vehicle dynamic effects represents an effective method for determining the dynamic behavior of vehicles carrying fluids in other critical maneuvers.

A practical approach for design of PD and PI like Interval Type-2 TSK fuzzy controllers

Interval type-2 fuzzy logic control systems (IT2 FLCSs) have the potential of handling uncertainties better than type-1 FLCSs. However, lack of systematic design methodology of IT2 FLCSs limits their utility. This paper presents systematic methods to design interval IT2 Takagi-Sugeno-Kang (TSK) FLCSs that are PD-type and PI-type fuzzy controllers to satisfy certain desired transient response. We adopt the MacVicar-Whelan rule-base system and present general schemes for the design of IT2 TSK FLCSs, that include the design of the TSK consequent parameters. To validate the performance of the proposed controllers, some nonlinear plants have been considered. Results show that the IT2 TSK FLCSs satisfy the desired performance measures in terms of a set point tracking. Moreover, they reveal remarkable improvements in comparison to their type-1 counterparts for the plants considered in this paper.

State of the Art Robotic Grippers and Applications

In this paper, we present a recent survey on robotic grippers. In many cases, modern grippers outperform their older counterparts which are now stronger, more repeatable, and faster. Technological advancements have also attributed to the development of gripping various objects. This includes soft fabrics, microelectromechanical systems, and synthetic sheets. In addition, newer materials are being used to improve functionality of grippers, which include piezoelectric, shape memory alloys, smart fluids, carbon fiber, and many more. This paper covers the very first robotic gripper to the newest developments in grasping methods. Unlike other survey papers, we focus on the applications of robotic grippers in industrial, medical, for fragile objects and soft fabrics grippers. We report on new advancements on grasping mechanisms and discuss their behavior for different purposes. Finally, we present the future trends of grippers in terms of flexibility and performance and their vital applications in emerging areas of robotic surgery, industrial assembly, space exploration, and micromanipulation. These advancements will provide a future outlook on the new trends in robotic grippers.