Design of stable fuzzy controllers for an AGV

Fuzzy logic control is a relatively new technology and hence it needs rigorous comparative analyses with other well-established conventional control schemes. Further, fuzzy controller stability analysis is a major hindrance for its popularity among control engineers. This paper shows how stable fuzzy controllers may be synthesized for a typical AGV from the perspective of variable structure systems (VSS) theory. VSS or sliding model control (SMC) is an established robust non-linear control methodology. The AGV is characterized by highly non-linear, coupled and configuration dependent dynamics, with uncertainty in model parameters. Similarity in performance of the fuzzy controllers to the SMC controller is demonstrated through experimental results obtained for steer control of the AGV

Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Induction Machine Control

In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations.

Dilemma of mathematics

The pursuit of knowledge and the use of reason, based on sense and observation is a key ingredient for research. Mathematics is a creation of human mind concerned chiefly with ideas, processes and reasoning. In this paper, we will try to give a new comprehensive definition of mathematics to understand “what is mathematics”. We will discuss the controversial nature and position of mathematics and its scientific status. We will highlight the position of mathematics in different civilizations. We will highlight the mythical issues about Mathematics. We will also discuss the current state of mathematics i.e. mathematics in crises, especially pure mathematics and will put forward the remedial suggestions. We have gathered together some of these impressions; these are all tentative, nothing final about them, but these are here nonetheless

Active vibration control of smart composite plates using optimized self-tuning fuzzy logic controller with optimization of placement, sizing and orientation of PFRC actuators

This paper deals with optimization of the sizing, location and orientation of the piezo-fiber reinforced composite (PFRC) actuators and active vibration control of the smart composite plates using particle-swarm optimized self-tuning fuzzy logic controller. The optimization criteria for optimal sizing, location and orientation of the PFRC actuators is based on the Gramian controllability matrix and the optimization process is performed by involving the limitation of the plates masses increase. Optimal configurations of five PFRC actuators for active vibration control of the first six modes of cantilever symmetric ((90 degrees/0 degrees/90 degrees/0 degrees)s), antisymmetric cross-ply ((90 degrees/0 degrees/90 degrees/0 degrees/90 degrees/0 degrees/90 degrees/0 degrees)) and antisymmetric angle-ply ((45 degrees/-45 degrees/45 degrees/-45 degrees/45 degrees/-45 degrees/45 degrees/-45 degrees)) composite plates are found using the particle swarm optimization. The detailed analysis of influences of the PFRC layer orientation and position (top or bottom side of composite plates), as well as bending-extension coupling of antisymmetric laminates on controllabilities is also performed. The experimental study is performed in order to validate this behavior on controllabilities of antisymmetric laminates. The particle swarm-optimized self-tuning fuzzy logic controller (FLC) adapted for the multiple-input multiple-output (MIMO) control is implemented for active vibration suppression of the plates. The membership functions as well as output matrices are optimized using the particle swarm optimization. The Mamdani and the zero-order Takagi-Sugeno-Kang fuzzy inference methods are employed and their performances are examined and compared. In order to represent the efficiency of the proposed controller, results obtained using the proposed particle swarm optimized self-tuning FLC are compared with the corresponding results in the case of the linear quadratic regulator (LQR) optimal control strategy.This is the peer reviewed version of the article: Zorić, N.; Tomović, A.; Obradović, A.; Radulović, R.; Petrović, G. R. Active Vibration Control of Smart Composite Plates Using Optimized Self-Tuning Fuzzy Logic Controller with Optimization of Placement, Sizing and Orientation of PFRC Actuators. Journal of Sound and Vibration 2019, 456, 173–198. [https://doi.org/10.1016/j.jsv.2019.05.035

Non-Linear Robust Observers For Systems With Non-Collocated Sensors And Actuators

Challenges in controlling highly nonlinear systems are not limited to the development of sophisticated control algorithms that are tolerant to significant modeling imprecision and external disturbances. Additional challenges stem from the implementation of the control algorithm such as the availability of the state variables needed for the computation of the control signals, and the adverse effects induced by non-collocated sensors and actuators. The present work investigates the adverse effects of non-collocated sensors and actuators on the phase characteristics of flexible structures and the ensuing implications on the performance of structural controllers. Two closed-loop systems are considered and their phase angle contours have been generated as functions of the normalized sensor location and the excitation frequency. These contours were instrumental in the development of remedial actions for rendering structural controllers immune to the detrimental effects of non-collocated sensors and actuators. Moreover, the current work has focused on providing experimental validation for the robust performances of a self-tuning observer and a sliding mode observer. The observers are designed based on the variable structure systems theory and the self-tuning fuzzy logic scheme. Their robustness and self-tuning characteristics allow one to use an imprecise model of the system and eliminate the need for the extensive tuning associated with a fixed rule-based expert fuzzy inference system. The first phase of the experimental work was conducted in a controlled environment on a flexible spherical robotic manipulator whose natural frequencies are configuration-dependent. Both controllers have yielded accurate estimates of the required state variables in spite of significant modeling imprecision. The observers were also tested under a completely uncontrolled environment, which involves a 16-ft boat operating in open-water under different sea states. Such an experimental work necessitates the development of a supervisory control algorithm to perform PTP tasks, prescribed throttle arm and steering tasks, surge speed and heading tracking tasks, or recovery maneuvers. This system has been implemented herein to perform prescribed throttle arm and steering control tasks based on estimated rather than measured state variables. These experiments served to validate the observers in a completely uncontrolled environment and proved their viability as reliable techniques for providing accurate estimates for the required state variables

Control techniques for mechatronic assisted surgery

The treatment response for traumatic head injured patients can be improved by using an autonomous robotic system to perform basic, time-critical emergency neurosurgery, reducing costs and saving lives. In this thesis, a concept for a neurosurgical robotic system is proposed to perform three specific emergency neurosurgical procedures; they are the placement of an intracranial pressure monitor, external ventricular drainage, and the evacuation of chronic subdural haematoma. The control methods for this system are investigated following a curiosity led approach. Individual problems are interpreted in the widest sense and solutions posed that are general in nature. Three main contributions result from this approach: 1) a clinical evidence based review of surgical robotics and a methodology to assist in their evaluation, 2) a new controller for soft-grasping of objects, and 3) new propositions and theorems for chatter suppression sliding mode controllers. These contributions directly assist in the design of the control system of the neurosurgical robot and, more broadly, impact other areas outside the narrow con nes of the target application. A methodology for applied research in surgical robotics is proposed. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers. However, the lack of conformity to the criteria in the top tier, combined with the inability to conclusively prove increased clinical benefit, particularly symptomatic benefit, is shown to be hampering the potential of surgical robotics in gaining wide establishment. A control scheme for soft-grasping objects is presented. Grasping a soft or fragile object requires the use of minimum contact force to prevent damage or deformation. Without precise knowledge of object parameters, real-time feedback control must be used to regulate the contact force and prevent slip. Moreover, the controller must be designed to have good performance characteristics to rapidly modulate the fingertip contact force in response to a slip event. A fuzzy sliding mode controller combined with a disturbance observer is proposed for contact force control and slip prevention. The robustness of the controller is evaluated through both simulation and experiment. The control scheme was found to be effective and robust to parameter uncertainty. When tested on a real system, however, chattering phenomena, well known to sliding mode research, was induced by the unmodelled suboptimal components of the system (filtering, backlash, and time delays). This reduced the controller performance. The problem of chattering and potential solutions are explored. Real systems using sliding mode controllers, such as the control scheme for soft-grasping, have a tendency to chatter at high frequencies. This is caused by the sliding mode controller interacting with un-modelled parasitic dynamics at the actuator-input and sensor-output of the plant. As a result, new chatter-suppression sliding mode controllers have been developed, which introduce new parameters into the system. However, the effect any particular choice of parameters has on system performance is unclear, and this can make tuning the parameters to meet a set of performance criteria di cult. In this thesis, common chatter-suppression sliding mode control strategies are surveyed and simple design and estimation methods are proposed. The estimation methods predict convergence, chattering amplitude, settling time, and maximum output bounds (overshoot) using harmonic linearizations and invariant ellipsoid sets