This paper introduces an optimal fuzzy proportional-integral-derivative (PID) controller. The fuzzy PID controller is a discrete-time version of the conventional PID controller, which preserves the same linear structure of the proportional, integral, and derivative parts but has constant coefficient yet self-tuned control gains. Fuzzy logic is employed only for the design; the resulting controller does not need to execute any fuzzy rule base, and is actually a conventional PID controller with analytical formulae. The main improvement is in endowing the classical controller with a certain adaptive control capability. The constant PID control gains are optimized by using the multiobjective genetic algorithm (MOGA), thereby yielding an optimal fuzzy PID controller. Computer simulations are shown to demonstrate its improvement over the fuzzy PID controller without MOGA optimization.

An optimal fuzzy PID controller

This paper describes the design principle, tracking performance, and stability analysis of a fuzzy proportional-derivative (PD) controller. First, the fuzzy PD controller is derived from the conventional continuous-time linear PD controller. Then, the fuzzification, control-rule base, and defuzzification in the design of the fuzzy PD controller are discussed in detail. The resulting controller is a discrete-time fuzzy version of the conventional PD controller, which has the same linear structure in the proportional and the derivative parts but has nonconstant gains: both the proportional and derivative gains are nonlinear functions of the input signals. The new fuzzy PD controller thus preserves the simple linear structure of the conventional PD controller yet enhances its self-tuning control capability. Computer simulation results have demonstrated this advantage of the fuzzy PD controller, particularly when the process to be controlled is nonlinear. After a detailed stability analysis, where a simple and realistic sufficient condition for the bounded-input/bounded-output stability of the overall feedback control system was derived, several computer simulation results are compared with the conventional PD controller. Although the conventional and fuzzy PD controllers are not exactly comparable, the authors compare them in order to have a sense of how well the fuzzy PD controller performs. For this reason, in the simulations several first-order and second-order linear systems, with or without time-delays, are first used to test the performance of the fuzzy PD controller for step reference inputs: the fuzzy PD control systems show remarkable performance, as well as (if not better than) the conventional PD control systems. Moreover, the fuzzy PD controller is compared to the conventional PD controller for a particular second-order linear system, showing the advantage of the fuzzy PD controller over the conventional one in the sense that in order to obtain the same control performance the conventional PD controller has to employ an extremely large gain while the fuzzy controller uses a reasonably small gain. Finally, in the case of nonlinear systems, the authors provide some examples to show that the fuzzy PD controller can track the set-points satisfactorily but the conventional PD controller cannot. >

New design and stability analysis of fuzzy proportional-derivative control systems

A two-link robotic manipulator is a Multi-Input Multi-Output (MIMO), highly nonlinear and coupled system. Therefore, designing an efficient controller for this system is a challenging task for the control engineers. In this paper, the Fractional Order Fuzzy Proportional-Integral-Derivative (FOFPID) controller for a two-link planar rigid robotic manipulator for trajectory tracking problem is investigated. Robustness testing of FOFPID controller for model uncertainties, disturbance rejection and noise suppression is also investigated. To study the effectiveness of FOFPID controller, its performance is compared with other three controllers namely Fuzzy PID (FPID), Fractional Order PID (FOPID) and conventional PID. For tuning of parameters of all the controllers, Cuckoo Search Algorithm (CSA) optimization technique was used. Two performance indices namely Integral of Absolute Error (IAE) and Integral of Absolute Change in Controller Output (IACCO) having equal weightage for both the links are considered for minimization. Numerical simulation results clearly indicate the superiority of FOFPID controller over the other controllers for trajectory tracking, model uncertainties, disturbance rejection and noise suppression.

Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator

Payment card transactions at a point of sale (POS) are secured in certain embodiments by intercepting, with a POS security layer installed on a POS terminal, payment data from the POS terminal, transmitting the payment data from the POS security layer to a server security application installed on a POS server, and providing false payment data from the POS security layer to a POS terminal application installed on the POS terminal. The false payment data in various embodiments is processed as if it were the payment data, such that the POS terminal transmits an authorization request to the POS server using the false payment data. In addition, the authorization request may be transmitted from the POS server to a payment gateway.

Secure payment card transactions

Before delivery, a manufacturer records module information identifying hardware modules, and corresponding software modules, installed in a vehicle. The module information includes a part number and a unique identifier for each hardware module, and name and version identifier of software loaded for each hardware module. The manufacturer, or a telematics operator, may broadcast files with upgraded software to vehicles over a wireless network. Or, upgraded software may be delivered to a vehicle via a connection between the vehicle and a computer, or a wired network. A vehicle's computer system authenticates a software file before upgrading from it by performing steps of an authentication sequence as a server in a client-server relationship with a computer device that broadcasted the file to the vehicle. A telematics system onboard the vehicle may collect and store vehicle usage information for use in determining when to upgrade from the authenticated software file.

Methods and systems for software upgrades

A modified fuzzy PI controller for a flexible-joint robot arm with uncertainties

In some embodiments, fast and secure communication can be achieved (e.g., in a fueling environment payment system) with systems and methods that validate an authentication request based on one or more pre-validated cryptographic keys.

Systems and methods for secure communication

A method and system for secure communication and control in a fueling environment. In one aspect, the fueling environment with secure communication comprises a fuel dispenser and at least one node communicable coupled with the fuel dispenser. The fuel dispenser is operable to generate a first public key and a first private key associated with the fuel dispenser and publish the first public key within the fueling environment. The fuel dispenser is further operable to authenticate a particular one of the nodes using, at least in part, a second public key associated with the particular node and the first public and the first private keys. The fuel dispenser may then dynamically generate a run-time symmetric key using, at least in part, the first private key and the second public key and communicate data associated with the fueling environment to the authenticated node, with the data encrypted using the symmetric key.

Secure communications and control in a fueling environment

A multimode system for receiving data in a retail environment includes: a secure input module for receiving high security input and low security input from a customer, the high security input to be communicated by the secure input module in cipher text, and the low security input to be communicated by the secure input module in plaintext. The multimode system is adapted to operate in a high security mode and a low security mode. The multimode system is adapted to enter the low security mode upon detection by the multimode system of a security breach condition. In the high security mode, the secure input module accepts low security input and high security input. In the low security mode, the secure input module accepts the low security input and does not accept the high security input.

Multimode retail system

This disclosure provides various embodiments of systems and methods for secure communications. In one aspect, the system includes a secure payment module (SPM) (120) in a fuel dispenser (105) and a point-of-sale (POS) system (165). The POS system (165) stores a public key certificate (180) uniquely identifying the SPM (120) and is configured to dynamically generate a first session key. The POS system (165) encrypts the first session key with a public key associated with the public key certificate (180), and transmits the encrypted first session key to the SPM (120). The SPM (120), which stores a private key associated with the public key certificate, is configured to receive and decrypt the first session key. The SPM (120) is further configured to receive a set of magnetic card data from a card reader (110), encrypt the set of magnetic card data with the first session key, and transmit the encrypted set of magnetic card data to the POS system (165).

Weiming Tang

Papers

A modified fuzzy PI controller for a flexible-joint robot arm with uncertainties

Systems and methods for secure communication

Secure communications and control in a fueling environment

Multimode retail system

System and method for secure communication in a retail environment