Search results for " fuzzy control"
showing 10 items of 13 documents
Finite-time stability and stabilisation for a class of nonlinear systems with time-varying delay
2014
This paper is concerned with the problems of finite-time stability FTS and finite-time stabilisation for a class of nonlinear systems with time-varying delay, which can be represented by Takagi–Sugeno fuzzy system. Some new delay-dependent FTS conditions are provided and applied to the design problem of finite-time fuzzy controllers. First, based on an integral inequality and a fuzzy Lyapunov–Krasovskii functional, a delay-dependent FTS criterion is proposed for open-loop fuzzy system by introducing some free fuzzy weighting matrices, which are less conservative than other existing ones. Then, the parallel distributed compensation controller is designed to ensure FTS of the time-delay fuzzy…
Intelligent Adaptive Motion Control for Ground Wheeled Vehicles
2014
In this paper a new intelligent adaptive control is applied to solve a problem of motion control of ground vehicles with two independent wheels actuated by a differential drive. The major objective of this work is to obtain a motion control system by using a new fuzzy inference mechanism where the Lyapunov’s stability can be assured. In particular the parameters of the kinematical control law are obtained using an intelligent Fuzzy mechanism, where the properties of the Fuzzy maps have been established to have the stability above. Due to the nonlinear map of the intelligent fuzzy inference mechanism (i.e. fuzzy rules and value of the rule), the parameters above are not constant, but, time a…
Type-2 Fuzzy Control of a Bioreactor
2009
Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a…
Method for designing PI-type fuzzy controllers for induction motor drives
2001
The paper illustrates a new systematic method for designing PI-type fuzzy controllers for direct field-oriented controlled induction motor drives. First, linear and decoupled models expressing the dynamics of speed, rotor flux, direct and inquadrature stator currents are derived using a nonlinear static compensator and choosing convenient input variables. Then, to guide the dynamics of the above quantities, four conventional PI controllers are designed independently, choosing their bandwidths conveniently. Finally, the input and output scale factors of PI-type fuzzy controllers are derived from the conventional PI controller parameters. The whole drive controller also includes a rotor flux …
Non linear control of glycaemia in type 1 diabetic patients
2011
A fuzzy controller for the closed loop control, by insulin infusion of glycaemia in type 1 diabetic patients is proposed. The controller uses type-2 fuzzy sets. The controller was tested in simulation using a complex nonlinear model of the glucose metabolism. Simulation results confirm the effectiveness and the robustness of the type-2 fuzzy logic controller. The design of the controller uses an optimization method based on genetic algorithms. This makes the type-2 fuzzy controller more efficient and faster than a fuzzy controller with type-1 fuzzy sets, allowing a more accurate control of the glucose in the blood.
Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort
2008
This paper considers motion control for a cooperative system of automated passenger vehicles. It develops a cooperative scheme based on a decentralized planning algorithm which considers the vehicles in an initial open chain configuration. In this scheme the trajectories are intersections-free, and each trajectory is planned independently of the others. To ensure the stabilization of each vehicle in the planned trajectory, a fuzzy closed loop motion control is presented, where, based on the properties of the Fuzzy maps, the Lyapunov’s stability of the motion errors is demonstrated for all the vehicles. Based on the ISO 2631-1 standard, the saturation property of the Fuzzy maps guarantees lo…
Trajectory Decentralized Fuzzy Control of Multiple UAVs.
2008
This paper considers a complete position and heading rate control system for multiple unmanned aerial vehicles (UAVs) with constant altitude. A decentralized trajectory planning algorithm is proposed, where the UAVs will avoid collisions while moving. In order to stabilize the UAVs in the reference planned trajectories and ensure the boundedness of the control velocities, a fuzzy control law is proposed with Lyapunov's stability proof. Simulation experiments developed in Matlab environment confirm the effectiveness and the robustness of the proposed control algorithm with respect to possible turbulence disturbances perturbing the nominal motion of the UAVs.
Relaxed Stability and Performance LMI Conditions for Takagi-Sugeno Fuzzy Systems With Polynomial Constraints on Membership Function Shapes
2008
Most linear matrix inequality (LMI) fuzzy control results in literature are valid for any membership function, i.e., independent of the actual membership shape. Hence, they are conservative (with respect to other nonlinear control approaches) when specific knowledge of the shapes is available. This paper presents relaxed LMI conditions for fuzzy control that incorporate such shape information in the form of polynomial constraints, generalizing previous works by the authors. Interesting particular cases are overlap (product) bounds and ellipsoidal regions. Numerical examples illustrate the achieved improvements, as well as the possibilities of solving some multiobjective problems. The result…
Fuzzy Control Strategy for Cooperative Non-holonomic Motion of Cybercars with Passengers Vibration Analysis
2021
The cybercars are electric road wheeled non-holonomic vehicles with fully automated driving capabilities. They contribute to sustainable mobility and are employed as passenger vehicles. Non-holonomic mechanics describes the motion of the cybercar constrained by non-integrable constraints, i.e. constraints on the system velocities that do not arise from constraints on the configuration alone. First of all there are thus with dynamic nonholonomic constraints, i.e. constraints preserved by the basic Euler-Lagrange equations (Bloch, 2000; Melluso, 2007; Raimondi & Melluso, 2006-a). Of course, these constraints are not externally imposed on the system but rather are consequences of the equations…
Predictive Intelligent Fuzzy Control for Cooperative Motion of Two Nonholonomic Wheeled Cars
2007
In this paper a problem of intelligent cooperative motion control of two wheeled nonholonomic cars (target and follower) is considered. Once a target car converges to a fixed state (position and orientation), a follower car coming from different position and orientation, converges to the state above, without excessive delay between the known arrival time of the target car and the arrival time of the follower. In this sense we present a new predictive fuzzy control system. A Kalman's filter and an odometric model are used to predict the future position and orientation of the target car. The prediction above is employed to plane a circular nonholonomic reference motion for the follower car. A…