This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergenc...

A novel adaptive control strategy is proposed herein to increase the efficiency of adaptive control by combining Takagi–Sugeno (T–S) fuzzy modeling and the Ge–Yao–Chen (GYC) partial region stability theory. This approach provides two major contributions: (1) increased synchronization efficiency, especially for parameters tracing and (2) a simpler controller design. Two simulated cases are prese...

In this paper, the convergence of parameter estimates and the interactions among the two adaptive fuzzy systems constituting an indirect adaptive fuzzy controller are studied, both analytically and by means of simulations with a second-order nonlinear system. The analytical results and the simulations, performed with various initial conditions and learning rates, highlight how the interactions ...

In this paper we design a fuzzy adaptive internal model control for the speed varying problem of a PMSM. The PMSM under the vector control model is studied. The designing of the fuzzy adaptive IMC involves three steps. First a standard internal model controller is designed. This model has high input saturation. A modified IMC is designed which reduces the input saturation. The variation of iner...

The decoupled control of torque and flux has made field-oriented control an attractive choice for high performance induction motor drives. However, changes in the speed tracking trajectory and external disturbances make it difficult to achieve an acceptable closed-loop tracking performance, especially when traditional linear controllers are used. This paper addresses this issue by applying dire...

An adaptive fuzzy control method is developed to control chaos in the permanent magnet synchronous motor drive system via backstepping. Fuzzy logic systems are used to approximate unknown nonlinearities, and an adaptive backstepping technique is employed to construct controllers. The proposed controller can suppress the chaos of PMSM and track the reference signal successfully. The simulation r...

The paper describes the development of an adaptive fuzzy control strategy for control of dissolved oxygen (DO) concentration on an activated sludge process (ASP). The technique is applied to the Benchmark Simulation Model n.1 (BSM1) which is a standard for performance assessment and evaluation of ASP control strategies. The controller uses DO concentration error feedback and manipulates the flo...

This paper shows implementation of indirect adaptive control law for nonlinear systems using TakagiSugeno fuzzy system. Takagi-Sugeno fuzzy system is used to identify nonlinear system components theta alpha and theta beta. Stable Indirect Adaptive control law is such that it has two control components one is certainty equivalence control and other is sliding mode control. Sliding mode controlle...

In this paper, an indirect adaptive fuzzy sliding mode control scheme is designed for hybrid electric bus. The trajectory tracking control for stopping the bus in a bus station is proposed. The control strategies of regenerative braking in the hybrid electric bus add the control difficulty of the longitudinal braking system. Its nonlinearities are estimated by adaptive fuzzy method and projecti...

The paper presents adaptation and optimization of the interaction structure of interactive systems by application of the control theory principles based on a fuzzy neural network. The interactive system is presented as a control system consisting of two parts: 1) plant of control or controlled plant (model of the real-life process) and 2) neurofuzzy-based feedback control algorithm. The last on...