In this paper, a new technique called robust loop shaping–fuzzy gain scheduled control (RLS–FGS) is proposed to design an effective nonlinear controller for a long stroke pneumatic servo system. In our technique, a nonlinear dynamic model of a long stroke pneumatic servo plant is identified by the fuzzy identification method and is used as the plant for our design. The structure of local contro...

FES control is difficult for musculoskeletal system’s time-variability and dynamic nonlinearity. It often needs good performance control models and complex control methods to get better tracking precision, also the high performance control model is hard to build. Neural network (NN) can learn complex nonlinear mappings so it can be used to identify control model on-line. At the mean while, PID ...

In this paper, a novel robust adaptive sliding-mode control scheme is presented high precision position control for a permanent magnet synchronous linear motor (PMSLM) servo system under the influence of unknown parameters, nonlinear friction, cogging forces, and external distance. The proposed strategy effectively combines the design techniques of adaptive control and sliding-mode control. In ...

In this paper, a method is introduced for finding gains for all proportional integral derivation (PID) controllers that satisfy a robust performance constraint for a given transfer function of any order with time-delay by using the frequency response. The H-infinity index of additive weight uncertainty on the basis of robust stability condition of closed loop system is first get by small gain t...

In this paper the control of flexible joint manipulators is studied in detail. The model of N -axis flexible joint manipulators is derived and reformulated in the form of singular perturbation theory and an integral manifold is used to separate fast dynamics from slow dynamics. A composite control algorithm is proposed for the flexible joint robots, which consists of two main parts. Fast contro...

An MIMO auto-tuning method is develop that can be used by a layman of control. The method is based on MIMO identification and robust control design. The identification part delivers process model and model error bounds. The controller design block performs control synthesis, simulation and robust analysis. All steps can be done automatically. The parameters the user needs to enter are minimal a...

This paper deals with the design of a novel fuzzy proportional–integral–derivative (PID) controller for automatic generation control (AGC) of a two unequal area interconnected thermal system. For the first time teaching–learning based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed fuzzy-PID controller. The design problem is formulated as an optimi...

The position control of a standard robotic arm under faults has been studied and the performance is compared using a combination of several control approaches. The manipulator of a robot is exposed to possible faults and combinations of control techniques are employed. Here, several control combinations of PID along with optimal and robust techniques such as LQR, H2, H∞ and H∞-static output fee...

It is commonly believed that for SISO systems, well tuned PID controllers work as well as model-based controllers and that PID controllers are more robust to model errors. In this paper we present a novel offset-free constrained LQ controller for SISO systems, which is implemented in an efficient way so that the total controller execution time is similar to that of a PID. The proposed controlle...

Abstract. This paper presents the design steps and carries a comparative study between three Linear Matrix Inequality (LMI)-based iterative multivariable Proportional-Integral-Derivative (PID) controllers; PID design using H∞-norm, named Hi, PID design using H2-norm, named H2, of the system transfer function, PID design with Maximum Output Control (MOC), named Max, and the classical LMI-based r...