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This paper shows how a self-tuning PID controller to control the temperature for the continuously stirred tank reactor (CSTR) and behaviour in a desired manner. The steps are modelling, simulation and analysis of difference of controller parameter in order to identify the ideal of the controller parameters. In addition, this project will on basis of a practical example tries to use a modelling of CSTR for control input and the temperature output will have a feedback loop to pass though the PID controller, and the PID controller will auto adjust the heating temperature. All the process will be built in Simulink.

In this paper, an adaptive sliding mode control is proposed for position tracking of rigid robotic manipulators with system parametric uncertainties. This control scheme can drive the position tracking error reach the designed sliding mode and then converge to zero asymptotically while avoiding the chattering phenomenon. Compared with the robust full-order sliding mode control technique, the proposed scheme can overcome the system uncertainties without requiring prior knowledge of their bounds. Theoretical analysis and simulation results validate the effectiveness of the proposed scheme.

In this study, a basic idea of U-state feedback control system design method is proposed based on U-model principle. Compared with U-model based nonlinear polynomial systems, the U-state space design is to determine the desired state variable equation x d (t), therefore to find the controller output u(t−1). The desired state equation can be designed/specified and transformed into the U-state space expression easily. The controller output can be obtained from resolving the equation. The desired state variables are updated by the corresponding state variables x(t). Assume that the state variables are measurable or obtained by a proper observer in this study. In case studies, two nonlinear discrete time state space models are selected to test the proposed approach. Computational experiments, that is, simulation studies, are used to demonstrate the procedure effectiveness.

This paper adopts a Hidden Markov Model as a basis for predicting the probabilities in location of soccer robot's trajectories, develops the corresponding algorithms, and then demonstrates the simplicity of the procedure with simulations. The purpose of the initial presentation is to establish a proper platform for the future comprehensive studies of using Hidden Markov Models to assemble critical observations with uncertainties or random measurement errors in stochastic system modelling and control.

The proposed paper looks into the modelling and control of a depyrogenation tunnel. Depyrogenation tunnels are used in pharmaceutical filling lines for removing pyrogens attached to containers (sterilization of glass containers), as well as, for drying purposes. Due to the nonlinear, multi inputs multi outputs nature of the system, a multiple inputs, multiple outputs (MIMO) state-space based modelling and control has been adopted. In this initial research stage and in order to validate both the model and the control scheme, computational experiments based on simulation have been carried out. This will ultimately help setup a proper platform for further developments. The initial results, as shown across the paper, are very promising.

In the first stage studies, this paper proposes a new piecewise linear discrete time dynamic model for describing global urine flow rate profiles against time sequence. The establishment of model has been guided by physician meaningful principles and measured data. To obtain the model parameters from measured data sequence, a number of existing approaches have been tailored/integrated including least squares algorithm for model time constant and gain estimation, Butterworth filter with specified cut off frequencies, for reducing noise effect induced by abdominal and bladder squeezing, then to facilitate counting the number of peaks. A few of real case studies are selected to demonstrate the effectiveness and efficiency of the proposed procedure.

This book describes the advances and applications in Sliding mode control (SMC) which is widely used as a powerful method to tackle uncertain nonlinear systems. The book is organized into 21 chapters which have been organised by the editors to reflect the various themes of sliding mode control. The book provides the reader with a broad range of material from first principles up to the current state of the art in the area of SMC and observation presented in a clear, matter-of-fact style. As such it is appropriate for graduate students with a basic knowledge of classical control theory and some knowledge of state-space methods and nonlinear systems. The resulting design procedures are emphasized using Matlab/Simulink software. .

The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, researchers and practitioners in the area of soft computing, systems modeling and control.