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The Incremental Rotary Encoder have been widely used to measure the angular speed of electrical drive such as Permanent Magnet Direct Current Motor (PMDCM). Nevertheless, speed measurement of PMDCM from the encoder signals can be subject to errors in some special condition such as in low resolution encoder. There are two main methods to measure the angular speed of PMDCM through encoder signal such as frequency-based and period-based wich has its own properties. Hence in this reseach aimed to improve the angular speed measurement with hybridization of frequency and period-based measurement. The Hybrid method is defined as paralleling the period and frequency then estimated the angular speed using sensor fusion with Kalman Filter. The experiment is doing by comparing of all method to get the best way in measuring. From the experimental showed that the Kalman filter parameter was fine tuned that resulting the sensor fusion or the mixed measurement between the frequency-based and the period based measure the angular speed accurately.

Particle swarm optimization (PSO) is an optimization algorithm that is simple and reliable to complete optimization. The balance between exploration and exploitation of PSO searching characteristics is maintained by inertia weight. Since this parameter has been introduced, there have been several different strategies to determine the inertia weight during a train of the run. This paper describes the method of adjusting the inertia weights using fuzzy signatures called signature PSO. Some parameters were used as a fuzzy signature variable to represent the particle situation in a run. The implementation to solve the tuning problem of linear quadratic regulator (LQR) control parameters is also presented in this paper. Another weight adjustment strategy is also used as a comparison in performance evaluation using an integral time absolute error (ITAE). Experimental results show that signature PSO was able to give a good approximation to the optimum control parameters of LQR in this case.

This paper presents a kinematic control algorithm development for a four-omni-wheeled robot such that the robot pose’s error decreases exponentially. A PID control scheme was used to regulate the angular speed of DC motors. Simulation experiments have been carried out to verify the mobile robot motion and the proposed control performances. This simulation would give a good initial robot and control design before realizing a real time robot controller. The results obtained through the simulation program elucidate that the robot is able to reach the specified static target and direction towards the robot in less than 6 seconds with the value of every RMSE below 0.01. These results also reveal that the proposed PID control can be utilized to make the robot moves smoothly as planned. The graphical form is employed to present the results of response, trajectory, and the changes in error values.

In this paper, we start to investigate missing measurement problem in a Quarter car model with Active Fault Tolerant Control (AFTC). AFTC is used to allow the parameters of the controller to be reconfigured in accordance error information obtained online to improve the stability and overall performance of the system when an error occurs. The design is divided into two parts. The first part is designed H-Infinity observer-based Fault Detection Filter (FDF) to generate a residual signal to estimate fault. FDF is designed to minimize the disturbance effect and maximize sensitivity fault. The second is a design fault tolerant control and Fault Compensation to guarantee the stability and performance system from disturbance by ignoring faults. And the function of fault compensation is to minimize effect fault of the system. The main contribution of this research is AFTC proved to solve the missing measurement problem in a Quarter car model. The simulation showed the effectiveness of this method for missing measurement problem which can reduce peak effect until 50% and 2 s faster in steady condition.

This paper investigates of a Robust H-Inflnity Active Fault Tolerant Control for Incomplete Information problem. Incomplete information includes of the Randomly Occurred Sensor Saturation (ROSS) and missing measurement. In this paper, we use active fault tolerant control to reconfiguration the controller on-line in real time. The main contribution of this paper is to show that Incomplete Information problem can be solved using Robust H-Infinity Active Fault Tolerant Control (AFTC) with Linear Matrix Inequality approach. A full car model is given to illustrate the effectiveness of the proposed result. The simulation shows the effectiveness of this method for incomplete information problem.

Sistem double inverted pendulum digunakan untuk mengkaji metodekontrol dari sistem nonlinear yang kompleks. Pada sistem tersebutditemukan tiga permasalahan, yaitu swing-up, stabilisasi, dan tracking.Pada penelitian ini digunakan metode LQR-Bat Algorithm untukmengoptimasi kestabilan pada sebuah double inverted pendulum. Hasilpenelitian menunjukkan penggunaan Bat Algorithm pada metode LQRdapat menyelesaikan permasalahan stabilisasi. Pada iterasi ke 300-400terjadi pengurangan nilai fitness yang menghasilkan fungsi SSE bernilaisemakin kecil.