Zool Ismail

By Vina Wahyuni Eka Putranti and Zool Hilmi Ismail

A robust tracking control for an Autonomous Underwater Vehicle (AUV) system operated in the extreme ocean environment activities is very much needed due to its external disturbances potentially disturb the stability of the system. This research proposes a new robust-region based controller which integrates Super Twisting Sliding Mode Control (STSMC) with region boundary approach in the presence of determined disturbances. STSMC is a second order SMC which combines between continuous signal and discontinuous signal to produce a robust system. By incorporating region based control into STSMC, the desired trajectory defined as a region produces an energy saving control compared to conventional point based control. Energy function of region error is applied on the AUV to maintain inside the desired region during tracking mission, thus, minimizing the energy usage. Analysis on a Lyapunov candidate proved that the proposed control achieved a global asymptotic stability and showed less chattering, providing 20s faster response time to handle perturbations, less transient of thrusters' propulsion and ability to save 50% of energy consumption compared to conventional SMC, Fuzzy SMC and STSMC. Overall, the newly developed controller contributed to a new robust, stable and energy saving controller for an AUV in the presence of external disturbances.

Part of the book: Recent Developments in Sliding Mode Control

By Zool Hilmi Ismail and Nohaidda Sariff

Research in the area of cooperative multi-agent robot systems has received wide attention among researchers in recent years. The main concern is to find the effective coordination among autonomous agents to perform the task in order to achieve a high quality of overall performance. Therefore, this paper reviewed various selected literatures primarily from recent conference proceedings and journals related to cooperation and coordination of multi-agent robot systems (MARS). The problems, issues, and directions of MARS research have been investigated in the literature reviews. Three main elements of MARS which are the type of agents, control architectures, and communications were discussed thoroughly in the beginning of this paper. A series of problems together with the issues were analyzed and reviewed, which included centralized and decentralized control, consensus, containment, formation, task allocation, intelligences, optimization and communications of multi-agent robots. Since the research in the field of multi-agent robot research is expanding, some issues and future challenges in MARS are recalled, discussed and clarified with future directions. Finally, the paper is concluded with some recommendations with respect to multi-agent systems.

Part of the book: Applications of Mobile Robots

By Nohaidda Sariff, Zool Hilmi Ismail, Ahmad Shah Hizam Md Yasir, Denesh Sooriamoorthy and Puteri Nor Aznie Fahsyar Syed Mahadzir

Finding consensus is one of the most important tasks in multi-agent robot motion coordination research, especially in a communication environment. This justification underlies the use of event-triggered controller in current multi-agent consensus research. However, the communication issue has not been adequately addressed in a broadcast communication environment for rendezvous applications. Therefore, the broadcast event-triggered (BET) controller with a new formulation was designed using the Simultaneous Perturbation Stochastic Algorithm (SPSA). Theorems and relevant proofs were presented. Agent performances with the BET controller were evaluated and compared with the conventional broadcast time-triggered (BTT) controller. The results showed an effective motion generated by a multi-agent robot to reach the rendezvous point based on the Bernoulli distribution and gradient approximation of the agent local controller. The BET controller has proven to work more efficiently than the BTT controller when it reaches convergence in less than 40.42% of time and 21.00% of iterations on average. The utilization of communication channels is slightly reduced for BET, which is 71.09% usage instead of fully utilized by BTT. The threshold value of the event-triggered function (ETF) and SPSA parameters affected agent performances. Future research may consider using an effective and efficient BET controller in a complex communication environment with many variations of graph topology networks.

Part of the book: Motion Planning for Dynamic Agents