This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program

Bats sonar algorithm (BSA) as a swarm intelligence approach utilises the concept of echolocation of bats to find prey. However, the algorithm is unable to achieve good precision and fast convergence rate to the optimum solution. With this in mind, an adaptive bats sonar algorithm is introduced with new paradigms of real bats echolocation behaviour. The performance of the algorithm is validated through rigorous tests with several single objective optimisation benchmark test functions. The obtained results show that the proposed scheme outperforms the BSA in terms of accuracy and convergence speed and can be efficiently employed to solve engineering problems.

<span>Underwater remotely operated vehicle (ROV) is important in underwater industries as well as for safety purposes. It can dive deeper than humans and can replace humans in a hazardous underwater environment. ROV depth control is difficult due to the hydrodynamic of the ROV itself and the underwater environment. Overshoot in the depth control may cause damage to the ROV and its investigated location. This paper presenting a new tuning approach of single input fuzzy logic controller (SIFLC) with gradient descent algorithm (GDA) and particle swarm optimization (PSO) implementation for ROV depth control. The ROV was modeled using system identification to simulate the depth system. Proportional integral derivative (PID) controller was applied to the model as a basic controller. SIFLC was then implemented in three tuning approaches which are heuristic, GDA, and PSO. The output transient was simulated using MATLAB Simulink and the percent overshoot (OS), time rise (Tr), and settling time (Ts) of the systems without and with controllers were compared and analyzed. The result shows that SIFLC GDA output has the best transient result at 0.1021% (OS), 0.7992s (Tr), and 0.9790s (Ts).</span>

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The significance of human motion intentions in a designed exoskeleton wrist control hand is essential for stroke survivors, thus making EMG signals an integral part of the overall system is critically important. However, EMG is a nonlinear signal that is easily influenced by several errors from its surroundings and certain of its applications require close monitoring to provide decent outcomes. Hence, this paper proposes to establish the relationship between EMG signals and wrist joint angle to estimate the desired wrist velocity. Fuzzy logic has been selected to form a dynamic modelling of wrist movement for a single muscle at different MVC levels and double muscles at a similar MVC level. The physical model of the exoskeleton hand using Simmechanics Matlab software has been developed to validate the performance of the fuzzy logic output result from both dynamic modelling approaches. A PID controller has been developed to smooth the exoskeleton hand movement fluctuations caused by the fuzzy logic decision-making process. As a conclusion, results showed a strong relationship between EMG signals and wrist joint angle improved the estimation results of desired wrist velocity for both dynamic modelling approaches hence strengthened the prediction process by providing a myoelectronic control device for the exoskeleton hand. ABSTRAK: Kepentingan dalam mengetahui kehendak gerakan pergelangan tangan manusia adalah penting untuk pesakit strok yang terselamat, justeru menjadikan isyarat EMG amat penting pada keseluruhan sistem. Walau bagaimanapun, EMG adalah isyarat tidak linear yang mudah dipengaruhi ralat sekitaran dan memerlukan pemantauan rapi bagi hasil yang baik. Oleh itu, kajian ini mencadangkan kewujudan hubungan antara isyarat EMG dan sudut sendi pergelangan tangan bagi menganggarkan halaju pergelangan tangan yang dikehendaki. Logik kabur (fuzzy logic) telah dipilih bagi membentuk model dinamik pergerakan pergelangan tangan pada otot tunggal di tahap MVC yang berbeza dan otot berganda pada tahap MVC yang serupa.  Model fizikal rangka luar tangan menggunakan perisian Matlab Simmekanik telah dibangunkan bagi mengesahkan prestasi Logik Kabur daripada kedua-dua pendekatan model dinamik. Pengawal PID telah dibangunkan bagi melicinkan gerakan turun naik tangan yang disebabkan proses membuat keputusan oleh Logik Kabur. Sebagai kesimpulan, dapatan kajian menunjukkan hubungan yang kukuh antara isyarat EMG dan sudut sendi pergelangan tangan. Ini meningkatkan anggaran dapatan halaju pergelangan tangan yang dikehendaki bagi kedua-dua pendekatan model dinamik seterusnya mengukuhkan proses ramalan melalui peranti kawalan mioelektronik rangka tangan.

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This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. One basic Ballistic Missile model [10] is used as an unstable model to formulate the control law algorithm using PFC. PFC algorithm development is computationally simple as a controller and it is not very complicated as the function of a missile will explode as it reaches the target. Furthermore, the analysis and issues of the implementation relating linear discrete-time unstable process are also being discussed. Hence, designed PFC algorithm need to find the suitable tuning parameters as its play an important part of the designing the autopilot controller. Thus, the tuning of the desired time constant, Ψ and small coincidence horizon n 1 in a single coincidence point shows that the PFC control law is built better in the dynamic pole of the unstable missile mode. As a result, by using a trajectory set-point, some positive results is presented and discussed as the missile follow its reference trajectory via some simulation using MATLAB 7.0.