Control and Signal Processing

The importance of control and signal processing in modern world cannot be over emphasised. Control systems are seen at work in small and house hold appliances, large scale industrial plants, very sophisticated and complex autonomous aerospace systems and vehicles. Control system technology has thus driven the engineers to operate at peak of their performance without compromising system stability and integrity. The advent of high performance computers and microprocessors has opened up possibilities of design and realization of innovative and more effective control algorithms. It significantly increases capability and performance of control systems. Thus, low cost quality products can be designed and realized by alleviating the need for expensive instrumentation and costly components.

Signal processing techniques have numerous applications in various contemporary fields such as telecommunication, quantum computing, spectral imaging, video and image processing, sonars, biomedicine, computer vision and seismology. Innovative and powerful algorithms have been developed and implemented in real–time applications on configurable integrated circuits and high performance new generation computers.

The Control and Signal Processing track of IBCAST provides a platform for scientists, engineers and students from universities and industries around the world to present their reseach work and innovative ideas to strengthen relations between academia and the industry. Papers of interest include those that describe theory, analytical techniques and latest technological developments.

Topics to be covered in this track include, but not limited to:

Control

• Nonlinear Systems and Control
• Adaptive and Robust Control
• Optimal and Model Predictive Control
• Safety Critical Resilient Control Systems
• Control of Hybrid and Discrete Time Systems
• Modeling and Simulation
• System Identification and Parameter Estimation
• Explainable AI for Fault-tolerant Control
• Perception, Guidance, Navigation and Control
• AI Based Model Predictive Control
• Deep Reinforcement Learning for Adaptive Control
• Swarm Optimization Algorithms
• Control of Renewable Power Generation Systems and Smart Grids
• Quantum Systems and Control

Signal Processing

• Computer Vision and Graphics
• Statistical Methods and Learning Algorithms
• Remote Sensing
• Big Data and Image/Audio/Text/Analytics
• Pattern Recognition, Bagging & Boosting Classifiers
• Image Recognition and Tracking
• Adversarial Attack Mitigation
• Single Shot Learning
• Medical Imaging Applications for Diagnostics and Pathology
• Multidimensional Signal Processing and Speech Recognition
• Sensor Networks
• Hyperspectral and Multispectral Imaging
• 3D Point Cloud Sensing & Processing
• Video Processing and Compression
• Algorithmic Implementations on FPGA/ ASIC/ Embedded Systems
• DSP related RTOS Issues
• Quantum Signal Processing