A. UNDERGRADUATE COURSES
1. ELECTRICAL TECHNOLOGY AND ELECTRIC MACHINES (5 th Semester)
Course Syllabus : Introduction. Fundamental definitions and basic electromagnetic theory. D.C. Circuits. Basic elements of electric circuits. Fundamental laws and theorems of electric circuits. Methods of analysis of electric circuits. D.C. circuits transients. Single-phase A.C. circuits. Generation of single phase A.C. voltage. Average (mean) and RMS (effective) values of voltage and current. Phasors. Complex functions and representation of sinusoidal phenomena. Reactance & impedance. Steady state analysis of series R-L-C circuits. A.C. power. Power factor; A.C. power as a complex quantity. Assessment of power factor. Admittance & susceptance in parallel circuits. Analysis of complex A.C. circuits. Resonance in series and parallel circuits. Three phase A.C. circuits. Generation of 3-phase balanced sinusoidal voltage. Star & Delta Connections. Line & Phase quantities. Solution of 3-phase star/delta circuits with balanced supply voltage and balanced load. Phasor diagrams in 3-phase circuits. 3-phase, 4-wire circuits. 3-phase circuits with unbalanced loads; Three phase power; Measurement of three phase power by Aron's method; Determination of load power factor from wattmeter readings; Assessment of power factor in 3-phase circuits. Magnetic circuits. Ampere circuital law. Similarities of magnetic and electric circuits. Solution of series, parallel & series-parallel magnetic circuits. Iron, hysteresis & eddy current losses; Energy stored in a magnetic field and force of attraction between pole faces. Transformers. Constructional features and principle of operation. The ideal transformer under no load & loaded conditions; its equivalent circuit. Practical transformer rating & its equivalent circuit. Various types of three phase connections of transformers. Autotransformer and its comparison with a two winding transformer). Rotating Machines. General constructional features. Conditions for production of steady electromagnetic torque. Multi polar machines. Mechanical & electrical angle and their relation. D.C. Machines. Constructional features. EMF & torque expressions. Classification of D.C. generators. Characteristics of shunt, separately and compound generator. Classification of D.C. motors. Characteristics of shunt & series motors. Starting of D.C. shunt motor. Speed control of shunt and series motors. A.C.Machines. Synchronous generators. Generators in parallel operation. Synchronous motors. Asynchronous generators and asynchronous motors. 3-phase wound-rotor motors. 3-phase squirrel cage motors. Single-phase motors. Step motors. Operation characteristics and regulation of motors.
2. PUMPS AND ELECTRICAL MOTORS (5 th Semester)
Course Syllabus : Pumps and pumping systems. General hydrodynamic principles, hydraulic energy equation, problem solution calculations. Pump categories . Positive displacement pumps, functional characteristics- Applications. Centrifugal pumps. Pump types, turbine pumps. Pump tests, pump selection. Pumping systems design and techno-economic computations. Applications. Introduction to electromagnetism. Introduction to electrical technology. Direct and alternating current. Phasor diagrams. Composite loads and computations. Power measurements. Power factor correction. Classification of motors. Direct Current motors. Alternating Current Motors. Single-phase motors. Three-phase motors. Synchronous motors. Asynchronous motors. 3-phase wound-rotor motors. 3-phase squirrel cage motors. Motor starting, Y-delta starters. Applications in Agriculture.
3. MEASUREMENT AND SENSORS (7 th Semester)
Course Syllabus : Introduction. Basic principles of metrology. Sensors and transducers. Measurement devices. Static and dynamic characteristics of measuring instruments and systems. Measuring errors. Accuracy and Precision of measurements. Noise and reference grounding. Filters. Calibration of measuring instruments. Passive and active sensors. Balance methods of measurement. D.C. and A.C. bridges. Measurement of electric variables. Multi-meters. Sensors and instruments for measuring temperature and other related quantities. Sensors for humidity and moisture measurements. Measuring moisture contents in soil, substrates, fruits and other bio-materials. Length measurement. Extensometers and LVDT. Measurement of force and other related quantities. Measurement of pressure. Velocity measurement. Doppler-effect measuring devices. Radars. Supersonic sensors. Anemometers. Flow-meters. Tachometers. Acceleration measurement. Accelerometers. Bimorphs. Energy absorption materials. Measurement of visual variables. Photometry. Colorimetry. Advanced visual methods of measurement. Remote sensing. Measurement of chemical quantities and ISFETs. Measurement of pH, electrical conductivity and chemical composition. Digital converters. Computer-based measuring systems. Sensor networks. Data acquisition and data processing systems. Data display.
4. AUTOMATIC PROCESS CONTROL (8 th Semester)
Course Syllabus : Fundamental concepts. Signals and systems. Purpose and benefits of automatic process control. Review of basic mathematical tools. Principles of mathematical modelling. Macroscopic patterns of processes. Dynamic behaviour of typical processes. Processes with dead time. Empirical model identification. System errors. Feedback control. The feedback loop. The three-term (PID) controller. Tuning of PID controllers for the achievement of dynamic performance. Systems stability. Algebraic criteria for stability assessment. The Rooth-Hurwitz criterion. The continuous-fraction criterion. Graphical criteria for stability assessment. The Nyquist criterio. Bode diagrams. Nichols chart. Root locus. Tuning of PID controllers to assess stability. Advanced tuning methods for PID controllers. Tuning based on the relay-feedback experiment. Controller auto-tuning. Lead-lag compensators. Predictive control. Synergism of industrial controllers. Digital implementation of process control algorithms. Practical application of feedback control. Performance of feedback control systems. Elements and devices for process automation. Regulators, transmitters, converters and relays. Proximity actuators. Actuators. Control valves. Servomotors. Variable speed drives. Flow, pressure, level and temperature regulators. Programmable logic controllers and other control logic devices. Applications of automatic control to the field of Biosystems Engineering.
5. ELECTRONICS AND MICROPROCESSORS (8 th Semester)
Course Syllabus : Introduction to Electronics. Semiconductors. Energy zones and transport phenomena in semiconductors. Diodes. Diode circuits. Bipolar junction transistor (BJT). The BJT as a switch. The BJT as an amplifier. Field effect transistor (FET). Operational amplifiers. Analog electronic circuits. Differential amplifiers and multi-stage amplifiers. Frequency response. Feedback. Output stages and power amplifiers. Analog integrated circuits. Signal generators and waveform generation circuits. Oscillators. Analog filters. MOS-based digital electronic circuits. Digital filters. Bipolar digital circuits. Boole algebra and Karnaugh tables. Gates. Synchronous and asynchronous sequential circuits. Locking circuits. Flip-Flops. Adders. Encoders. Decoders. Counters. Registers. Shifters. Multiplexers. Demultiplexers. Analog to Digital (A/D) and Digital to Analog (D/A) converters. Memories. Microprocessors. Microprocessor architecture. Elementary microprocessor programming.
6. INFORMATION TECHNOLOGY IN AGRICULTURE (9 th Semester)
Course Syllabus : Introduction to MATLAB and Lab-View software packages. Computer-based distributed control systems. Digital control. Embedded systems. Software techniques to embed cones in to systems. 8 bit microcontrollers. Memory organization. Design of target board. Interfacing techniques. Timers. I/O devices. Interrupts. Serial interface. Processors in embedded systems. Data converters, DMA, SPI, PWM, WDT. Serial and parallel memories. Synchronous and asynchronous communication. Software development tools for embedded systems. PIC and IVR microcontrollers. Introduction to C programming. C programming for microcontrollers. Data communication and networking. Transmission of digital data. Network basics. Network hardware. Network protocols. Network operating systems. Network services. Control networks and sensor networks. Real time operating systems. Real time control systems. Supervisory control and data acquisition/management systems. Knowledge-based nad Experience-based control and management systems. Digital signal processing. A/D and D/A converters. Signal modulation and demodulation. Digital image processing. Image perception. Image sampling and quantization. Image enhancement. Image filtering and restoration. Image analysis and computer vision. Image compression.
7. APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE (9 th Semester)
Course Syllabus : Introduction to Intelligence and Artificial Intelligence. Problem solution. Problem description and solution search. S???t??? search algorithms. Evolutionary algorithms. Genetic programming. Meta-Heuristic algorithms. Photosynthetic algorithm. Ant colony optimization and particle swarm optimization. Basic principles of knowledge and reasoning representation. Inference mechanisms. Reasoning types. Semantic networks, frames, objects and scripts. Representation using rules. Rule systems. Deduction systems. Uncertainty. Bayesian probability networks. Inference networks. Fuzziness. Fuzzy sets. Fuzzy variables and fuzzy rules. Membership functions. Fuzzy reasoning and fuzzy control. Basic principles of planning. Advanced techniques for planning. Machine learning and learning algorithms. Artificial Neural Networks. Learning algorithms for neural networks. Feedforward Neural Networks. Hopefield Networks. Recurrent neural networks. Neuro-fuzzy control. Knowledge discovery in databases. Characteristics, structure and operation of Knowledge Systems. Model-based reasoning. Qualitative reasoning. Case-based reasoning. Knowledge technology. Knowledge acquisition and modelling. Classification. Classification methods. Fault detection and troubleshooting. Intelligent agents. Multi-agent systems. Semantic Web. Ontologies. Web services. Applications in bio-process modelling. Climate management and control. Hydroponics management. Fault detection and diagnostics. Optimal and integrated system design.
8. PRECISION AGRICULTURE AND ROBOTICS (9 th Semester)
Course Syllabus : Introduction and basic concepts of Precision Agriculture. Positioning systems, yield monitoring and mapping. Sampling in space and time. On-farm experiments. Spatial variability. Introduction to GIS. Remote sensing. Site-specific farm management. Development of management zones. Global positioning systems. Variable rate technologies. Introduction to robotics. Coordinate transformations. Forward and inverse kinematics. Motion planning. Dynamics of robots. Robot control. Robotic sensors. Machine vision. Robotic intelligence. Mobile robots and autonomous vehicles. MEMS and micro-robotics. Applications of robotics in agriculture. Robotic agricultural vehicles and tractors. Fruit picking robots. Robots in the Food industry.
9. MEASUREMENT AND CONTROL SYSTEMS IN THE FOOD INDUSTRY (9 th Semester)
Course Syllabus : Instrumentation and measurement if the Food Industry. Basic concepts of measurement systems. Sensors. Performance characteristics of sensors. Temperature sensors. Optical Sensors. Electric and magnetic sensors. Mechanical sensors. Acoustic sensors. Chemical sensors. Radiation sensors. Errors of measurement systems. Calibration. Amplifiers. Signal transmitters. Digitalization. Computer-based measurement systems. Introductory concepts of automatic control. Review of basic mathematical tools. Principles of mathematical modelling. Macroscopic patterns of processes. Dynamic behaviour of typical processes. Processes with dead time. Feedback control. The feedback loop. Stability. The three-term (PID) controller. PID controller tuning. Controller auto-tuning. Synergism of industrial controllers. Digital implementation of process control algorithms. Elements and devices for process automation. Regulators, transmitters, converters and relays. Proximity actuators. Actuators. Control valves. Servomotors. Variable speed drives. Flow, pressure, level and temperature regulators. Programmable logic controllers and other control logic devices. Applications of automatic control in the Food Industry.
B. POSTGRADUATE COURSES
1. ADVANCED ELECTRICAL TECHNOLOGY & POWER ELECTRONICS (1 st Semester)
Course Syllabus : Elements of electric machines. Generators and motors. Conventional electric generators. Synchronous and asynchronous (inductive) generators. Standby generator sets. Introduction to wind generartors. Types and characteristics of wind generators. Wind generators without gearbox. Autonomous operation of wind generators. Power maximization in wind generators. Operation principles of photovoltaic (PV) generators. Types of photovoltaic devices. Autonomous operation of PV generators. Daily dependence of operation of PV generators. Power maximization in PV generators. Energy storage. Principles of Power Electronics. Basic semiconductor physics and technology . The pn junction. Power switching devices and their static electrical characteristics. Electrical ratings and characteristics of power semiconductor switching devices. Cooling of power switching semiconductor devices. Load, switch and commutation considerations. Driving transistors and thyristors. Protecting diodes, transistors and thyristors. Switching-aid circuits with energy recovery. Device series and parallel operation, protection and interference. Naturally commutating AC to DC converters – Uncontrolled rectifiers. Naturally commutating AC to DC converters – Controlled rectifiers. AC voltage regulators . DC choppers . DC to AC inverters-Switched mode. DC to AC inverters-Resonant mode. DC to DC converters-Switched mode. DC to DC converters-Resonant mode. HV direct current transmission. FACTS Devices and custom controllers. Inverter grid connection for embedded generation. Energy sources and storage-Primary sources. Energy sources and storage-Secondary sources. Capacitors . Resistors. Soft magnetic materials -Inductors and transformers. Hard magnetic materials-Permanent magnets. Contactors and relays.
2. DESIGN OF GREENHOUSE ELECTROMECHANICAL EQUIPMENT (1 st semester)
Course Syllabus : Heating generation and co-generation systems. Heating distribution systems. Heating valves and gates. Thermal shading. Design of thermal circuits. Greenhouse irrigation systems. Substrates and irrigation application modes. Open and closed hydroponics systems. Control of irrigation amount. Equipment for the upgrading of available water and of recycling water. Calculations and design. Equipment and operation of Nutrient Film Technique based hydroponics. Ventilation systems. Passve and dynamic ventilation. Operation modes. Discetized, staged and continuous ventilation. Special limit conditions. Winter operation. Summer operation. Cooling systems. Mist-fog and their generation modes. Problems arising from the use of saline water. Wet-pad and its mode of operation. Shading courtain and its mode of operation. Equipment for pest control. Harvesting equipment. Lighting equipment. Periodic lighting. Equipment of nurseries. Greenhouse robotic systems. Intensive crop production. Plant factories. Electrical installations. Wires. Codes for electrical equipment. Greenhouse root and shoot environment. Supervisory control and data acquisition systems for greenhouse management. Computer Integrated Management and i ntelligent c ontrol of g reenhouses .
3. SPECIAL ASPECTS OF ELECTROMECHANICAL EQUIPMENT AND AUTOMATION IN IRRIGATION (1 st semester)
Course Syllabus : Elements of irrigation networks. Main irrigation techniques. Sprinkler Irrigation Design. Rotating head or revolving sprinkler systems. Perforated pipe systems. Portable, semi-portable, semi-permanent, sold set and permanent sprinkler systems. Components of a sprinkler irrigation system. Pump units. Main/submain and lateral tubings. Couplers. Sprinkler heads. Valves, bends, plugs and risers. Water meters. Pressure gauges. Tees, reducers, elbows, hydrants, butterfly valves. Fertilizer applicators. Rules for sprinkler system design. Selection of the appropriate sprinkler system. Constraints in application of sprinkler irrigation. Operation and maintenance of sprinkler systems. Troubleshooting. Drip Irrigation Design. Isolation valves. Control valves. Emergency Shut-off valves. Zone control valves (Standard glob valve, anti-siphon valve, indexing valves, operation methods). Valve body materials. Valve installation and wiring. Backflow preventers (Atmospheric vacuum brakers, pressure vacuum brakers, double-check type backflow preventers, reduced pressure type backflow preventers, pressure losses in backflow preventers). Pressure regulators and pressure reducing valves. Drip irrigation emmiters and their types (Long-path emmiter, soaker hose, porous pipe, drip tape, laser tubing, short-path emmiters, turbulent-flow emmiters, vortex emmiters, diaphragm emmiters, adjustable flow emmiters, mechanical emmiters, driplines, dripperlines). Pressure compensated vs. Non-pressure compensated emmiters. Flow characteristics of drip irrigation emmiters. Installation. Spitting and multi-outlet emmiters. Drip emiiter spacing. Pipes and selection of pipe size. Drip systems for slop and hillsides. Gravity flow and rain barrel drip systems. Automation systems for irrigation networks. Centralized control. Remote operation and remote control. Automatized network management. Electrical installations. Wires. Codes for electrical equipment.
4. ENVIRONMENTAL AND PROCESS CONTROL (2 nd Semester)
Course Syllabus : Introduction. Modelling and analysis of control systems. Transfer function and state-space modelling. The PID controller. Proportional-integral-derivative (PID) enhancements. Review of continuous-time Internal Model Control (IMC), and IMC-based PID. Cascade, ratio and feedforward control. Inferential control, override control/selective control, scheduling controller tuning and implementation issues. Other advanced control techniques: Deadtime compensation (the Smith Predictor). Multi-input multi-output (MIMO) control Systems. Process and control loop interactions, control loop, pairings. The relative gain array (RGA) method. Introduction to singular value analysis. Decoupling control systems and multivariable control techniques. Digital control systems: Introduction, Z-transforms, development of discrete time models, dynamic response of discrete time systems, discrete time control algorithms, closed loop analysis and digital control system implementation. Implementation of digital PID algorithms. Identification of discrete models for digital control: ARMA and ARMAX models. Digital model-based control: IMC and Dahlin's method. Model predictive control. Analysis of multivariable systems. Adaptive Control. Model reference adaptive control. Direct adaptive control. Nonlinear control. Nonlinear adaptive control. The backsteping approach. Nonlinear damping. Lyapunov techniques for adaptive control. Optimal control design. LQR problem. State estimation, Kalman filtering, Separation principle and LQG controller design. Robust control: Robust stability and robust performance. H 2 and H ¥ control. Fuzzy control. Artificial neural networks for process identification and control. Supervisory control and data acquisition systems. Programmable logic controls : programming languages, hardware and system sizing, plc installation, maintenance & troubleshooting. Environmental control of greenhouses: Techniques for temperature, humidity and CO 2 control. Ventilation control systems for greenhouses. Environmental control of animal buildings: Techniques for temperature, humidity and odour control. Ventilation control of livestock buildings. Control of hydroponics systems: pH and electrical conductivity control.
5. ADVANCED ANALYTICAL MEASUREMENTS (2 nd Semester)
Course Syllabus : Analytical measurements and their importance. Validation and Uncertainty. Errors in analytical measurements. Statistics of repeated measurements. Propagation of errors. Significance tests. Comparison of an experimental mean with a known value. Comparison of two experimental means. Paired t-test. One-sided and two-sided tests. F-test for the comparison of standard deviations. Confidence intervals. Outliers. Analysis of variance. Comparison of several means. The arithmetic of ANOVA calculations. The chi-squared test. Testing for normality of distribution. The quality of analytical measurements. Sampling. Separation and estimation of variances using ANOVA. Quality control methods. Stewhart charts. Establishing the process capability. Average run length: cusum charts. Proficiency testing schemes. Collaborative trials. Uncertainty. Acceptable sampling. Calibration methods in instrumental analysis. Calibration graphs in instrumental analysis. The product-moment correlation coefficient. The line of regression of y on x. Errors in the slope and intercept of the regression line. Calculation of a concentration and its random error. Limits of detection. The method of standard additions. Use of regression lines for comparing analytical methods. Weighted regression lines. Intersection of two straight lines. ANOVA and regression calculations. Curve fitting. Outliers in regression. Non-parametric and robust methods. The median: initial data analysis. The sign test. The Wald-Wolfowitz runs test. The Wilcoxon signed rank test. Simple tests for two independent samples. Non-parametric tests for more than two samples. Rank correlation. Non-parametric regression methods. Robust methods. Robust regression methods. The Kolmogorov test for goodness of fit. Experimental design and optimization. Randomization and blocking. Two-way ANOVA. Latin squares and other designs. Interactions. Factorial versus one-at-a-time design. Factorial design and optimization. Optimization: basic principles and univariate methods. Optimization using the alternating variable search method. The method of steepest ascent. Simplex optimization. Simulated annealing. Multivariate analysis. Initial analysis. Principal component analysis. Cluster analysis. Discriminate analysis. K-nearest neighbour method. Disjoint class modelling. Multiple regression. Principal component regression. Multivariate regression. Partial least squares regression. Multivariate calibration. Artificial neural networks.