Control Philosophy Research Articles

Intelligent Traffic Control, Gathering and Monitoring Traffic Data Using CCTV Images

Although the number of automobiles on the road currently is more than it was a few years ago, the infrastructure of roads and traffic systems has not kept up with this expansion, which makes handling traffic challenging. This mismatch causes hence a lot of traffic congestion, crowding, and pollution. All throughout the globe, handling increasing traffic is a major challenge. Operations depend on traffic management in great part. It has to do with planning, running, and purchasing the necessary transportation services—cars, trucks, railroads, boats—that carry commodities and vehicles. Intelligent Traffic Systems (ITS) might be a fantastic approach to address these types of issues by means of modern technology. Given this, traffic control philosophy has to change to accommodate smart cities—which use computer vision techniques to run an adaptive traffic management system depending on CCTV image stream analytics. The adaptive traffic management system detects and counts vehicles accurately. In smart cities, where traffic lights must be automated based on vehicle density, this technique is particularly helpful. This study investigated intelligent traffic control, gathering and monitoring traffic data through using CCTV images. It embodies possible risks in the implementation state, benefits, challenges, as well as the future prospect of ITS.

Intelligent control algorithms to ensure the flight safety of aerospace vehicles

An overview of the architectures, functions and algorithms of aircraft-type aerospace vehicles equipped with fly-by-wire (FBW) digital integrated control systems (ICS) is given. The ICS has a hierarchical architecture, including the primary, backup and emergency control systems with a sophisticated control reconfiguration logic in the event of failures. Digital control computers have dissimilar redundancy of equipment and software. At the atmospheric flight stage, integrator control laws provide the specified control characteristics, flight envelope protection, automatic trim of vehicle and crew workload alleviation. Further integration of manual and automatic control, implementation of the control philosophy as a continuation of the pilot's actions, more intellectual control system and human-machine interface, use of multiple control surfaces to ensure optimal vehicle configuration and alleviate structural loading together with basic control functions are considered as promising areas for ICS improvement.

Better Living through Political Engineering

Much has been written about the philosophy of social control, particularly as it developed from the end of the nineteenth century to the early 1920s. Yet little if any appreciation has been given to the work of James MacKaye and Helen Sumner in promoting the program of political engineering and their efforts at establishing to this end an Institute of Political Engineering. This essay will examine the philosophy of James MacKaye and the creation of the institute that was to fulfill his mission, and it will highlight the important contribution of Helen Sumner in its creation.

Design of an Advanced Optimal Fuzzy Controller For a Binary Distillation Column

The most common control philosophy followed in the chemical process industries is the SISO system using the conventional PID controller algorithms. One drawback is relying on models for both control and design work in Chemical process industries (CPI) is that many problems are very complex and accurate models are difficult, if not impossible to obtain. To overcome these problems, it will be helpful to apply techniques that use human judgment and experience rather than precise mathematical models, which in the major cases deduced from the linearization of the system and simplification hypothesis. The fuzzy logic systems are capable of handling complex, nonlinear systems using simple solutions. However, obtaining an optimal set of fuzzy membership functions is not an easy task. In this chapter a solution based on artificial intelligence is proposed to improve the control of a binary distillation column. The solution is based on the use of the advantages of both fuzzy logic and genetic algorithms. The fuzzy logic is used as a supervisory PI controller that is a simple PI controller that generally used in controlling distillation columns with parameters deduced from the fuzzy supervisor. The membership functions shape is deduced by using research algorithms based on hierarchical genetic algorithms. The results show that the Fuzzy supervisory PI controller provide an excellent tracking toward set point change.

Development and experimental validation of a hydraulic design and control philosophies for 5th generation district heating and cooling networks

Sector coupling and energy sharing are key elements in effectively decarbonising the thermal grid. 5th Generation District Heating and Cooling (5GDHC) provides a system for combining heating and cooling via an ambient temperature network. A main design challenge for 5GDHC is establishing a control regime that allows flow bidirectionality and energy synergies between heating and cooling. This work develops and experimentally validates a 5GDHC system wide hydraulic design and two fitting control strategies on a small scale. One has fixed grid return temperatures (TGridFix) while the other free floating grid temperatures (TGridFloat). Both feature decentralised variable speed pumping and a centralised passive balancing unit aimed at alleviating control instabilities arising from pump hunting. Experiments showed that TGridFix demonstrates slightly higher electrical consumption for the booster heat pump (Seasonal Coefficient of Performance of 3.84 compared to 4.16 for 20 h of operation) due to a mismatch between the evaporator and the grid temperature difference. Overall, TGridFix can lead to low prosumer interaction and better system wide predictability. Further considerations on generalisability of findings and full-scale implementations are highlighted. This works presents a set of detailed and experimentally validated control philosophies for 5GDHC systems, elucidating a key system implementation challenge.

Development and application of closed-loop-oriented intelligent control system for blast furnace air volume addition or reduction

Adjusting the upper and lower parts is an important means to ensure stable operation of blast furnaces. It is a common operation method to adjust the smelting state of the blast furnace by adjusting the air volume. Most of the domestic blast furnace air volume increase and decrease operations are confirmed by manual experience, and it is difficult to realize intelligent automatic control. This paper presents an intelligent control system for regulating air volume in blast furnaces, based on operational logic, expert knowledge, fundamental theories, and other relevant information. The system enables automatic analysis of the blast furnace's state and intelligent reasoning of the foreman's operational methods, laying the foundation for achieving closed-loop control. The system unifies the control philosophy and stabilizes the control methods for regulating air volume in blast furnaces. This achieves standardization of operation and proceduralization of cause analysis. The system enhances adaptability by creating an information feedback mechanism, increasing acceptance among blast furnace operators, and continuously resolving various anomalies in practical applications. The system currently maintains a true hit rate of over 95%, enabling effective reduction of operational misjudgments, intelligent control of airflow adjustment, and promotion of stable and smooth blast furnace operation.

Modeling kinematic variability reveals displacement and velocity based dual control of saccadic eye movements.

Noise is a ubiquitous component of motor systems that leads to behavioral variability of all types of movements. Nonetheless, systems-based models investigating human movements are generally deterministic and explain only the central tendencies like mean trajectories. In this paper, a novel approach to modeling kinematic variability of movements is presented and tested on the oculomotor system. This approach reconciles the two prominent philosophies of saccade control: displacement-based control versus velocity-based control. This was achieved by quantifying the variability in saccadic eye movements and developing a stochastic model of its control. The proposed stochastic dual model generated significantly better fits of inter-trial variances of the saccade trajectories compared to existing models. These results suggest that the saccadic system can flexibly use the information of both desired displacement and velocity for its control. This study presents a potential framework for investigating computational principles of motor control in the presence of noise utilizing stochastic modeling of kinematic variability.

A Distributed Model Predictive Control Strategy for Constrained Multi-Agent Systems: The Uncertain Target Capturing Scenario

In this paper, a distributed control architecture is presented for addressing the target capturing problem of a multi-agent system whose dynamics is described by double integrator models subject to bounded disturbance effects. Starting from novel kinematic models used as reference trajectories, the aim consists in driving the multi-agent system within the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">containment</i> region without entering the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">distancing</i> one and, whenever necessary, there remaining confined. The underlying control problem has been tackled by means of model predictive control arguments. In particular, two different distributed strategies have been developed, and adequately switched to each other, in order to guarantee constraint satisfaction within the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">capturing</i> region despite any disturbance realization. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper proposes a methodological solution for dealing with the capturing problem for multi-agent systems operating in uncertain environments where the target is defined by the ring resulting from the distancing and containment ellipsoids. Differently from the existing literature, the proposed approach combines into a unique framework properties coming from potential fields theory and distributed model predictive control philosophy. It is interesting to put in light that the underlying control strategy allows the users to face surveillance and rescue operations, to cite a few, in computational affordable way due to the required memory resources because most of computations can be straightforwardly moved in the off-line phase.

Engineering AI for provable retention of objectives over time

AbstractI argue that ensuring artificial intelligence (AI) retains alignment with human values over time is critical yet understudied. Most research focuses on static alignment, neglecting crucial retention dynamics enabling stability during learning and autonomy. This paper elucidates limitations constraining provable retention, arguing key gaps include formalizing dynamics, transparency of advanced systems, participatory scaling, and risks of uncontrolled recursive self‐improvement. I synthesize technical and ethical perspectives into a conceptual framework grounded in control theory and philosophy to analyze dynamics. I argue priorities should shift towards capability modulation, participatory design, and advanced modeling to verify enduring alignment. Overall, I argue that realizing AI safely aligned throughout its lifetime necessitates translating principles into formal methods, demonstrations, and systems integrating technical and humanistic rigor.

A low voltage microgrid protection scheme using digital instrument transformers

AbstractModern power systems have several measurement devices for reliable, safe, and improved operation and control. Due to the high infiltration of inverter‐based resources, protecting modern power systems has become challenging. This paper proposes a new protection scheme based on the computation of ‘discrepant impedance’ using real‐time protocol services for data exchange. The sampled values of voltages and currents are transmitted to a central processing unit to implement the protection scheme. With the development of digital instrument transformers (IEC 61869‐9), the current and voltage samples are directly interfaced wired or wirelessly to the IEC 61850‐9‐2 process bus. The proposed protection scheme is validated with grid forming and grid following inverters on Consortium for Electric Reliability Technology Solutions (CERTS) microgrid network using a real‐time digital simulator. The protection scheme is independent of the type of energy sources and their control philosophy, operation modes and topology of the microgrid network.

Implications for control systems in highly volatile energy markets: Using a high purity distillation electrification case study

The transition to increasingly renewable electricity grids and the electrification of industrial processes are two recent developments promising to be potential solutions towards net zero in industrial production processes. Generally, grid electricity is perceived as a stable and reliable resource that can be accessed on demand. However, that is not always the case for large industrial users (100 MW+), and a key future challenge that must be overcome is the inherent uncertainty of the electricity supply by renewable sources, as well as in pricing. In methanol production, the concept of using electrolysis and CO2 capture is being explored as a way of replacing reforming to produce syngas for “green” methanol production. With the omission of the reforming process which supplies energy as steam for the process, there is now a need to electrify the affected downstream unit operations. Distillation is a key unit operation in chemical operations that consumes large amounts of energy for reboiler duty and holds the key to making on-specification AA-grade methanol, a precursor chemical. With the volatility of the electricity market, hence supply, these columns must be able to withstand a sudden large reboiler duty drop. This paper developed a novel process operations and control principle to allow for the flexible operation of a high-purity methanol distillation column in volatile energy markets. At its core is the concept of using a distillation column as a “process battery”. Results obtained from a validated process simulation show that the novel “process battery” operations principle can withstand a supply-side change as great as 75% within a time span of 5 min without breaking complex quality and performance specifications of the column. This control philosophy is a major departure from the traditional process control and operating regimes that are focused on maintaining steady operations under all conditions.

Supervised reinforcement learning based trajectory tracking control for autonomous vehicles

Recent developments in autonomous vehicle technologies and applications gain a lot of interest by the public, as the popularity of both driver assistance and automated driving systems increase. One of the most promising aspect of the autonomous vehicle compared to conventional human driven vehicle is the increased level of safety. Machine learning techniques enables to achieve fast and efficient control actions compared to model based techniques. However, the advantages of a more conservative model based controller are their better robustness properties. In this paper a synergy of the two control philosophy is presented through a trajectory tracking control design for autonomous vehicles. A supervised reinforcement learning (RL) control method is introduced, where a robust Linear Parameter Varying (LPV) controller supervises the operation of the trained RL agent. Thus, in case sensor noise is detected, the guaranteed stability LPV controller takes over the steering control action. In order to demonstrate the operation of the proposed method, three different simulations have been evaluated and compared in CarSim simulation environment.

Exploring the interdependence between control and protection philosophies in inverter integrated power system: A case study on directional relaying schemes

The potential impacts of the inverter-interfaced renewable energy resources (IIRERs) on the performance of sequence-based directional relaying schemes (SBDRS) have been investigated in this paper. The directional overcurrent relays such as 67POS, 67NEG, 67ZERO and 32Q have been considered for the investigation. CIGRE-14 bus system with IIRERs along with detailed modeling of inverter control scheme (with and without grid codes) and SBDRS have been done in the PSCAD environment. The mathematical analysis and circuit realization of the IIRERs have been attempted in the paper. The exclusive fault characteristics exhibited by IIRERs cause the conventional SBDRS to mal-operate. Significant change in levels of sequence currents and angular relationships between sequence voltages and currents during faults contributes to relay's unpredictable behavior. The comparative study based on different fault types, fault resistances and interconnecting transformer connections have also been done. The study reveals the impact of non-generalized angular differences between positive sequence voltage and current at the inverter terminal on performance of 67POS. It is found that 67NEG and 32Q mal-operated for all types of unbalanced faults while the 67ZERO can be utilized for grounded fault with delta-star grounded connection of interconnecting transformer.

Energy Recovery Maximisation Modelling Subject to Constrained Cooling

The primary heat rejection cycle, which is critical for the stability and integrity of the metal production process and equipment, involves the transfer of heat from flue gas to a fluid circulated through a gas-cooler. The rate of heat transfer from the flue gas is influenced by several parameters, including the temperature of the cooling fluid. Heat transfer rates that are too high or too low can negatively impact equipment’s life, emphasising the need for a temperature operational envelope in the cooling fluid prior to entering the gas-cooler. Rejected heat is used for power generation, transferred to the environment, or both. This study examines the impact of control philosophies on both temperature and power generation, while maintaining the exit temperature within the desired range as the highest priority. A more advanced philosophy that combines bypass control with feedforward parameters can maintain temperatures within safe operating limits at all times, while improving the power generation, compared to a typical works approach which is used as a baseline. This study presents a formulation that increased power generation from an average of 6.11 MW for a typical works philosophy to 10.68 MW, while maintaining the temperature within the operating temperature envelope.

Off-design of a CO2-based mixture transcritical cycle for CSP applications: Analysis at part load and variable ambient temperature

This work focuses on the off-design analysis of a simple recuperative transcritical power cycle working with the CO2 + C6F6 mixture as working fluid. The cycle is air-cooled and proposed for a state-of-the-art concentrated solar plant with solar salts as heat transfer fluid in a hot region, with a cycle minimum and maximum temperature of 51 °C and 550 °C at design conditions. The design of each cycle heat exchanger (primary, recuperator and condenser) is carried out in MATLAB with referenced models and the turbine designed in CFD, providing performance maps adopted by the cycle operating in sliding pressure. The off-design of the cycle is developed with a routine simulating the thermodynamic conditions of the cycle at variable ambient temperature and thermal inputs down to 40 % of the nominal value. The results show that the cycle can efficiently run in a wide range of part load conditions and ambient temperatures, from around 0 °C to over 40 °C, with net electric cycle efficiencies from 45 % to 36 %: according to the control philosophy proposed, the condenser fans are fixed at design speed, while the cycle operates in sliding pressure, when is possible. The results evidence the flexibility and good performances of the proposed system in various operating conditions.

Optimal control of mineral processing plants using constrained model predictive static programming

The model predictive static programming (MPSP) technique, which is extended recently to incorporate applicable state and control constraints, operates on the philosophy of nonlinear model predictive control (NMPC). However, it reduces the problem into a lower-dimensional problem of control variables alone, thereby enhancing computational efficiency significantly. Because of this, problems with larger dimensions and/or increased complexity can be solved using MPSP without changing the computational infrastructure. In this paper, the MPSP technique with applicable constraints is applied to two challenging control problems in the mineral processing industry: (i) a single-stage grinding mill circuit model, and (ii) a four-cell flotation circuit model. The results are compared with a conventional nonlinear MPC approach. Comparison studies show that constrained MPSP executes much faster than constrained MPC with similar/improved performance. Therefore, it can be considered a potential optimal control candidate for mineral processing plants.

A new protection scheme for feeders of microgrids with inverter-based resources

Due to the unavailability of a suitable relay for microgrid protection, various utilities are fitting available IEDs for the protection of microgrids. At present, microgrid protection is achieved using a combination of conventional numerical relays. These numerical relays are not suitable for all kinds of microgrid architectures and do not provide complete protection with inverter-based generators. Since these relays were designed considering the fault characteristics of synchronous generators, they fail to respond to the fault characterized by inverter-based generators. This paper proposes a new protection technique that is independent of the type of generating sources, control philosophy of inverters as well as microgrid architecture. Simulations are performed using PSCAD/EMTDC and performance of the protection scheme is also evaluated in real-time using RTDS. Pertinent results are presented which demonstrate the effectiveness of the proposed scheme.

Adaptive neural network based compensation control of quadrotor for robust trajectory tracking

SummaryNeural network (NN) methods have become increasingly efficient and applicable in control. This article presents a novel nested control strategy based on adaptive radial basis function neural networks (RBFNN) and NN supervised control embedded with integrator back stepping (IBS) for a robust position and attitude trajectory tracking of quadrotor aerial robot in presence of modeling uncertainties, sensing noise, and external bounded disturbance. The control philosophy is derived from the decentralized inverse dynamics, where the adaptive RBFNN is adopted for the outer loop to approximate the unknown external disturbance, and adaptively compensate for their effect. In conjunction with a supervised control that stabilizes the attitude in the inner loop by adaptively compensating the unknown and unmodeled uncertainties, avoiding initial instability of the attitude during NN convergence. Furthermore, noise is attenuated by an adaptive extended Kalman filter. Stability analysis was elaborated using Lyapunov stability theory. Simulation of adaptive RBFNN control philosophy proved robustness and effectiveness compared to proportional integral derivative, IBS, and offline decentralized convolution neural network algorithms as it generates the control law by guarantying a fast convergence of parameters, better external disturbance compensation, and noise attenuation. The proposed scheme of robust tracking was validated.

UNDERSTANDING THE IMPLICATIONS OF TAXATION POLICY IN PAKISTAN: A CASE OF FAILED MULTI-STAKEHOLDER INITIATIVES

Pakistan has multifaceted taxation difficulties in tobacco control and administration. Tobacco taxation issues include industry pressures, blaming the unauthorized market, and revenue theft at the collecting point. To avoid tax evasion and produce taxes on a consistent basis, a simple taxation system is required and suggested by related stakeholders for the execution of policies. A huge amount of tax is collected from this sector by the revenue collection agencies adding big portion in national deposits. On the other hand, tobacco usage is responsible for greatly raising the economic burden, greater health expenditures, and indirect costs associated with premature death, disability owing to tobacco-related illnesses, and loss of productivity. Effective tobacco taxes minimize various externalities by reducing consumption, legal consumption patterns and prevalence, as well as contributing to a reduction in government spending on health care expenditures directly due to cigarette smoking diseases. The philosophy of tax administration and control is creating policy conflict between different public institutions in Pakistan. The revenue collecting institutions believe on lowering the tax rates to overcome the illicit tobacco manufacturing and sales while health institutes believes on coercive measures and high tax rates to avoid and control the tax consumption. This paper will discuss the policy conflict, control mechanism, institutes tax philosophy, tax mechanism, and best practices around the globe to avoid policy conflict and better governance.

Enhance Power Quality through Series Compensation in Power System

Abstract: The power quality requirement is one of the most important issues especially with the introduction of sophisticated device whose performance is very sensitive to the quality of power supply. Power quality problem is an occurrence manifested as a non standard voltage, current or frequency that results in failure of end user equipment. One of the major problem deal with sag and harmonics .To solve this problem series compensation is used to improve power quality of an isolated power system is considered. The role of compensator not only mitigates voltage sag but also reduces harmonics due to presence of nonlinear load in the network. In this paper series compensation is proposed and principle of harmonics mitigation is explain and the compensation strategies and control philosophy used in series compensation is explain. The isolated power system model is simulated in matlab Simu link software and simulation result shows the reduce harmonics and thus improve power quality of the isolated power system